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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Sat, 17 Nov 2012 06:47:21 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/17/t13531528820o5ho9kpa0wtdji.htm/, Retrieved Sun, 28 Apr 2024 18:40:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=190063, Retrieved Sun, 28 Apr 2024 18:40:01 +0000

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User-defined keywords

Estimated Impact

114

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [] [2012-11-17 11:47:21] [00ffffaac852cc6d7cd42123567c45a2] [Current]
-   PD      [Multiple Regression] [] [2012-11-19 12:16:25] [6808ef3204f32b6b44f616bd4c52b0ae] 
- R PD        [Multiple Regression] [] [2012-11-19 16:51:03] [af1abf97761ac0cf7dc5c55ff51240a9] 

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Dataseries X:

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10.708	12.3	23	154.25	67.75	36.2	93.1	85.2	94.5	59.0	37.3	21.9	32.0	27.4	17.1
10.853	6.1	22	173.25	72.25	38.5	93.6	83.0	98.7	58.7	37.3	23.4	30.5	28.9	18.2
10.414	25.3	22	154.00	66.25	34.0	95.8	87.9	99.2	59.6	38.9	24.0	28.8	25.2	16.6
10.751	10.4	26	184.75	72.25	37.4	101.8	86.4	101.2	60.1	37.3	22.8	32.4	29.4	18.2
10.340	28.7	24	184.25	71.25	34.4	97.3	100.0	101.9	63.2	42.2	24.0	32.2	27.7	17.7
10.502	20.9	24	210.25	74.75	39.0	104.5	94.4	107.8	66.0	42.0	25.6	35.7	30.6	18.8
10.549	19.2	26	181.00	69.75	36.4	105.1	90.7	100.3	58.4	38.3	22.9	31.9	27.8	17.7
10.704	12.4	25	176.00	72.50	37.8	99.6	88.5	97.1	60.0	39.4	23.2	30.5	29.0	18.8
10.900	4.1	25	191.00	74.00	38.1	100.9	82.5	99.9	62.9	38.3	23.8	35.9	31.1	18.2
10.722	11.7	23	198.25	73.50	42.1	99.6	88.6	104.1	63.1	41.7	25.0	35.6	30.0	19.2
10.830	7.1	26	186.25	74.50	38.5	101.5	83.6	98.2	59.7	39.7	25.2	32.8	29.4	18.5
10.812	7.8	27	216.00	76.00	39.4	103.6	90.9	107.7	66.2	39.2	25.9	37.2	30.2	19.0
10.513	20.8	32	180.50	69.50	38.4	102.0	91.6	103.9	63.4	38.3	21.5	32.5	28.6	17.7
10.505	21.2	30	205.25	71.25	39.4	104.1	101.8	108.6	66.0	41.5	23.7	36.9	31.6	18.8
10.484	22.1	35	187.75	69.50	40.5	101.3	96.4	100.1	69.0	39.0	23.1	36.1	30.5	18.2
10.512	20.9	35	162.75	66.00	36.4	99.1	92.8	99.2	63.1	38.7	21.7	31.1	26.4	16.9
10.333	29.0	34	195.75	71.00	38.9	101.9	96.4	105.2	64.8	40.8	23.1	36.2	30.8	17.3
10.468	22.9	32	209.25	71.00	42.1	107.6	97.5	107.0	66.9	40.0	24.4	38.2	31.6	19.3
10.622	16.0	28	183.75	67.75	38.0	106.8	89.6	102.4	64.2	38.7	22.9	37.2	30.5	18.5
10.610	16.5	33	211.75	73.50	40.0	106.2	100.5	109.0	65.8	40.6	24.0	37.1	30.1	18.2
10.551	19.1	28	179.00	68.00	39.1	103.3	95.9	104.9	63.5	38.0	22.1	32.5	30.3	18.4
10.640	15.2	28	200.50	69.75	41.3	111.4	98.8	104.8	63.4	40.6	24.6	33.0	32.8	19.9
10.631	15.6	31	140.25	68.25	33.9	86.0	76.4	94.6	57.4	35.3	22.2	27.9	25.9	16.7
10.584	17.7	32	148.75	70.00	35.5	86.7	80.0	93.4	54.9	36.2	22.1	29.8	26.7	17.1
10.668	14.0	28	151.25	67.75	34.5	90.2	76.3	95.8	58.4	35.5	22.9	31.1	28.0	17.6
10.911	3.7	27	159.25	71.50	35.7	89.6	79.7	96.5	55.0	36.7	22.5	29.9	28.2	17.7
10.811	7.9	34	131.50	67.50	36.2	88.6	74.6	85.3	51.7	34.7	21.4	28.7	27.0	16.5
10.468	22.9	31	148.00	67.50	38.8	97.4	88.7	94.7	57.5	36.0	21.0	29.2	26.6	17.0
10.910	3.7	27	133.25	64.75	36.4	93.5	73.9	88.5	50.1	34.5	21.3	30.5	27.9	17.2
10.790	8.8	29	160.75	69.00	36.7	97.4	83.5	98.7	58.9	35.3	22.6	30.1	26.7	17.6
10.716	11.9	32	182.00	73.75	38.7	100.5	88.7	99.8	57.5	38.7	33.9	32.5	27.7	18.4
10.862	5.7	29	160.25	71.25	37.3	93.5	84.5	100.6	58.5	38.8	21.5	30.1	26.4	17.9
10.719	11.8	27	168.00	71.25	38.1	93.0	79.1	94.5	57.3	36.2	24.5	29.0	30.0	18.8
10.502	21.3	41	218.50	71.00	39.8	111.7	100.5	108.3	67.1	44.2	25.2	37.5	31.5	18.7
10.263	32.3	41	247.25	73.50	42.1	117.0	115.6	116.1	71.2	43.3	26.3	37.3	31.7	19.7
10.101	40.1	49	191.75	65.00	38.4	118.5	113.1	113.8	61.9	38.3	21.9	32.0	29.8	17.0
10.438	24.2	40	202.25	70.00	38.5	106.5	100.9	106.2	63.5	39.9	22.6	35.1	30.6	19.0
10.346	28.4	50	196.75	68.25	42.1	105.6	98.8	104.8	66.0	41.5	24.7	33.2	30.5	19.4
10.202	35.2	46	363.15	72.25	51.2	136.2	148.1	147.7	87.3	49.1	29.6	45.0	29.0	21.4
10.258	32.6	50	203.00	67.00	40.2	114.8	108.1	102.5	61.3	41.1	24.7	34.1	31.0	18.3
10.217	34.5	45	262.75	68.75	43.2	128.3	126.2	125.6	72.5	39.6	26.6	36.4	32.7	21.4
10.250	32.9	44	205.00	29.50	36.6	106.0	104.3	115.5	70.6	42.5	23.7	33.6	28.7	17.4
10.279	31.6	48	217.00	70.00	37.3	113.3	111.2	114.1	67.7	40.9	25.0	36.7	29.8	18.4
10.269	32.0	41	212.00	71.50	41.5	106.6	104.3	106.0	65.0	40.2	23.0	35.8	31.5	18.8
10.814	7.7	39	125.25	68.00	31.5	85.1	76.0	88.2	50.0	34.7	21.0	26.1	23.1	16.1
10.670	13.9	43	164.25	73.25	35.7	96.6	81.5	97.2	58.4	38.2	23.4	29.7	27.4	18.3
10.742	10.8	40	133.50	67.50	33.6	88.2	73.7	88.5	53.3	34.5	22.5	27.9	26.2	17.3
10.665	5.6	39	148.50	71.25	34.6	89.8	79.5	92.7	52.7	37.5	21.9	28.8	26.8	17.9
10.678	13.6	45	135.75	68.50	32.8	92.3	83.4	90.4	52.0	35.8	20.6	28.8	25.5	16.3
10.903	4.0	47	127.50	66.75	34.0	83.4	70.4	87.2	50.6	34.4	21.9	26.8	25.8	16.8
10.756	10.2	47	158.25	72.25	34.9	90.2	86.7	98.3	52.6	37.2	22.4	26.0	25.8	17.3
10.840	6.6	40	139.25	69.00	34.3	89.2	77.9	91.0	51.4	34.9	21.0	26.7	26.1	17.2
10.807	8.0	51	137.25	67.75	36.5	89.7	82.0	89.1	49.3	33.7	21.4	29.6	26.0	16.9
10.848	6.3	49	152.75	73.50	35.1	93.3	79.6	91.6	52.6	37.6	22.6	38.5	27.4	18.5
10.906	3.9	42	136.25	67.50	37.8	87.6	77.6	88.6	51.9	34.9	22.5	27.7	27.5	18.5
10.473	22.6	54	198.00	72.00	39.9	107.6	100.0	99.6	57.2	38.0	22.0	35.9	30.2	18.9
10.524	20.4	58	181.50	68.00	39.1	100.0	99.8	102.5	62.1	39.6	22.5	33.1	28.3	18.5
10.356	28.0	62	201.25	69.50	40.5	111.5	104.2	105.8	61.8	39.8	22.7	37.7	30.9	19.2
10.280	31.5	54	202.50	70.75	40.5	115.4	105.3	97.0	59.1	38.0	22.5	31.6	28.8	18.2
10.430	24.6	61	179.75	65.75	38.4	104.8	98.3	99.6	60.6	37.7	22.9	34.5	29.6	18.5
10.396	26.1	62	216.00	73.25	41.4	112.3	104.8	103.1	61.6	40.9	23.1	36.2	31.8	20.2
10.317	29.8	56	178.75	68.50	35.6	102.9	94.7	100.8	60.9	38.0	22.1	32.5	29.8	18.3
10.298	30.7	54	193.25	70.25	38.0	107.6	102.4	99.4	61.0	39.4	23.6	32.7	29.9	19.1
10.403	25.8	61	178.00	67.00	37.4	105.3	99.7	99.7	60.8	40.1	22.7	33.6	29.0	18.8
10.264	32.3	57	205.50	70.00	40.1	105.3	105.5	108.3	65.0	41.2	24.7	35.3	31.1	18.4
10.313	30.0	55	183.50	67.50	40.9	103.0	100.3	104.2	64.8	40.2	22.7	34.8	30.1	18.7
10.499	21.5	54	151.50	70.75	35.6	90.0	83.9	93.9	55.0	36.1	21.7	29.6	27.4	17.4
10.673	13.8	55	154.75	71.50	36.9	95.4	86.6	91.8	54.3	35.4	21.5	32.8	27.4	18.7
10.847	6.3	54	155.25	69.25	37.5	89.3	78.4	96.1	56.0	37.4	22.4	32.6	28.1	18.1
10.693	12.9	55	156.75	71.50	36.3	94.4	84.6	94.3	51.2	37.4	21.6	27.3	27.1	17.3
10.439	24.3	62	167.50	71.50	35.5	97.6	91.5	98.5	56.6	38.6	22.4	31.5	27.3	18.6
10.788	8.8	55	146.75	68.75	38.7	88.5	82.8	95.5	58.9	37.6	21.6	30.3	27.3	18.3
10.796	8.5	56	160.75	73.75	36.4	93.6	82.9	96.3	52.9	37.5	23.1	29.7	27.3	18.2
10.680	13.5	55	125.00	64.00	33.2	87.7	76.0	88.6	50.9	35.4	19.1	29.3	25.7	16.9
10.720	11.8	61	143.00	65.75	36.5	93.4	83.3	93.0	55.5	35.2	20.9	29.4	27.0	16.8
10.666	18.5	61	148.25	67.50	36.0	91.6	81.8	94.8	54.5	37.0	21.4	29.3	27.0	18.3
10.790	8.8	57	162.50	69.50	38.7	91.6	78.8	94.3	56.7	39.7	24.2	30.2	29.2	18.1
10.483	22.2	69	177.75	68.50	38.7	102.0	95.0	98.3	55.0	38.3	21.8	30.8	25.7	18.8
10.498	21.5	81	161.25	70.25	37.8	96.4	95.4	99.3	53.5	37.5	21.5	31.4	26.8	18.3
10.560	18.8	66	171.25	69.25	37.4	102.7	98.6	100.2	56.5	39.3	22.7	30.3	28.7	19.0
10.283	31.4	67	163.75	67.75	38.4	97.7	95.8	97.1	54.8	38.2	23.7	29.4	27.2	19.0
10.382	26.8	64	150.25	67.25	38.1	97.1	89.0	96.9	54.8	38.0	22.0	29.9	25.2	17.7
10.568	18.4	64	190.25	72.75	39.3	103.1	97.8	99.6	58.9	39.0	23.0	34.3	29.6	19.0
10.377	27.0	70	170.75	70.00	38.7	101.8	94.9	95.0	56.0	36.5	24.1	31.2	27.3	19.2
10.378	27.0	72	168.00	69.25	38.5	101.4	99.8	96.2	56.3	36.6	22.0	29.7	26.3	18.0
10.386	26.6	67	167.00	67.50	36.5	98.9	89.7	96.2	54.7	37.8	33.7	32.4	27.7	18.2
10.648	14.9	72	157.75	67.25	37.7	97.5	88.1	96.9	57.2	37.7	21.8	32.6	28.0	18.8
10.462	23.1	64	160.00	65.75	36.5	104.3	90.9	93.8	57.8	39.5	23.3	29.2	28.4	18.1
10.800	8.3	46	176.75	72.50	38.0	97.3	86.0	99.3	61.0	38.4	23.8	30.2	29.3	18.8
10.666	14.1	48	176.00	73.00	36.7	96.7	86.5	98.3	60.4	39.9	24.4	28.8	29.6	18.7
10.520	20.5	46	177.00	70.00	37.2	99.7	95.6	102.2	58.3	38.2	22.5	29.1	27.7	17.7
10.573	18.2	44	179.75	69.50	39.2	101.9	93.2	100.6	58.9	39.7	23.1	31.4	28.4	18.8
10.795	8.5	47	165.25	70.50	37.5	97.2	83.1	95.4	56.9	38.3	22.1	30.1	28.2	18.4
10.424	24.9	46	192.50	71.75	38.0	106.6	97.5	100.6	58.9	40.5	24.5	33.3	29.6	19.1
10.785	9.0	47	184.25	74.50	37.3	99.6	88.8	101.4	57.4	39.6	24.6	30.3	27.9	17.8
10.991	17.4	53	224.50	77.75	41.1	113.2	99.2	107.5	61.7	42.3	23.2	32.9	30.8	20.4
10.770	9.6	38	188.75	73.25	37.5	99.1	91.6	102.4	60.6	39.4	22.9	31.6	30.1	18.5
10.730	11.3	50	162.50	66.50	38.7	99.4	86.7	96.2	62.1	39.3	23.3	30.6	27.8	18.2
10.582	17.8	46	156.50	68.25	35.9	95.1	88.2	92.8	54.7	37.3	21.9	31.6	27.5	18.2
10.484	22.2	47	197.00	72.00	40.0	107.5	94.0	103.7	62.7	39.0	22.3	35.3	30.9	18.3
10.506	21.2	49	198.50	73.50	40.1	106.5	95.0	101.7	59.0	39.4	22.3	32.2	31.0	18.6
10.524	20.4	48	173.75	72.00	37.0	99.1	92.0	98.3	59.3	38.4	22.4	27.9	26.2	17.0
10.530	20.1	41	172.75	71.25	36.3	96.7	89.2	98.3	60.0	38.4	23.2	31.0	29.2	18.4
10.480	22.3	49	196.75	73.75	40.7	103.5	95.5	101.6	59.1	39.8	25.4	31.0	30.3	19.7
10.412	25.4	43	177.00	69.25	39.6	104.0	98.6	99.5	59.5	36.1	22.0	30.1	27.2	17.7
10.578	18.0	43	165.50	68.50	31.1	93.1	87.3	96.6	54.7	39.0	24.8	31.0	29.4	18.8
10.547	19.3	43	200.25	73.50	38.6	105.2	102.8	103.6	61.2	39.3	23.5	30.5	28.5	18.1
10.569	18.3	52	203.25	74.25	42.0	110.0	101.6	100.7	55.8	38.7	23.4	35.1	29.6	19.1
10.593	17.3	43	194.00	75.50	38.5	110.1	88.7	102.1	57.5	40.0	24.8	35.1	30.7	19.2
10.500	21.4	40	168.50	69.25	34.2	97.8	92.3	100.6	57.5	36.8	22.8	32.1	26.0	17.3
10.538	19.7	43	170.75	68.50	37.2	96.3	90.6	99.3	61.9	38.0	22.3	33.3	28.2	18.1
10.355	28.0	43	183.25	70.00	37.1	108.0	105.0	103.0	63.7	40.0	23.6	33.5	27.8	17.4
10.486	22.1	47	178.25	70.00	40.2	99.7	95.0	98.6	62.3	38.1	23.9	35.3	31.1	19.8
10.503	21.3	42	163.00	70.25	35.3	93.5	89.6	99.8	61.5	37.8	21.9	30.7	27.6	17.4
10.384	26.7	48	175.25	71.75	38.0	100.7	92.4	97.5	59.3	38.1	21.8	31.8	27.3	17.5
10.607	16.7	40	158.00	69.25	36.3	97.0	86.6	92.6	55.9	36.3	22.1	29.8	26.3	17.3
10.529	20.1	48	177.25	72.75	36.8	96.0	90.0	99.7	58.8	38.4	22.8	29.9	28.0	18.1
10.671	13.9	51	179.00	72.00	41.0	99.2	90.0	96.4	56.8	38.8	23.3	33.4	29.8	19.5
10.404	25.8	40	191.00	74.00	38.3	95.4	92.4	104.3	64.6	41.1	24.8	33.6	29.5	18.5
10.575	18.1	44	187.50	72.25	38.0	101.8	87.5	101.0	58.5	39.2	24.5	32.1	28.6	18.0
10.358	27.9	52	206.50	74.50	40.8	104.3	99.2	104.1	58.5	39.3	24.6	33.9	31.2	19.5
10.414	25.3	44	185.25	71.50	39.5	99.2	98.1	101.4	57.1	40.5	23.2	33.0	29.6	18.4
10.652	14.7	40	160.25	68.75	36.9	99.3	83.3	97.5	60.5	38.7	22.6	34.4	28.0	17.6
10.623	16.0	47	151.50	66.75	36.9	94.0	86.1	95.2	58.1	36.5	22.1	30.6	27.5	17.6
10.674	13.8	50	161.00	66.50	37.7	98.9	84.1	94.0	58.5	36.6	23.5	34.4	29.2	18.0
10.587	17.5	46	167.00	67.00	36.6	101.0	89.9	100.0	60.7	36.0	21.9	35.6	30.2	17.6
10.373	27.2	42	177.50	68.75	38.9	98.7	92.1	98.5	60.7	36.8	22.2	33.8	30.3	17.2
10.590	17.4	43	152.25	67.75	37.5	95.9	78.0	93.2	53.5	35.8	20.8	33.9	28.2	17.4
10.515	20.8	40	192.25	73.25	39.8	103.9	93.5	99.5	61.7	39.0	21.8	33.3	29.6	18.1
10.648	14.9	42	165.25	69.75	38.3	96.2	87.0	97.8	57.4	36.9	22.2	31.6	27.8	17.7
10.575	18.1	49	171.75	71.50	35.5	97.8	90.1	95.8	57.0	38.7	23.2	27.5	26.5	17.6
10.472	22.7	40	171.25	70.50	36.3	94.6	90.3	99.1	60.3	38.5	23.0	31.2	28.4	17.1
10.452	23.6	47	197.00	73.25	37.8	103.6	99.8	103.2	61.2	38.1	22.6	33.5	28.6	17.9
10.398	26.1	50	157.00	66.75	37.8	100.4	89.4	92.3	56.1	35.6	20.5	33.6	29.3	17.3
10.435	24.4	41	168.25	69.50	36.5	98.4	87.2	98.4	56.0	36.9	23.0	34.0	29.8	18.1
10.374	27.1	44	186.00	69.75	37.8	104.6	101.1	102.1	58.9	37.9	22.7	30.9	28.8	17.6
10.491	21.8	39	166.75	70.75	37.0	92.9	86.1	95.6	58.8	36.1	22.4	32.7	28.3	17.1
10.325	29.4	43	187.75	74.00	37.7	97.8	98.6	100.6	63.6	39.2	23.8	34.3	28.4	17.7
10.481	22.4	40	168.25	71.25	34.3	98.3	88.5	98.3	58.1	38.4	22.5	31.7	27.4	17.6
10.522	20.4	49	212.75	75.00	40.8	104.7	106.6	107.7	66.5	42.5	24.5	35.5	29.8	18.7
10.422	24.9	40	176.75	71.00	37.4	98.6	93.1	101.6	59.1	39.6	21.6	30.8	27.9	16.6
10.571	18.3	40	173.25	69.50	36.5	99.5	93.0	99.3	60.4	38.2	22.0	32.0	28.5	17.8
10.459	23.3	52	167.00	67.75	37.5	102.7	91.0	98.9	57.1	36.7	22.3	31.6	27.5	17.9
10.775	9.4	23	159.75	72.25	35.5	92.1	77.1	93.9	56.1	36.1	22.7	30.5	27.2	18.2
10.754	10.3	23	188.15	77.50	38.0	96.6	85.3	102.5	59.1	37.6	23.2	31.8	29.7	18.3
10.664	14.2	24	156.00	70.75	35.7	92.7	81.9	95.3	56.4	36.5	22.0	33.5	28.3	17.3
10.550	19.2	24	208.50	72.75	39.2	102.0	99.1	110.1	71.2	43.5	25.2	36.1	30.3	18.7
10.322	29.6	25	206.50	69.75	40.9	110.9	100.5	106.2	68.4	40.8	24.6	33.3	29.7	18.4
10.873	5.3	25	143.75	72.50	35.2	92.3	76.5	92.1	51.9	35.7	22.0	25.8	25.2	16.9
10.416	25.2	26	223.00	70.25	40.6	114.1	106.8	113.9	67.6	42.7	24.7	36.0	30.4	18.4
10.776	9.4	26	152.25	69.00	35.4	92.9	77.6	93.5	56.9	35.9	20.4	31.6	29.0	17.8
10.542	19.6	26	241.75	74.50	41.8	108.3	102.9	114.4	72.9	43.5	25.1	38.5	33.8	19.6
10.758	10.1	27	146.00	72.25	34.1	88.5	72.8	91.1	53.6	36.8	23.8	27.8	26.3	17.4
10.610	16.5	27	156.75	67.25	37.9	94.0	88.2	95.2	56.8	37.4	22.8	30.6	28.3	17.9
10.510	21.0	27	200.25	73.50	38.2	101.1	100.1	105.0	62.1	40.0	24.9	33.7	29.2	19.4
10.594	17.3	28	171.50	75.25	35.6	92.1	83.5	98.3	57.3	37.8	21.7	32.2	27.7	17.7
10.287	31.2	28	205.75	69.00	38.5	105.6	105.0	106.4	68.6	40.0	25.2	35.2	30.7	19.1
10.761	10.0	28	182.50	72.25	37.0	98.5	90.8	102.5	60.8	38.5	25.0	31.6	28.0	18.6
10.704	12.5	30	136.50	68.75	35.9	88.7	76.6	89.8	50.1	34.8	21.8	27.0	34.9	16.9
10.477	22.5	31	177.25	71.50	36.2	101.1	92.4	99.3	59.4	39.0	24.6	30.1	28.2	18.2
10.775	9.4	31	151.25	72.25	35.0	94.0	81.2	91.5	52.5	36.6	21.0	27.0	26.3	16.5
10.653	14.6	33	196.00	73.00	38.5	103.8	95.6	105.1	61.4	40.6	25.0	31.3	29.2	19.1
10.690	13.0	33	184.25	68.75	40.7	98.9	92.1	103.5	64.0	37.3	23.5	33.5	30.6	19.7
10.644	15.1	34	140.00	70.50	36.0	89.2	83.4	89.6	52.4	35.6	20.4	28.3	26.2	16.5
10.370	27.3	34	218.75	72.00	39.5	111.4	106.0	108.8	63.8	42.0	23.4	34.0	31.2	18.5
10.549	19.2	35	217.00	73.75	40.5	107.5	95.1	104.5	64.8	41.3	25.6	36.4	33.7	19.4
10.492	21.8	35	166.25	68.00	38.5	99.1	90.4	95.6	55.5	34.2	21.9	30.2	28.7	17.7
10.525	20.3	35	224.75	72.25	43.9	108.2	100.4	106.8	63.3	41.7	24.6	37.2	33.1	19.8
10.180	34.3	35	228.25	69.50	40.4	114.9	115.9	111.9	74.4	40.6	24.0	36.1	31.8	18.8
10.610	16.5	35	172.75	69.50	37.6	99.1	90.8	98.1	60.1	39.1	23.4	32.5	29.8	17.4
10.926	3.0	35	152.25	67.75	37.0	92.2	81.9	92.8	54.7	36.2	22.1	30.4	27.4	17.7
10.983	.7	35	125.75	65.50	34.0	90.8	75.0	89.2	50.0	34.8	22.0	24.8	25.9	16.9
10.521	20.5	35	177.25	71.00	38.4	100.5	90.3	98.7	57.8	37.3	22.4	31.0	28.7	17.7
10.603	16.9	36	176.25	71.50	38.7	98.2	90.3	99.9	59.2	37.7	21.5	32.4	28.4	17.8
10.414	25.3	36	226.75	71.75	41.5	115.3	108.8	114.4	69.2	42.4	24.0	35.4	21.0	20.1
10.763	9.9	37	145.25	69.25	36.0	96.8	79.4	89.2	50.3	34.8	22.2	31.0	26.9	16.9
10.689	13.1	37	151.00	67.00	35.3	92.6	83.2	96.4	60.0	38.1	22.0	31.5	26.6	16.7
10.316	29.9	37	241.25	71.50	42.1	119.2	110.3	113.9	69.8	42.6	24.8	34.4	29.5	18.4
10.477	22.5	38	187.25	69.25	38.0	102.7	92.7	101.9	64.7	39.5	24.7	34.8	30.3	18.1
10.603	16.9	39	234.75	74.50	42.8	109.5	104.5	109.9	69.5	43.1	25.8	39.1	32.5	19.9
10.387	26.6	39	219.25	74.25	40.0	108.5	104.6	109.8	68.1	42.8	24.1	35.6	29.0	19.0
11.089	.0	40	118.50	68.00	33.8	79.3	69.4	85.0	47.2	33.5	20.2	27.7	24.6	16.5
10.725	11.5	40	145.75	67.25	35.5	95.5	83.6	91.6	54.1	36.2	21.8	31.4	28.3	17.2
10.713	12.1	40	159.25	69.75	35.3	92.3	86.8	96.1	58.0	39.4	22.7	30.0	26.4	17.4
10.587	17.5	40	170.50	74.25	37.7	98.9	90.4	95.5	55.4	38.9	22.4	30.5	28.9	17.7
10.794	8.6	40	167.50	71.50	39.4	89.5	83.7	98.1	57.3	39.7	22.6	32.9	29.3	18.2
10.453	23.6	41	232.75	74.25	41.9	117.5	109.3	108.8	67.7	41.3	24.7	37.2	31.8	20.0
10.524	20.4	41	210.50	72.00	38.5	107.4	98.9	104.1	63.5	39.8	23.5	36.4	30.4	19.1
10.520	20.5	41	202.25	72.50	40.8	109.2	98.0	101.8	62.8	41.3	24.8	36.6	32.4	18.8
10.434	24.4	41	185.00	68.25	38.0	103.4	101.2	103.1	61.5	40.4	22.9	33.4	29.2	18.5
10.728	11.4	41	153.00	69.25	36.4	91.4	80.6	92.3	54.3	36.3	21.8	29.6	27.3	17.9
10.140	38.1	42	244.25	76.00	41.8	115.2	113.7	112.4	68.5	45.0	25.5	37.1	31.2	19.9
10.624	15.9	42	193.50	70.50	40.7	104.9	94.1	102.7	60.6	38.6	24.7	34.0	30.1	18.7
10.429	24.7	42	224.75	74.75	38.5	106.7	105.7	111.8	65.3	43.3	26.0	33.7	29.9	18.5
10.470	22.8	42	162.75	72.75	35.4	92.2	85.6	96.5	60.2	38.9	22.4	31.7	27.1	17.1
10.411	25.5	42	180.00	68.25	38.5	101.6	96.6	100.6	61.1	38.4	24.1	32.9	29.8	18.8
10.488	22.0	42	156.25	69.00	35.5	97.8	86.0	96.2	57.7	38.6	24.0	31.2	27.3	17.4
10.583	17.7	42	168.00	71.50	36.5	92.0	89.7	101.0	62.3	38.0	22.3	30.8	27.8	16.9
10.841	6.6	42	167.25	72.75	37.6	94.0	78.0	99.0	57.5	40.0	22.5	30.6	30.0	18.5
10.462	23.6	43	170.75	67.50	37.4	103.7	89.7	94.2	58.5	39.0	24.1	33.8	28.8	18.8
10.709	12.2	43	178.25	70.25	37.8	102.7	89.2	99.2	60.2	39.2	23.8	31.7	28.4	18.6
10.484	22.1	43	150.00	69.25	35.2	91.1	85.7	96.9	55.5	35.7	22.0	29.4	26.6	17.4
10.340	28.7	43	200.50	71.50	37.9	107.2	103.1	105.5	68.8	38.3	23.7	32.1	28.9	18.7
10.854	6.0	44	184.00	74.00	37.9	100.8	89.1	102.6	60.6	39.0	24.0	32.9	29.2	18.4
10.209	34.8	44	223.00	69.75	40.9	121.6	113.9	107.1	63.5	40.3	21.8	34.8	30.7	17.4
10.610	16.6	44	208.75	73.00	41.9	105.6	96.3	102.0	63.3	39.8	24.1	37.3	23.1	19.4
10.250	32.9	44	166.00	65.50	39.1	100.6	93.9	100.1	58.9	37.6	21.4	33.1	29.5	17.3
10.254	32.8	47	195.00	72.50	40.2	102.7	101.3	101.7	60.7	39.4	23.3	36.7	31.6	18.4
10.771	9.6	47	160.50	70.25	36.0	99.8	83.9	91.8	53.0	36.2	22.5	31.4	27.5	17.7
10.742	10.8	47	159.75	70.75	34.5	92.9	84.4	94.0	56.0	38.2	22.6	29.0	26.2	17.6
10.829	7.1	49	140.50	68.00	35.8	91.2	79.4	89.0	51.1	35.0	21.7	30.9	28.8	17.4
10.373	27.2	49	216.25	74.50	40.2	115.6	104.0	109.0	63.7	40.3	23.2	36.8	31.0	18.9
10.543	19.5	49	168.25	71.75	38.3	98.3	89.7	99.1	56.3	38.8	23.0	29.5	27.9	18.6
10.561	18.7	50	194.75	70.75	39.0	103.7	97.6	104.2	60.0	40.9	25.5	32.7	30.0	19.0
10.543	19.5	50	172.75	73.00	37.4	98.7	87.6	96.1	57.1	38.1	21.8	28.6	26.7	18.0
0.9950	47.5	51	219.00	64.00	41.2	119.8	122.1	112.8	62.5	36.9	23.6	34.7	29.1	18.4
10.678	13.6	51	149.25	69.75	34.8	92.8	81.1	96.3	53.8	36.5	21.5	31.3	26.3	17.8
10.819	7.5	51	154.50	70.00	36.9	93.3	81.5	94.4	54.7	39.0	22.6	27.5	25.9	18.6
10.433	24.5	52	199.25	71.75	39.4	106.8	100.0	105.0	63.9	39.2	22.9	35.7	30.4	19.2
10.646	15.0	53	154.50	69.25	37.6	93.9	88.7	94.5	53.7	36.2	22.0	28.5	25.7	17.1
10.706	12.4	54	153.25	70.50	38.5	99.0	91.8	96.2	57.7	38.1	23.9	31.4	29.9	18.9
10.399	26.0	54	230.00	72.25	42.5	119.9	110.4	105.5	64.2	42.7	27.0	38.4	32.0	19.6
10.726	11.5	54	161.75	67.50	37.4	94.2	87.6	95.6	59.7	40.2	23.4	27.9	27.0	17.8
10.874	5.2	55	142.25	67.25	35.2	92.7	82.8	91.9	54.4	35.2	22.5	29.4	26.8	17.0
10.740	10.9	55	179.75	68.75	41.1	106.9	95.3	98.2	57.4	37.1	21.8	34.1	31.1	19.2
10.703	12.5	55	126.50	66.75	33.4	88.8	78.2	87.5	50.8	33.0	19.7	25.3	22.0	15.8
10.650	14.8	55	169.50	68.25	37.2	101.7	91.1	97.1	56.6	38.5	22.6	33.4	29.3	18.8
10.418	25.2	55	198.50	74.25	38.3	105.3	96.7	106.6	64.0	42.6	23.4	33.2	30.0	18.4
10.647	14.9	56	174.50	69.50	38.1	104.0	89.4	98.4	58.4	37.4	22.5	34.6	30.1	18.8
10.601	17.0	56	167.75	68.50	37.4	98.6	93.0	97.0	55.4	38.8	23.2	32.4	29.7	19.0
10.745	10.6	57	147.75	65.75	35.2	99.6	86.4	90.1	53.0	35.0	21.3	31.7	27.3	16.9
10.620	16.1	57	182.25	71.75	39.4	103.4	96.7	100.7	59.3	38.6	22.8	31.8	29.1	19.0
10.636	15.4	58	175.50	71.50	38.0	100.2	88.1	97.8	57.1	38.9	23.6	30.9	29.6	18.0
10.384	26.7	58	161.75	67.25	35.1	94.9	94.9	100.2	56.8	35.9	21.0	27.8	26.1	17.6
10.403	25.8	60	157.75	67.50	40.4	97.2	93.3	94.0	54.3	35.7	21.0	31.3	28.7	18.3
10.563	18.6	62	168.75	67.50	38.3	104.7	95.6	93.7	54.4	37.1	22.7	30.3	26.3	18.3
10.424	24.8	62	191.50	72.25	40.6	104.0	98.2	101.1	59.3	40.3	23.0	32.6	28.5	19.0
10.372	27.3	63	219.15	69.50	40.2	117.6	113.8	111.8	63.4	41.1	22.3	35.1	29.6	18.5
10.705	12.4	64	155.25	69.50	37.9	95.8	82.8	94.5	61.2	39.1	22.3	29.8	28.9	18.3
10.316	29.9	65	189.75	65.75	40.8	106.4	100.5	100.5	59.2	38.1	24.0	35.9	30.5	19.1
10.599	17.0	65	127.50	65.75	34.7	93.0	79.7	87.6	50.7	33.4	20.1	28.5	24.8	16.5
10.207	35.0	65	224.50	68.25	38.8	119.6	118.0	114.3	61.3	42.1	23.4	34.9	30.1	19.4
10.304	30.4	66	234.25	72.00	41.4	119.7	109.0	109.1	63.7	42.4	24.6	35.6	30.7	19.5
10.256	32.6	67	227.75	72.75	41.3	115.8	113.4	109.8	65.6	46.0	25.4	35.3	29.8	19.5
10.334	29.0	67	199.50	68.50	40.7	118.3	106.1	101.6	58.2	38.8	24.1	32.1	29.3	18.5
10.641	15.2	68	155.50	69.25	36.3	97.4	84.3	94.4	54.3	37.5	22.6	29.2	27.3	18.5
10.308	30.2	69	215.50	70.50	40.8	113.7	107.6	110.0	63.3	44.0	22.6	37.5	32.6	18.8
10.736	11.0	70	134.25	67.00	34.9	89.2	83.6	88.8	49.6	34.8	21.5	25.6	25.7	18.5
10.236	33.6	72	201.00	69.75	40.9	108.5	105.0	104.5	59.6	40.8	23.2	35.2	28.6	20.1
10.328	29.3	72	186.75	66.00	38.9	111.1	111.5	101.7	60.3	37.3	21.5	31.3	27.2	18.0
10.399	26.0	72	190.75	70.50	38.9	108.3	101.3	97.8	56.0	41.6	22.7	30.5	29.4	19.8
10.271	31.9	74	207.50	70.00	40.8	112.4	108.5	107.1	59.3	42.2	24.6	33.7	30.0	20.9

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	17 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 17 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190063&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]17 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190063&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190063&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	17 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Multiple Linear Regression - Estimated Regression Equation
Fat[t] = + 3.46446917493056 -2.07442577566231Density[t] + 0.0705592926470338Age[t] -0.0783934514200624Weight[t] -0.0459118591136573Height[t] -0.476184080075973Neck[t] -0.019993427804318Chest[t] + 0.856618191495847Abdomen[t] -0.246802192207272Hip[t] + 0.28919293084057Thigh[t] + 0.185852531713632Knee[t] + 0.110142959754307Ankle[t] + 0.159976375626986Biceps[t] + 0.4338780396212Forearm[t] -1.50455290326014Wrist[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Fat[t] =  +  3.46446917493056 -2.07442577566231Density[t] +  0.0705592926470338Age[t] -0.0783934514200624Weight[t] -0.0459118591136573Height[t] -0.476184080075973Neck[t] -0.019993427804318Chest[t] +  0.856618191495847Abdomen[t] -0.246802192207272Hip[t] +  0.28919293084057Thigh[t] +  0.185852531713632Knee[t] +  0.110142959754307Ankle[t] +  0.159976375626986Biceps[t] +  0.4338780396212Forearm[t] -1.50455290326014Wrist[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190063&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Fat[t] =  +  3.46446917493056 -2.07442577566231Density[t] +  0.0705592926470338Age[t] -0.0783934514200624Weight[t] -0.0459118591136573Height[t] -0.476184080075973Neck[t] -0.019993427804318Chest[t] +  0.856618191495847Abdomen[t] -0.246802192207272Hip[t] +  0.28919293084057Thigh[t] +  0.185852531713632Knee[t] +  0.110142959754307Ankle[t] +  0.159976375626986Biceps[t] +  0.4338780396212Forearm[t] -1.50455290326014Wrist[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190063&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190063&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
Fat[t] = + 3.46446917493056 -2.07442577566231Density[t] + 0.0705592926470338Age[t] -0.0783934514200624Weight[t] -0.0459118591136573Height[t] -0.476184080075973Neck[t] -0.019993427804318Chest[t] + 0.856618191495847Abdomen[t] -0.246802192207272Hip[t] + 0.28919293084057Thigh[t] + 0.185852531713632Knee[t] + 0.110142959754307Ankle[t] + 0.159976375626986Biceps[t] + 0.4338780396212Forearm[t] -1.50455290326014Wrist[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	3.46446917493056	17.475912	0.1982	0.843025	0.421513
Density	-2.07442577566231	0.480743	-4.315	2.3e-05	1.2e-05
Age	0.0705592926470338	0.031276	2.256	0.024981	0.012491
Weight	-0.0783934514200624	0.0517	-1.5163	0.130775	0.065388
Height	-0.0459118591136573	0.092801	-0.4947	0.621245	0.310623
Neck	-0.476184080075973	0.224316	-2.1228	0.034806	0.017403
Chest	-0.019993427804318	0.095673	-0.209	0.834646	0.417323
Abdomen	0.856618191495847	0.086462	9.9075	0	0
Hip	-0.246802192207272	0.141085	-1.7493	0.081532	0.040766
Thigh	0.28919293084057	0.139836	2.0681	0.039717	0.019859
Knee	0.185852531713632	0.236811	0.7848	0.433347	0.216674
Ankle	0.110142959754307	0.214209	0.5142	0.607602	0.303801
Biceps	0.159976375626986	0.165198	0.9684	0.333837	0.166918
Forearm	0.4338780396212	0.19219	2.2576	0.024884	0.012442
Wrist	-1.50455290326014	0.516881	-2.9108	0.003948	0.001974

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 3.46446917493056 & 17.475912 & 0.1982 & 0.843025 & 0.421513 \tabularnewline
Density & -2.07442577566231 & 0.480743 & -4.315 & 2.3e-05 & 1.2e-05 \tabularnewline
Age & 0.0705592926470338 & 0.031276 & 2.256 & 0.024981 & 0.012491 \tabularnewline
Weight & -0.0783934514200624 & 0.0517 & -1.5163 & 0.130775 & 0.065388 \tabularnewline
Height & -0.0459118591136573 & 0.092801 & -0.4947 & 0.621245 & 0.310623 \tabularnewline
Neck & -0.476184080075973 & 0.224316 & -2.1228 & 0.034806 & 0.017403 \tabularnewline
Chest & -0.019993427804318 & 0.095673 & -0.209 & 0.834646 & 0.417323 \tabularnewline
Abdomen & 0.856618191495847 & 0.086462 & 9.9075 & 0 & 0 \tabularnewline
Hip & -0.246802192207272 & 0.141085 & -1.7493 & 0.081532 & 0.040766 \tabularnewline
Thigh & 0.28919293084057 & 0.139836 & 2.0681 & 0.039717 & 0.019859 \tabularnewline
Knee & 0.185852531713632 & 0.236811 & 0.7848 & 0.433347 & 0.216674 \tabularnewline
Ankle & 0.110142959754307 & 0.214209 & 0.5142 & 0.607602 & 0.303801 \tabularnewline
Biceps & 0.159976375626986 & 0.165198 & 0.9684 & 0.333837 & 0.166918 \tabularnewline
Forearm & 0.4338780396212 & 0.19219 & 2.2576 & 0.024884 & 0.012442 \tabularnewline
Wrist & -1.50455290326014 & 0.516881 & -2.9108 & 0.003948 & 0.001974 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190063&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]3.46446917493056[/C][C]17.475912[/C][C]0.1982[/C][C]0.843025[/C][C]0.421513[/C][/ROW]
[ROW][C]Density[/C][C]-2.07442577566231[/C][C]0.480743[/C][C]-4.315[/C][C]2.3e-05[/C][C]1.2e-05[/C][/ROW]
[ROW][C]Age[/C][C]0.0705592926470338[/C][C]0.031276[/C][C]2.256[/C][C]0.024981[/C][C]0.012491[/C][/ROW]
[ROW][C]Weight[/C][C]-0.0783934514200624[/C][C]0.0517[/C][C]-1.5163[/C][C]0.130775[/C][C]0.065388[/C][/ROW]
[ROW][C]Height[/C][C]-0.0459118591136573[/C][C]0.092801[/C][C]-0.4947[/C][C]0.621245[/C][C]0.310623[/C][/ROW]
[ROW][C]Neck[/C][C]-0.476184080075973[/C][C]0.224316[/C][C]-2.1228[/C][C]0.034806[/C][C]0.017403[/C][/ROW]
[ROW][C]Chest[/C][C]-0.019993427804318[/C][C]0.095673[/C][C]-0.209[/C][C]0.834646[/C][C]0.417323[/C][/ROW]
[ROW][C]Abdomen[/C][C]0.856618191495847[/C][C]0.086462[/C][C]9.9075[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Hip[/C][C]-0.246802192207272[/C][C]0.141085[/C][C]-1.7493[/C][C]0.081532[/C][C]0.040766[/C][/ROW]
[ROW][C]Thigh[/C][C]0.28919293084057[/C][C]0.139836[/C][C]2.0681[/C][C]0.039717[/C][C]0.019859[/C][/ROW]
[ROW][C]Knee[/C][C]0.185852531713632[/C][C]0.236811[/C][C]0.7848[/C][C]0.433347[/C][C]0.216674[/C][/ROW]
[ROW][C]Ankle[/C][C]0.110142959754307[/C][C]0.214209[/C][C]0.5142[/C][C]0.607602[/C][C]0.303801[/C][/ROW]
[ROW][C]Biceps[/C][C]0.159976375626986[/C][C]0.165198[/C][C]0.9684[/C][C]0.333837[/C][C]0.166918[/C][/ROW]
[ROW][C]Forearm[/C][C]0.4338780396212[/C][C]0.19219[/C][C]2.2576[/C][C]0.024884[/C][C]0.012442[/C][/ROW]
[ROW][C]Wrist[/C][C]-1.50455290326014[/C][C]0.516881[/C][C]-2.9108[/C][C]0.003948[/C][C]0.001974[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190063&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190063&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	3.46446917493056	17.475912	0.1982	0.843025	0.421513
Density	-2.07442577566231	0.480743	-4.315	2.3e-05	1.2e-05
Age	0.0705592926470338	0.031276	2.256	0.024981	0.012491
Weight	-0.0783934514200624	0.0517	-1.5163	0.130775	0.065388
Height	-0.0459118591136573	0.092801	-0.4947	0.621245	0.310623
Neck	-0.476184080075973	0.224316	-2.1228	0.034806	0.017403
Chest	-0.019993427804318	0.095673	-0.209	0.834646	0.417323
Abdomen	0.856618191495847	0.086462	9.9075	0	0
Hip	-0.246802192207272	0.141085	-1.7493	0.081532	0.040766
Thigh	0.28919293084057	0.139836	2.0681	0.039717	0.019859
Knee	0.185852531713632	0.236811	0.7848	0.433347	0.216674
Ankle	0.110142959754307	0.214209	0.5142	0.607602	0.303801
Biceps	0.159976375626986	0.165198	0.9684	0.333837	0.166918
Forearm	0.4338780396212	0.19219	2.2576	0.024884	0.012442
Wrist	-1.50455290326014	0.516881	-2.9108	0.003948	0.001974

Multiple Linear Regression - Regression Statistics
Multiple R	0.875973415883793
R-squared	0.76732942533512
Adjusted R-squared	0.753585171979389
F-TEST (value)	55.8291094812471
F-TEST (DF numerator)	14
F-TEST (DF denominator)	237
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	4.15425848735143
Sum Squared Residuals	4090.11366839634

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.875973415883793 \tabularnewline
R-squared & 0.76732942533512 \tabularnewline
Adjusted R-squared & 0.753585171979389 \tabularnewline
F-TEST (value) & 55.8291094812471 \tabularnewline
F-TEST (DF numerator) & 14 \tabularnewline
F-TEST (DF denominator) & 237 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 4.15425848735143 \tabularnewline
Sum Squared Residuals & 4090.11366839634 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190063&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.875973415883793[/C][/ROW]
[ROW][C]R-squared[/C][C]0.76732942533512[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.753585171979389[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]55.8291094812471[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]14[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]237[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]4.15425848735143[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]4090.11366839634[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190063&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190063&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R	0.875973415883793
R-squared	0.76732942533512
Adjusted R-squared	0.753585171979389
F-TEST (value)	55.8291094812471
F-TEST (DF numerator)	14
F-TEST (DF denominator)	237
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	4.15425848735143
Sum Squared Residuals	4090.11366839634

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.3	15.9199351191195	-3.61993511911949
2	6.1	8.66045668215501	-2.56045668215501
3	25.3	18.6822450779901	6.61775492200987
4	10.4	11.767791802012	-1.36779180201196
5	28.7	27.4821748823409	1.21782511765909
6	20.9	17.4715562795515	3.42844372044848
7	19.2	16.5946891097283	2.60531089027173
8	12.4	14.1586844912188	-1.75868449121883
9	4.1	9.88578105584531	-5.78578105584531
10	11.7	10.6706676482444	1.02933235175557
11	7.1	9.41442817274954	-2.31442817274954
12	7.8	12.7220441516948	-4.92204415169484
13	20.8	17.8703315980842	2.92966840191576
14	21.2	24.7240559254832	-3.52405592548321
15	22.1	24.2112524780163	-2.11125247801627
16	20.9	22.8692758403064	-1.96927584030642
17	29	23.8693062785825	5.13069372141754
18	22.9	19.5098714428533	3.39012855714671
19	16	16.7715315573044	-0.77153155730443
20	16.5	22.6568857883471	-6.15688578834707
21	19.1	20.4967148773441	-1.39671487734409
22	15.2	19.4831158782399	-4.28311587823991
23	15.6	9.88667914950284	5.71332085049716
24	17.7	11.3946515950854	6.30534840491465
25	14	8.4798023684644	5.5201976315356
26	3.7	8.22621456256947	-4.52621456256947
27	7.9	9.10961026056871	-1.20961026056871
28	22.9	17.6893542222526	5.21064577774744
29	3.7	5.93115895930214	-2.23115895930214
30	8.8	11.1058863131255	-2.30588631312546
31	11.9	13.8415368913955	-1.94153689139553
32	5.7	10.9045007967427	-5.20450079674272
33	11.8	6.49335053340234	5.30664946659766
34	21.3	24.2853912916875	-2.98539129168751
35	32.3	31.9110851399653	0.388914860034695
36	40.1	35.9973581653848	4.10264183461519
37	24.2	23.8989061613896	0.301093838610388
38	28.4	22.4596947735492	5.94030522645076
39	35.2	42.2860334746234	-7.08603347462343
40	32.6	32.0470575974818	0.55294240251817
41	34.5	34.7310312083206	-0.23103120832061
42	32.9	31.7475670637536	1.15243293624635
43	31.6	33.4222038893585	-1.82220388935851
44	32	26.3551367955531	5.64486320444688
45	7.7	10.6728409364813	-2.97284093648126
46	13.9	10.6913180392534	3.20868196074656
47	10.8	8.07263666796648	2.72736333203352
48	5.6	10.0569095365757	-4.45690953657568
49	13.6	17.4763486296056	-3.8763486296056
50	4	5.67412068913163	-1.67412068913163
51	10.2	14.2483855068306	-4.0483855068306
52	6.6	9.25193728759104	-2.65193728759104
53	8	13.3198178917093	-5.31981789170929
54	6.3	10.971615845097	-4.67161584509702
55	3.9	7.38217468460199	-3.48217468460199
56	22.6	23.0885315447135	-0.488531544713525
57	20.4	25.4869596313078	-5.08695963130785
58	28	27.3418809720908	0.658119027909185
59	31.5	28.2960153517564	3.20398464824362
60	24.6	25.8474395826721	-1.24743958267213
61	26.1	25.5028366320646	0.597163367935438
62	29.8	23.7946365962366	6.00536340376343
63	30.7	27.5066215759799	3.19337842402014
64	25.8	27.2502050472702	-1.45020504727024
65	32.3	29.9472061065932	2.35279389340683
66	30	26.3371791136746	3.66282088632537
67	21.5	15.7637098071217	5.73629019287832
68	13.8	15.4897015218144	-1.68970152181436
69	6.3	9.00994077050197	-2.70994077050197
70	12.9	13.8494499763274	-0.949449976327361
71	24.3	19.8941410219652	4.40585897803481
72	8.8	13.0257236162847	-4.22572361628468
73	8.5	11.1000379214003	-2.60003792140026
74	13.5	11.9402555156152	1.55974448438485
75	11.8	16.4930881934111	-4.69308819341111
76	18.5	12.4856909024298	6.01430909757024
77	8.8	9.85099161677834	-1.05099161677833
78	22.2	19.375098875049	2.824901124951
79	21.5	22.7502279583558	-1.25022795835576
80	18.8	24.3382649232555	-5.53826492325547
81	31.4	22.249879143626	9.15012085637403
82	26.8	18.2370459994813	8.56295400051872
83	18.4	22.7821693873353	-4.38216938733533
84	27	21.2425792054131	5.75742079458693
85	27	26.6418037432797	0.358196256720298
86	26.6	20.5691009411103	6.03089905888975
87	14.9	17.6813573013418	-2.78135730134179
88	23.1	22.3503753226859	0.749624677314055
89	8.3	12.9003241142948	-4.60032411429481
90	14.1	14.8894021525257	-0.789402152525685
91	20.5	21.2407679844085	-0.740767984408521
92	18.2	17.6747573477943	0.5252426522057
93	8.5	11.410069501425	-2.91006950142503
94	24.9	21.8591822531791	3.04081774682085
95	9	14.6729796345423	-5.67297963454225
96	17.4	16.0398580531667	1.36014194683334
97	9.6	16.6504881056881	-7.05048810568814
98	11.3	16.4559666574094	-5.15596665740935
99	17.8	17.7779814296476	0.0220185703523795
100	22.2	19.3728911453978	2.82710885460221
101	21.2	18.7049343306496	2.49506566935042
102	20.4	20.0482272617147	0.351772738285287
103	20.1	17.6192113890169	2.48078861098311
104	22.3	17.405848135294	4.89415186470599
105	25.4	23.1396760226298	2.26032397737025
106	18	17.9354625596383	0.0645374403617317
107	19.3	25.1577361431077	-5.85773614310773
108	18.3	21.4747449898227	-3.17474498982269
109	17.3	12.9406689077959	4.35933109220409
110	21.4	20.4799148237805	0.920085176219468
111	19.7	19.3201044458803	0.379895554119744
112	28	31.8338368586555	-3.83383685865547
113	22.1	20.8296950565738	1.27030494342621
114	21.3	20.0100823821335	1.28991761786651
115	26.7	20.4915058452889	6.20849415471114
116	16.7	16.3182672468256	0.381732753174366
117	20.1	17.1728868961251	2.92711310387494
118	13.9	14.5232871495932	-0.623287149593224
119	25.8	18.9910447499522	6.80895525004782
120	18.1	13.8767754045715	4.22322459542847
121	27.9	20.3614805034152	7.53851949658477
122	25.3	22.4103038163856	2.88969618361437
123	14.7	14.5571458071537	0.142854192846301
124	16	16.9782674361003	-0.978267436100324
125	13.8	15.4870452657237	-1.68704526572372
126	17.5	20.4375101915596	-2.93751019155961
127	27.2	21.4402243554154	5.75977564458459
128	17.4	9.4200555870639	7.9799444129361
129	20.8	18.9777732029824	1.82222679701762
130	14.9	14.7991969676981	0.100803032301915
131	18.1	18.5645996711993	-0.464599671199268
132	22.7	20.3319434762316	2.36805652376843
133	23.6	24.3471793048803	-0.747179304880333
134	26.1	21.0019635034233	5.09803649657665
135	24.4	16.1162985857972	8.28370141420284
136	27.1	26.1163216934992	0.983678306500838
137	21.8	16.7805894113681	5.01941058863192
138	29.4	26.1692123421551	3.23078765784492
139	22.4	18.2318941061893	4.16810589381072
140	20.4	28.488603671709	-8.088603671709
141	24.9	21.3338471148058	3.56615288519418
142	18.3	21.0672067930528	-2.76720679305279
143	23.3	18.713483799741	4.58651620025895
144	9.4	5.75066095675246	3.64933904324754
145	10.3	9.29179047635031	1.00820952364969
146	14.2	12.4686275228939	1.73137247710615
147	19.2	22.8370105947116	-3.63701059471163
148	29.6	23.2148783961225	6.38512160387749
149	5.3	5.97065497901681	-0.670654979016813
150	25.2	26.2176183728328	-1.01761837283281
151	9.4	8.75571315178945	0.644286848210549
152	19.6	22.1666915845716	-2.56669158457162
153	10.1	4.80178286308688	5.29821713691312
154	16.5	16.2463947917929	0.253605208207122
155	21	21.1238865234689	-0.123886523468921
156	17.3	11.5628913968837	5.73710860311627
157	31.2	28.3065069996273	2.89349300037268
158	10	15.0998216155703	-5.09982161557034
159	12.5	11.4972512271511	1.00274877284889
160	22.5	18.9285875858824	3.5714124141176
161	9.4	11.7579650770766	-2.35796507707663
162	14.6	17.5179412643655	-2.9179412643655
163	13	15.034537989247	-2.03453798924697
164	15.1	15.0606572571262	0.0393427428737826
165	27.3	26.7860027180342	0.513997281965775
166	19.2	18.3839354686455	0.816064531354535
167	21.8	17.0153055771263	4.78469442287371
168	20.3	19.0306921006514	1.2693078993486
169	34.3	36.8538840379084	-2.55388403790839
170	16.5	20.0490622862441	-3.54906228624408
171	3	11.1163464919011	-8.11634649190106
172	0.7	7.63974072244449	-6.93974072244449
173	20.5	16.5483018503841	3.95169814961585
174	16.9	16.4345934563173	0.465406543682701
175	25.3	21.2994679454584	4.00053205454165
176	9.9	10.7677005593322	-0.86770055933225
177	13.1	16.1164135491316	-3.01641354913162
178	29.9	27.8772649795187	2.02273502048125
179	22.5	20.9181999665676	1.58180003343244
180	16.9	23.5872809516682	-6.68728095166824
181	26.6	25.3533225366803	1.24667746331972
182	0	4.04299487310511	-4.04299487310511
183	11.5	15.9155116808685	-4.41551168086846
184	12.1	17.0295610947951	-4.92956109479505
185	17.5	17.9949640789798	-0.494964078979783
186	8.6	11.4497888643528	-2.84978886435281
187	23.6	27.1253321310927	-3.52533213109265
188	20.4	21.8908310811789	-1.49083108117889
189	20.5	22.7590427634567	-2.25904276345666
190	24.4	26.1530105168034	-1.75301051680343
191	11.4	10.53186401937	0.86813598062996
192	38.1	30.7188055981424	7.38119440185762
193	15.9	17.5498420644491	-1.64984206444909
194	24.7	26.5539637927033	-1.8539637927033
195	22.8	17.6276663457037	5.17233365429633
196	25.5	22.5114688699609	2.98853113003907
197	22	17.4820721163212	4.51792788367879
198	17.7	19.8104714052382	-2.1104714052382
199	6.6	6.70491637417965	-0.104916374179649
200	23.6	18.4562011638055	5.1437988361945
201	12.2	15.6839738148258	-3.48397381482581
202	22.1	15.8993196037949	6.20068039620507
203	28.7	27.3015949362627	1.39840506373726
204	6	14.8369093058723	-8.83690930587227
205	34.8	34.8990788282207	-0.0990788282207168
206	16.6	15.256974994356	1.34302500564402
207	32.9	22.8315196499761	10.0684803500239
208	32.8	26.7148132409084	6.0851867590916
209	9.6	13.5631343619174	-3.96313436191745
210	10.8	14.8494756025136	-4.04947560251364
211	7.1	12.4333666954267	-5.33336669542668
212	27.2	25.1319146304935	2.06808536950653
213	19.5	15.6104244753107	3.88957552468933
214	18.7	21.2363373508427	-2.5363373508427
215	19.5	14.8400854652166	4.65991453478336
216	47.5	57.6573599746697	-10.1573599746697
217	13.6	11.6352700462731	1.96472995372692
218	7.5	9.5822790438326	-2.0822790438326
219	24.5	23.7283898855993	0.77161011440069
220	15	17.3687173565667	-2.36871735656672
221	12.4	20.3580207930818	-7.9580207930818
222	26	30.2669757210485	-4.2669757210485
223	11.5	17.7084286328179	-6.20842863281793
224	5.2	15.6868365103193	-10.4868365103193
225	10.9	19.4668148624532	-8.56681486245325
226	12.5	12.6883831303368	-0.188383130336762
227	14.8	18.9405825274766	-4.14058252747659
228	25.2	22.5933082297581	2.6066917702419
229	14.9	17.1605329621295	-2.26053296212948
230	17	20.3449711295063	-3.34497112950626
231	10.6	19.2845024228963	-8.68450242289632
232	16.1	20.9884924193453	-4.88849241934534
233	15.4	16.7311001175373	-1.33110011753733
234	26.7	22.9031023001526	3.79689769984742
235	25.8	20.7713869655334	5.02861303446664
236	18.6	21.8876400171782	-3.28764001717816
237	24.8	21.8082026095979	2.99179739040208
238	27.3	33.4730902722564	-6.17309027225636
239	12.4	15.2491930772909	-2.84919307729091
240	29.9	25.5721871339394	4.32781286606062
241	17	14.8975448964825	2.10245510351754
242	35	35.7324865140208	-0.732486514020806
243	30.4	28.1028959500662	2.29710404993377
244	32.6	33.3382694065437	-0.738269406543713
245	29	28.7467343738108	0.253265626189185
246	15.2	14.3447319945064	0.855268005493605
247	30.2	30.9722160816427	-0.772216081642711
248	11	14.4187203372517	-3.4187203372517
249	33.6	26.0329109647771	7.56708903522289
250	29.3	35.5837217140321	-6.2837217140321
251	26	25.0034281027273	0.996571897272681
252	31.9	27.3979694372055	4.50203056279448

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.3 & 15.9199351191195 & -3.61993511911949 \tabularnewline
2 & 6.1 & 8.66045668215501 & -2.56045668215501 \tabularnewline
3 & 25.3 & 18.6822450779901 & 6.61775492200987 \tabularnewline
4 & 10.4 & 11.767791802012 & -1.36779180201196 \tabularnewline
5 & 28.7 & 27.4821748823409 & 1.21782511765909 \tabularnewline
6 & 20.9 & 17.4715562795515 & 3.42844372044848 \tabularnewline
7 & 19.2 & 16.5946891097283 & 2.60531089027173 \tabularnewline
8 & 12.4 & 14.1586844912188 & -1.75868449121883 \tabularnewline
9 & 4.1 & 9.88578105584531 & -5.78578105584531 \tabularnewline
10 & 11.7 & 10.6706676482444 & 1.02933235175557 \tabularnewline
11 & 7.1 & 9.41442817274954 & -2.31442817274954 \tabularnewline
12 & 7.8 & 12.7220441516948 & -4.92204415169484 \tabularnewline
13 & 20.8 & 17.8703315980842 & 2.92966840191576 \tabularnewline
14 & 21.2 & 24.7240559254832 & -3.52405592548321 \tabularnewline
15 & 22.1 & 24.2112524780163 & -2.11125247801627 \tabularnewline
16 & 20.9 & 22.8692758403064 & -1.96927584030642 \tabularnewline
17 & 29 & 23.8693062785825 & 5.13069372141754 \tabularnewline
18 & 22.9 & 19.5098714428533 & 3.39012855714671 \tabularnewline
19 & 16 & 16.7715315573044 & -0.77153155730443 \tabularnewline
20 & 16.5 & 22.6568857883471 & -6.15688578834707 \tabularnewline
21 & 19.1 & 20.4967148773441 & -1.39671487734409 \tabularnewline
22 & 15.2 & 19.4831158782399 & -4.28311587823991 \tabularnewline
23 & 15.6 & 9.88667914950284 & 5.71332085049716 \tabularnewline
24 & 17.7 & 11.3946515950854 & 6.30534840491465 \tabularnewline
25 & 14 & 8.4798023684644 & 5.5201976315356 \tabularnewline
26 & 3.7 & 8.22621456256947 & -4.52621456256947 \tabularnewline
27 & 7.9 & 9.10961026056871 & -1.20961026056871 \tabularnewline
28 & 22.9 & 17.6893542222526 & 5.21064577774744 \tabularnewline
29 & 3.7 & 5.93115895930214 & -2.23115895930214 \tabularnewline
30 & 8.8 & 11.1058863131255 & -2.30588631312546 \tabularnewline
31 & 11.9 & 13.8415368913955 & -1.94153689139553 \tabularnewline
32 & 5.7 & 10.9045007967427 & -5.20450079674272 \tabularnewline
33 & 11.8 & 6.49335053340234 & 5.30664946659766 \tabularnewline
34 & 21.3 & 24.2853912916875 & -2.98539129168751 \tabularnewline
35 & 32.3 & 31.9110851399653 & 0.388914860034695 \tabularnewline
36 & 40.1 & 35.9973581653848 & 4.10264183461519 \tabularnewline
37 & 24.2 & 23.8989061613896 & 0.301093838610388 \tabularnewline
38 & 28.4 & 22.4596947735492 & 5.94030522645076 \tabularnewline
39 & 35.2 & 42.2860334746234 & -7.08603347462343 \tabularnewline
40 & 32.6 & 32.0470575974818 & 0.55294240251817 \tabularnewline
41 & 34.5 & 34.7310312083206 & -0.23103120832061 \tabularnewline
42 & 32.9 & 31.7475670637536 & 1.15243293624635 \tabularnewline
43 & 31.6 & 33.4222038893585 & -1.82220388935851 \tabularnewline
44 & 32 & 26.3551367955531 & 5.64486320444688 \tabularnewline
45 & 7.7 & 10.6728409364813 & -2.97284093648126 \tabularnewline
46 & 13.9 & 10.6913180392534 & 3.20868196074656 \tabularnewline
47 & 10.8 & 8.07263666796648 & 2.72736333203352 \tabularnewline
48 & 5.6 & 10.0569095365757 & -4.45690953657568 \tabularnewline
49 & 13.6 & 17.4763486296056 & -3.8763486296056 \tabularnewline
50 & 4 & 5.67412068913163 & -1.67412068913163 \tabularnewline
51 & 10.2 & 14.2483855068306 & -4.0483855068306 \tabularnewline
52 & 6.6 & 9.25193728759104 & -2.65193728759104 \tabularnewline
53 & 8 & 13.3198178917093 & -5.31981789170929 \tabularnewline
54 & 6.3 & 10.971615845097 & -4.67161584509702 \tabularnewline
55 & 3.9 & 7.38217468460199 & -3.48217468460199 \tabularnewline
56 & 22.6 & 23.0885315447135 & -0.488531544713525 \tabularnewline
57 & 20.4 & 25.4869596313078 & -5.08695963130785 \tabularnewline
58 & 28 & 27.3418809720908 & 0.658119027909185 \tabularnewline
59 & 31.5 & 28.2960153517564 & 3.20398464824362 \tabularnewline
60 & 24.6 & 25.8474395826721 & -1.24743958267213 \tabularnewline
61 & 26.1 & 25.5028366320646 & 0.597163367935438 \tabularnewline
62 & 29.8 & 23.7946365962366 & 6.00536340376343 \tabularnewline
63 & 30.7 & 27.5066215759799 & 3.19337842402014 \tabularnewline
64 & 25.8 & 27.2502050472702 & -1.45020504727024 \tabularnewline
65 & 32.3 & 29.9472061065932 & 2.35279389340683 \tabularnewline
66 & 30 & 26.3371791136746 & 3.66282088632537 \tabularnewline
67 & 21.5 & 15.7637098071217 & 5.73629019287832 \tabularnewline
68 & 13.8 & 15.4897015218144 & -1.68970152181436 \tabularnewline
69 & 6.3 & 9.00994077050197 & -2.70994077050197 \tabularnewline
70 & 12.9 & 13.8494499763274 & -0.949449976327361 \tabularnewline
71 & 24.3 & 19.8941410219652 & 4.40585897803481 \tabularnewline
72 & 8.8 & 13.0257236162847 & -4.22572361628468 \tabularnewline
73 & 8.5 & 11.1000379214003 & -2.60003792140026 \tabularnewline
74 & 13.5 & 11.9402555156152 & 1.55974448438485 \tabularnewline
75 & 11.8 & 16.4930881934111 & -4.69308819341111 \tabularnewline
76 & 18.5 & 12.4856909024298 & 6.01430909757024 \tabularnewline
77 & 8.8 & 9.85099161677834 & -1.05099161677833 \tabularnewline
78 & 22.2 & 19.375098875049 & 2.824901124951 \tabularnewline
79 & 21.5 & 22.7502279583558 & -1.25022795835576 \tabularnewline
80 & 18.8 & 24.3382649232555 & -5.53826492325547 \tabularnewline
81 & 31.4 & 22.249879143626 & 9.15012085637403 \tabularnewline
82 & 26.8 & 18.2370459994813 & 8.56295400051872 \tabularnewline
83 & 18.4 & 22.7821693873353 & -4.38216938733533 \tabularnewline
84 & 27 & 21.2425792054131 & 5.75742079458693 \tabularnewline
85 & 27 & 26.6418037432797 & 0.358196256720298 \tabularnewline
86 & 26.6 & 20.5691009411103 & 6.03089905888975 \tabularnewline
87 & 14.9 & 17.6813573013418 & -2.78135730134179 \tabularnewline
88 & 23.1 & 22.3503753226859 & 0.749624677314055 \tabularnewline
89 & 8.3 & 12.9003241142948 & -4.60032411429481 \tabularnewline
90 & 14.1 & 14.8894021525257 & -0.789402152525685 \tabularnewline
91 & 20.5 & 21.2407679844085 & -0.740767984408521 \tabularnewline
92 & 18.2 & 17.6747573477943 & 0.5252426522057 \tabularnewline
93 & 8.5 & 11.410069501425 & -2.91006950142503 \tabularnewline
94 & 24.9 & 21.8591822531791 & 3.04081774682085 \tabularnewline
95 & 9 & 14.6729796345423 & -5.67297963454225 \tabularnewline
96 & 17.4 & 16.0398580531667 & 1.36014194683334 \tabularnewline
97 & 9.6 & 16.6504881056881 & -7.05048810568814 \tabularnewline
98 & 11.3 & 16.4559666574094 & -5.15596665740935 \tabularnewline
99 & 17.8 & 17.7779814296476 & 0.0220185703523795 \tabularnewline
100 & 22.2 & 19.3728911453978 & 2.82710885460221 \tabularnewline
101 & 21.2 & 18.7049343306496 & 2.49506566935042 \tabularnewline
102 & 20.4 & 20.0482272617147 & 0.351772738285287 \tabularnewline
103 & 20.1 & 17.6192113890169 & 2.48078861098311 \tabularnewline
104 & 22.3 & 17.405848135294 & 4.89415186470599 \tabularnewline
105 & 25.4 & 23.1396760226298 & 2.26032397737025 \tabularnewline
106 & 18 & 17.9354625596383 & 0.0645374403617317 \tabularnewline
107 & 19.3 & 25.1577361431077 & -5.85773614310773 \tabularnewline
108 & 18.3 & 21.4747449898227 & -3.17474498982269 \tabularnewline
109 & 17.3 & 12.9406689077959 & 4.35933109220409 \tabularnewline
110 & 21.4 & 20.4799148237805 & 0.920085176219468 \tabularnewline
111 & 19.7 & 19.3201044458803 & 0.379895554119744 \tabularnewline
112 & 28 & 31.8338368586555 & -3.83383685865547 \tabularnewline
113 & 22.1 & 20.8296950565738 & 1.27030494342621 \tabularnewline
114 & 21.3 & 20.0100823821335 & 1.28991761786651 \tabularnewline
115 & 26.7 & 20.4915058452889 & 6.20849415471114 \tabularnewline
116 & 16.7 & 16.3182672468256 & 0.381732753174366 \tabularnewline
117 & 20.1 & 17.1728868961251 & 2.92711310387494 \tabularnewline
118 & 13.9 & 14.5232871495932 & -0.623287149593224 \tabularnewline
119 & 25.8 & 18.9910447499522 & 6.80895525004782 \tabularnewline
120 & 18.1 & 13.8767754045715 & 4.22322459542847 \tabularnewline
121 & 27.9 & 20.3614805034152 & 7.53851949658477 \tabularnewline
122 & 25.3 & 22.4103038163856 & 2.88969618361437 \tabularnewline
123 & 14.7 & 14.5571458071537 & 0.142854192846301 \tabularnewline
124 & 16 & 16.9782674361003 & -0.978267436100324 \tabularnewline
125 & 13.8 & 15.4870452657237 & -1.68704526572372 \tabularnewline
126 & 17.5 & 20.4375101915596 & -2.93751019155961 \tabularnewline
127 & 27.2 & 21.4402243554154 & 5.75977564458459 \tabularnewline
128 & 17.4 & 9.4200555870639 & 7.9799444129361 \tabularnewline
129 & 20.8 & 18.9777732029824 & 1.82222679701762 \tabularnewline
130 & 14.9 & 14.7991969676981 & 0.100803032301915 \tabularnewline
131 & 18.1 & 18.5645996711993 & -0.464599671199268 \tabularnewline
132 & 22.7 & 20.3319434762316 & 2.36805652376843 \tabularnewline
133 & 23.6 & 24.3471793048803 & -0.747179304880333 \tabularnewline
134 & 26.1 & 21.0019635034233 & 5.09803649657665 \tabularnewline
135 & 24.4 & 16.1162985857972 & 8.28370141420284 \tabularnewline
136 & 27.1 & 26.1163216934992 & 0.983678306500838 \tabularnewline
137 & 21.8 & 16.7805894113681 & 5.01941058863192 \tabularnewline
138 & 29.4 & 26.1692123421551 & 3.23078765784492 \tabularnewline
139 & 22.4 & 18.2318941061893 & 4.16810589381072 \tabularnewline
140 & 20.4 & 28.488603671709 & -8.088603671709 \tabularnewline
141 & 24.9 & 21.3338471148058 & 3.56615288519418 \tabularnewline
142 & 18.3 & 21.0672067930528 & -2.76720679305279 \tabularnewline
143 & 23.3 & 18.713483799741 & 4.58651620025895 \tabularnewline
144 & 9.4 & 5.75066095675246 & 3.64933904324754 \tabularnewline
145 & 10.3 & 9.29179047635031 & 1.00820952364969 \tabularnewline
146 & 14.2 & 12.4686275228939 & 1.73137247710615 \tabularnewline
147 & 19.2 & 22.8370105947116 & -3.63701059471163 \tabularnewline
148 & 29.6 & 23.2148783961225 & 6.38512160387749 \tabularnewline
149 & 5.3 & 5.97065497901681 & -0.670654979016813 \tabularnewline
150 & 25.2 & 26.2176183728328 & -1.01761837283281 \tabularnewline
151 & 9.4 & 8.75571315178945 & 0.644286848210549 \tabularnewline
152 & 19.6 & 22.1666915845716 & -2.56669158457162 \tabularnewline
153 & 10.1 & 4.80178286308688 & 5.29821713691312 \tabularnewline
154 & 16.5 & 16.2463947917929 & 0.253605208207122 \tabularnewline
155 & 21 & 21.1238865234689 & -0.123886523468921 \tabularnewline
156 & 17.3 & 11.5628913968837 & 5.73710860311627 \tabularnewline
157 & 31.2 & 28.3065069996273 & 2.89349300037268 \tabularnewline
158 & 10 & 15.0998216155703 & -5.09982161557034 \tabularnewline
159 & 12.5 & 11.4972512271511 & 1.00274877284889 \tabularnewline
160 & 22.5 & 18.9285875858824 & 3.5714124141176 \tabularnewline
161 & 9.4 & 11.7579650770766 & -2.35796507707663 \tabularnewline
162 & 14.6 & 17.5179412643655 & -2.9179412643655 \tabularnewline
163 & 13 & 15.034537989247 & -2.03453798924697 \tabularnewline
164 & 15.1 & 15.0606572571262 & 0.0393427428737826 \tabularnewline
165 & 27.3 & 26.7860027180342 & 0.513997281965775 \tabularnewline
166 & 19.2 & 18.3839354686455 & 0.816064531354535 \tabularnewline
167 & 21.8 & 17.0153055771263 & 4.78469442287371 \tabularnewline
168 & 20.3 & 19.0306921006514 & 1.2693078993486 \tabularnewline
169 & 34.3 & 36.8538840379084 & -2.55388403790839 \tabularnewline
170 & 16.5 & 20.0490622862441 & -3.54906228624408 \tabularnewline
171 & 3 & 11.1163464919011 & -8.11634649190106 \tabularnewline
172 & 0.7 & 7.63974072244449 & -6.93974072244449 \tabularnewline
173 & 20.5 & 16.5483018503841 & 3.95169814961585 \tabularnewline
174 & 16.9 & 16.4345934563173 & 0.465406543682701 \tabularnewline
175 & 25.3 & 21.2994679454584 & 4.00053205454165 \tabularnewline
176 & 9.9 & 10.7677005593322 & -0.86770055933225 \tabularnewline
177 & 13.1 & 16.1164135491316 & -3.01641354913162 \tabularnewline
178 & 29.9 & 27.8772649795187 & 2.02273502048125 \tabularnewline
179 & 22.5 & 20.9181999665676 & 1.58180003343244 \tabularnewline
180 & 16.9 & 23.5872809516682 & -6.68728095166824 \tabularnewline
181 & 26.6 & 25.3533225366803 & 1.24667746331972 \tabularnewline
182 & 0 & 4.04299487310511 & -4.04299487310511 \tabularnewline
183 & 11.5 & 15.9155116808685 & -4.41551168086846 \tabularnewline
184 & 12.1 & 17.0295610947951 & -4.92956109479505 \tabularnewline
185 & 17.5 & 17.9949640789798 & -0.494964078979783 \tabularnewline
186 & 8.6 & 11.4497888643528 & -2.84978886435281 \tabularnewline
187 & 23.6 & 27.1253321310927 & -3.52533213109265 \tabularnewline
188 & 20.4 & 21.8908310811789 & -1.49083108117889 \tabularnewline
189 & 20.5 & 22.7590427634567 & -2.25904276345666 \tabularnewline
190 & 24.4 & 26.1530105168034 & -1.75301051680343 \tabularnewline
191 & 11.4 & 10.53186401937 & 0.86813598062996 \tabularnewline
192 & 38.1 & 30.7188055981424 & 7.38119440185762 \tabularnewline
193 & 15.9 & 17.5498420644491 & -1.64984206444909 \tabularnewline
194 & 24.7 & 26.5539637927033 & -1.8539637927033 \tabularnewline
195 & 22.8 & 17.6276663457037 & 5.17233365429633 \tabularnewline
196 & 25.5 & 22.5114688699609 & 2.98853113003907 \tabularnewline
197 & 22 & 17.4820721163212 & 4.51792788367879 \tabularnewline
198 & 17.7 & 19.8104714052382 & -2.1104714052382 \tabularnewline
199 & 6.6 & 6.70491637417965 & -0.104916374179649 \tabularnewline
200 & 23.6 & 18.4562011638055 & 5.1437988361945 \tabularnewline
201 & 12.2 & 15.6839738148258 & -3.48397381482581 \tabularnewline
202 & 22.1 & 15.8993196037949 & 6.20068039620507 \tabularnewline
203 & 28.7 & 27.3015949362627 & 1.39840506373726 \tabularnewline
204 & 6 & 14.8369093058723 & -8.83690930587227 \tabularnewline
205 & 34.8 & 34.8990788282207 & -0.0990788282207168 \tabularnewline
206 & 16.6 & 15.256974994356 & 1.34302500564402 \tabularnewline
207 & 32.9 & 22.8315196499761 & 10.0684803500239 \tabularnewline
208 & 32.8 & 26.7148132409084 & 6.0851867590916 \tabularnewline
209 & 9.6 & 13.5631343619174 & -3.96313436191745 \tabularnewline
210 & 10.8 & 14.8494756025136 & -4.04947560251364 \tabularnewline
211 & 7.1 & 12.4333666954267 & -5.33336669542668 \tabularnewline
212 & 27.2 & 25.1319146304935 & 2.06808536950653 \tabularnewline
213 & 19.5 & 15.6104244753107 & 3.88957552468933 \tabularnewline
214 & 18.7 & 21.2363373508427 & -2.5363373508427 \tabularnewline
215 & 19.5 & 14.8400854652166 & 4.65991453478336 \tabularnewline
216 & 47.5 & 57.6573599746697 & -10.1573599746697 \tabularnewline
217 & 13.6 & 11.6352700462731 & 1.96472995372692 \tabularnewline
218 & 7.5 & 9.5822790438326 & -2.0822790438326 \tabularnewline
219 & 24.5 & 23.7283898855993 & 0.77161011440069 \tabularnewline
220 & 15 & 17.3687173565667 & -2.36871735656672 \tabularnewline
221 & 12.4 & 20.3580207930818 & -7.9580207930818 \tabularnewline
222 & 26 & 30.2669757210485 & -4.2669757210485 \tabularnewline
223 & 11.5 & 17.7084286328179 & -6.20842863281793 \tabularnewline
224 & 5.2 & 15.6868365103193 & -10.4868365103193 \tabularnewline
225 & 10.9 & 19.4668148624532 & -8.56681486245325 \tabularnewline
226 & 12.5 & 12.6883831303368 & -0.188383130336762 \tabularnewline
227 & 14.8 & 18.9405825274766 & -4.14058252747659 \tabularnewline
228 & 25.2 & 22.5933082297581 & 2.6066917702419 \tabularnewline
229 & 14.9 & 17.1605329621295 & -2.26053296212948 \tabularnewline
230 & 17 & 20.3449711295063 & -3.34497112950626 \tabularnewline
231 & 10.6 & 19.2845024228963 & -8.68450242289632 \tabularnewline
232 & 16.1 & 20.9884924193453 & -4.88849241934534 \tabularnewline
233 & 15.4 & 16.7311001175373 & -1.33110011753733 \tabularnewline
234 & 26.7 & 22.9031023001526 & 3.79689769984742 \tabularnewline
235 & 25.8 & 20.7713869655334 & 5.02861303446664 \tabularnewline
236 & 18.6 & 21.8876400171782 & -3.28764001717816 \tabularnewline
237 & 24.8 & 21.8082026095979 & 2.99179739040208 \tabularnewline
238 & 27.3 & 33.4730902722564 & -6.17309027225636 \tabularnewline
239 & 12.4 & 15.2491930772909 & -2.84919307729091 \tabularnewline
240 & 29.9 & 25.5721871339394 & 4.32781286606062 \tabularnewline
241 & 17 & 14.8975448964825 & 2.10245510351754 \tabularnewline
242 & 35 & 35.7324865140208 & -0.732486514020806 \tabularnewline
243 & 30.4 & 28.1028959500662 & 2.29710404993377 \tabularnewline
244 & 32.6 & 33.3382694065437 & -0.738269406543713 \tabularnewline
245 & 29 & 28.7467343738108 & 0.253265626189185 \tabularnewline
246 & 15.2 & 14.3447319945064 & 0.855268005493605 \tabularnewline
247 & 30.2 & 30.9722160816427 & -0.772216081642711 \tabularnewline
248 & 11 & 14.4187203372517 & -3.4187203372517 \tabularnewline
249 & 33.6 & 26.0329109647771 & 7.56708903522289 \tabularnewline
250 & 29.3 & 35.5837217140321 & -6.2837217140321 \tabularnewline
251 & 26 & 25.0034281027273 & 0.996571897272681 \tabularnewline
252 & 31.9 & 27.3979694372055 & 4.50203056279448 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190063&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.3[/C][C]15.9199351191195[/C][C]-3.61993511911949[/C][/ROW]
[ROW][C]2[/C][C]6.1[/C][C]8.66045668215501[/C][C]-2.56045668215501[/C][/ROW]
[ROW][C]3[/C][C]25.3[/C][C]18.6822450779901[/C][C]6.61775492200987[/C][/ROW]
[ROW][C]4[/C][C]10.4[/C][C]11.767791802012[/C][C]-1.36779180201196[/C][/ROW]
[ROW][C]5[/C][C]28.7[/C][C]27.4821748823409[/C][C]1.21782511765909[/C][/ROW]
[ROW][C]6[/C][C]20.9[/C][C]17.4715562795515[/C][C]3.42844372044848[/C][/ROW]
[ROW][C]7[/C][C]19.2[/C][C]16.5946891097283[/C][C]2.60531089027173[/C][/ROW]
[ROW][C]8[/C][C]12.4[/C][C]14.1586844912188[/C][C]-1.75868449121883[/C][/ROW]
[ROW][C]9[/C][C]4.1[/C][C]9.88578105584531[/C][C]-5.78578105584531[/C][/ROW]
[ROW][C]10[/C][C]11.7[/C][C]10.6706676482444[/C][C]1.02933235175557[/C][/ROW]
[ROW][C]11[/C][C]7.1[/C][C]9.41442817274954[/C][C]-2.31442817274954[/C][/ROW]
[ROW][C]12[/C][C]7.8[/C][C]12.7220441516948[/C][C]-4.92204415169484[/C][/ROW]
[ROW][C]13[/C][C]20.8[/C][C]17.8703315980842[/C][C]2.92966840191576[/C][/ROW]
[ROW][C]14[/C][C]21.2[/C][C]24.7240559254832[/C][C]-3.52405592548321[/C][/ROW]
[ROW][C]15[/C][C]22.1[/C][C]24.2112524780163[/C][C]-2.11125247801627[/C][/ROW]
[ROW][C]16[/C][C]20.9[/C][C]22.8692758403064[/C][C]-1.96927584030642[/C][/ROW]
[ROW][C]17[/C][C]29[/C][C]23.8693062785825[/C][C]5.13069372141754[/C][/ROW]
[ROW][C]18[/C][C]22.9[/C][C]19.5098714428533[/C][C]3.39012855714671[/C][/ROW]
[ROW][C]19[/C][C]16[/C][C]16.7715315573044[/C][C]-0.77153155730443[/C][/ROW]
[ROW][C]20[/C][C]16.5[/C][C]22.6568857883471[/C][C]-6.15688578834707[/C][/ROW]
[ROW][C]21[/C][C]19.1[/C][C]20.4967148773441[/C][C]-1.39671487734409[/C][/ROW]
[ROW][C]22[/C][C]15.2[/C][C]19.4831158782399[/C][C]-4.28311587823991[/C][/ROW]
[ROW][C]23[/C][C]15.6[/C][C]9.88667914950284[/C][C]5.71332085049716[/C][/ROW]
[ROW][C]24[/C][C]17.7[/C][C]11.3946515950854[/C][C]6.30534840491465[/C][/ROW]
[ROW][C]25[/C][C]14[/C][C]8.4798023684644[/C][C]5.5201976315356[/C][/ROW]
[ROW][C]26[/C][C]3.7[/C][C]8.22621456256947[/C][C]-4.52621456256947[/C][/ROW]
[ROW][C]27[/C][C]7.9[/C][C]9.10961026056871[/C][C]-1.20961026056871[/C][/ROW]
[ROW][C]28[/C][C]22.9[/C][C]17.6893542222526[/C][C]5.21064577774744[/C][/ROW]
[ROW][C]29[/C][C]3.7[/C][C]5.93115895930214[/C][C]-2.23115895930214[/C][/ROW]
[ROW][C]30[/C][C]8.8[/C][C]11.1058863131255[/C][C]-2.30588631312546[/C][/ROW]
[ROW][C]31[/C][C]11.9[/C][C]13.8415368913955[/C][C]-1.94153689139553[/C][/ROW]
[ROW][C]32[/C][C]5.7[/C][C]10.9045007967427[/C][C]-5.20450079674272[/C][/ROW]
[ROW][C]33[/C][C]11.8[/C][C]6.49335053340234[/C][C]5.30664946659766[/C][/ROW]
[ROW][C]34[/C][C]21.3[/C][C]24.2853912916875[/C][C]-2.98539129168751[/C][/ROW]
[ROW][C]35[/C][C]32.3[/C][C]31.9110851399653[/C][C]0.388914860034695[/C][/ROW]
[ROW][C]36[/C][C]40.1[/C][C]35.9973581653848[/C][C]4.10264183461519[/C][/ROW]
[ROW][C]37[/C][C]24.2[/C][C]23.8989061613896[/C][C]0.301093838610388[/C][/ROW]
[ROW][C]38[/C][C]28.4[/C][C]22.4596947735492[/C][C]5.94030522645076[/C][/ROW]
[ROW][C]39[/C][C]35.2[/C][C]42.2860334746234[/C][C]-7.08603347462343[/C][/ROW]
[ROW][C]40[/C][C]32.6[/C][C]32.0470575974818[/C][C]0.55294240251817[/C][/ROW]
[ROW][C]41[/C][C]34.5[/C][C]34.7310312083206[/C][C]-0.23103120832061[/C][/ROW]
[ROW][C]42[/C][C]32.9[/C][C]31.7475670637536[/C][C]1.15243293624635[/C][/ROW]
[ROW][C]43[/C][C]31.6[/C][C]33.4222038893585[/C][C]-1.82220388935851[/C][/ROW]
[ROW][C]44[/C][C]32[/C][C]26.3551367955531[/C][C]5.64486320444688[/C][/ROW]
[ROW][C]45[/C][C]7.7[/C][C]10.6728409364813[/C][C]-2.97284093648126[/C][/ROW]
[ROW][C]46[/C][C]13.9[/C][C]10.6913180392534[/C][C]3.20868196074656[/C][/ROW]
[ROW][C]47[/C][C]10.8[/C][C]8.07263666796648[/C][C]2.72736333203352[/C][/ROW]
[ROW][C]48[/C][C]5.6[/C][C]10.0569095365757[/C][C]-4.45690953657568[/C][/ROW]
[ROW][C]49[/C][C]13.6[/C][C]17.4763486296056[/C][C]-3.8763486296056[/C][/ROW]
[ROW][C]50[/C][C]4[/C][C]5.67412068913163[/C][C]-1.67412068913163[/C][/ROW]
[ROW][C]51[/C][C]10.2[/C][C]14.2483855068306[/C][C]-4.0483855068306[/C][/ROW]
[ROW][C]52[/C][C]6.6[/C][C]9.25193728759104[/C][C]-2.65193728759104[/C][/ROW]
[ROW][C]53[/C][C]8[/C][C]13.3198178917093[/C][C]-5.31981789170929[/C][/ROW]
[ROW][C]54[/C][C]6.3[/C][C]10.971615845097[/C][C]-4.67161584509702[/C][/ROW]
[ROW][C]55[/C][C]3.9[/C][C]7.38217468460199[/C][C]-3.48217468460199[/C][/ROW]
[ROW][C]56[/C][C]22.6[/C][C]23.0885315447135[/C][C]-0.488531544713525[/C][/ROW]
[ROW][C]57[/C][C]20.4[/C][C]25.4869596313078[/C][C]-5.08695963130785[/C][/ROW]
[ROW][C]58[/C][C]28[/C][C]27.3418809720908[/C][C]0.658119027909185[/C][/ROW]
[ROW][C]59[/C][C]31.5[/C][C]28.2960153517564[/C][C]3.20398464824362[/C][/ROW]
[ROW][C]60[/C][C]24.6[/C][C]25.8474395826721[/C][C]-1.24743958267213[/C][/ROW]
[ROW][C]61[/C][C]26.1[/C][C]25.5028366320646[/C][C]0.597163367935438[/C][/ROW]
[ROW][C]62[/C][C]29.8[/C][C]23.7946365962366[/C][C]6.00536340376343[/C][/ROW]
[ROW][C]63[/C][C]30.7[/C][C]27.5066215759799[/C][C]3.19337842402014[/C][/ROW]
[ROW][C]64[/C][C]25.8[/C][C]27.2502050472702[/C][C]-1.45020504727024[/C][/ROW]
[ROW][C]65[/C][C]32.3[/C][C]29.9472061065932[/C][C]2.35279389340683[/C][/ROW]
[ROW][C]66[/C][C]30[/C][C]26.3371791136746[/C][C]3.66282088632537[/C][/ROW]
[ROW][C]67[/C][C]21.5[/C][C]15.7637098071217[/C][C]5.73629019287832[/C][/ROW]
[ROW][C]68[/C][C]13.8[/C][C]15.4897015218144[/C][C]-1.68970152181436[/C][/ROW]
[ROW][C]69[/C][C]6.3[/C][C]9.00994077050197[/C][C]-2.70994077050197[/C][/ROW]
[ROW][C]70[/C][C]12.9[/C][C]13.8494499763274[/C][C]-0.949449976327361[/C][/ROW]
[ROW][C]71[/C][C]24.3[/C][C]19.8941410219652[/C][C]4.40585897803481[/C][/ROW]
[ROW][C]72[/C][C]8.8[/C][C]13.0257236162847[/C][C]-4.22572361628468[/C][/ROW]
[ROW][C]73[/C][C]8.5[/C][C]11.1000379214003[/C][C]-2.60003792140026[/C][/ROW]
[ROW][C]74[/C][C]13.5[/C][C]11.9402555156152[/C][C]1.55974448438485[/C][/ROW]
[ROW][C]75[/C][C]11.8[/C][C]16.4930881934111[/C][C]-4.69308819341111[/C][/ROW]
[ROW][C]76[/C][C]18.5[/C][C]12.4856909024298[/C][C]6.01430909757024[/C][/ROW]
[ROW][C]77[/C][C]8.8[/C][C]9.85099161677834[/C][C]-1.05099161677833[/C][/ROW]
[ROW][C]78[/C][C]22.2[/C][C]19.375098875049[/C][C]2.824901124951[/C][/ROW]
[ROW][C]79[/C][C]21.5[/C][C]22.7502279583558[/C][C]-1.25022795835576[/C][/ROW]
[ROW][C]80[/C][C]18.8[/C][C]24.3382649232555[/C][C]-5.53826492325547[/C][/ROW]
[ROW][C]81[/C][C]31.4[/C][C]22.249879143626[/C][C]9.15012085637403[/C][/ROW]
[ROW][C]82[/C][C]26.8[/C][C]18.2370459994813[/C][C]8.56295400051872[/C][/ROW]
[ROW][C]83[/C][C]18.4[/C][C]22.7821693873353[/C][C]-4.38216938733533[/C][/ROW]
[ROW][C]84[/C][C]27[/C][C]21.2425792054131[/C][C]5.75742079458693[/C][/ROW]
[ROW][C]85[/C][C]27[/C][C]26.6418037432797[/C][C]0.358196256720298[/C][/ROW]
[ROW][C]86[/C][C]26.6[/C][C]20.5691009411103[/C][C]6.03089905888975[/C][/ROW]
[ROW][C]87[/C][C]14.9[/C][C]17.6813573013418[/C][C]-2.78135730134179[/C][/ROW]
[ROW][C]88[/C][C]23.1[/C][C]22.3503753226859[/C][C]0.749624677314055[/C][/ROW]
[ROW][C]89[/C][C]8.3[/C][C]12.9003241142948[/C][C]-4.60032411429481[/C][/ROW]
[ROW][C]90[/C][C]14.1[/C][C]14.8894021525257[/C][C]-0.789402152525685[/C][/ROW]
[ROW][C]91[/C][C]20.5[/C][C]21.2407679844085[/C][C]-0.740767984408521[/C][/ROW]
[ROW][C]92[/C][C]18.2[/C][C]17.6747573477943[/C][C]0.5252426522057[/C][/ROW]
[ROW][C]93[/C][C]8.5[/C][C]11.410069501425[/C][C]-2.91006950142503[/C][/ROW]
[ROW][C]94[/C][C]24.9[/C][C]21.8591822531791[/C][C]3.04081774682085[/C][/ROW]
[ROW][C]95[/C][C]9[/C][C]14.6729796345423[/C][C]-5.67297963454225[/C][/ROW]
[ROW][C]96[/C][C]17.4[/C][C]16.0398580531667[/C][C]1.36014194683334[/C][/ROW]
[ROW][C]97[/C][C]9.6[/C][C]16.6504881056881[/C][C]-7.05048810568814[/C][/ROW]
[ROW][C]98[/C][C]11.3[/C][C]16.4559666574094[/C][C]-5.15596665740935[/C][/ROW]
[ROW][C]99[/C][C]17.8[/C][C]17.7779814296476[/C][C]0.0220185703523795[/C][/ROW]
[ROW][C]100[/C][C]22.2[/C][C]19.3728911453978[/C][C]2.82710885460221[/C][/ROW]
[ROW][C]101[/C][C]21.2[/C][C]18.7049343306496[/C][C]2.49506566935042[/C][/ROW]
[ROW][C]102[/C][C]20.4[/C][C]20.0482272617147[/C][C]0.351772738285287[/C][/ROW]
[ROW][C]103[/C][C]20.1[/C][C]17.6192113890169[/C][C]2.48078861098311[/C][/ROW]
[ROW][C]104[/C][C]22.3[/C][C]17.405848135294[/C][C]4.89415186470599[/C][/ROW]
[ROW][C]105[/C][C]25.4[/C][C]23.1396760226298[/C][C]2.26032397737025[/C][/ROW]
[ROW][C]106[/C][C]18[/C][C]17.9354625596383[/C][C]0.0645374403617317[/C][/ROW]
[ROW][C]107[/C][C]19.3[/C][C]25.1577361431077[/C][C]-5.85773614310773[/C][/ROW]
[ROW][C]108[/C][C]18.3[/C][C]21.4747449898227[/C][C]-3.17474498982269[/C][/ROW]
[ROW][C]109[/C][C]17.3[/C][C]12.9406689077959[/C][C]4.35933109220409[/C][/ROW]
[ROW][C]110[/C][C]21.4[/C][C]20.4799148237805[/C][C]0.920085176219468[/C][/ROW]
[ROW][C]111[/C][C]19.7[/C][C]19.3201044458803[/C][C]0.379895554119744[/C][/ROW]
[ROW][C]112[/C][C]28[/C][C]31.8338368586555[/C][C]-3.83383685865547[/C][/ROW]
[ROW][C]113[/C][C]22.1[/C][C]20.8296950565738[/C][C]1.27030494342621[/C][/ROW]
[ROW][C]114[/C][C]21.3[/C][C]20.0100823821335[/C][C]1.28991761786651[/C][/ROW]
[ROW][C]115[/C][C]26.7[/C][C]20.4915058452889[/C][C]6.20849415471114[/C][/ROW]
[ROW][C]116[/C][C]16.7[/C][C]16.3182672468256[/C][C]0.381732753174366[/C][/ROW]
[ROW][C]117[/C][C]20.1[/C][C]17.1728868961251[/C][C]2.92711310387494[/C][/ROW]
[ROW][C]118[/C][C]13.9[/C][C]14.5232871495932[/C][C]-0.623287149593224[/C][/ROW]
[ROW][C]119[/C][C]25.8[/C][C]18.9910447499522[/C][C]6.80895525004782[/C][/ROW]
[ROW][C]120[/C][C]18.1[/C][C]13.8767754045715[/C][C]4.22322459542847[/C][/ROW]
[ROW][C]121[/C][C]27.9[/C][C]20.3614805034152[/C][C]7.53851949658477[/C][/ROW]
[ROW][C]122[/C][C]25.3[/C][C]22.4103038163856[/C][C]2.88969618361437[/C][/ROW]
[ROW][C]123[/C][C]14.7[/C][C]14.5571458071537[/C][C]0.142854192846301[/C][/ROW]
[ROW][C]124[/C][C]16[/C][C]16.9782674361003[/C][C]-0.978267436100324[/C][/ROW]
[ROW][C]125[/C][C]13.8[/C][C]15.4870452657237[/C][C]-1.68704526572372[/C][/ROW]
[ROW][C]126[/C][C]17.5[/C][C]20.4375101915596[/C][C]-2.93751019155961[/C][/ROW]
[ROW][C]127[/C][C]27.2[/C][C]21.4402243554154[/C][C]5.75977564458459[/C][/ROW]
[ROW][C]128[/C][C]17.4[/C][C]9.4200555870639[/C][C]7.9799444129361[/C][/ROW]
[ROW][C]129[/C][C]20.8[/C][C]18.9777732029824[/C][C]1.82222679701762[/C][/ROW]
[ROW][C]130[/C][C]14.9[/C][C]14.7991969676981[/C][C]0.100803032301915[/C][/ROW]
[ROW][C]131[/C][C]18.1[/C][C]18.5645996711993[/C][C]-0.464599671199268[/C][/ROW]
[ROW][C]132[/C][C]22.7[/C][C]20.3319434762316[/C][C]2.36805652376843[/C][/ROW]
[ROW][C]133[/C][C]23.6[/C][C]24.3471793048803[/C][C]-0.747179304880333[/C][/ROW]
[ROW][C]134[/C][C]26.1[/C][C]21.0019635034233[/C][C]5.09803649657665[/C][/ROW]
[ROW][C]135[/C][C]24.4[/C][C]16.1162985857972[/C][C]8.28370141420284[/C][/ROW]
[ROW][C]136[/C][C]27.1[/C][C]26.1163216934992[/C][C]0.983678306500838[/C][/ROW]
[ROW][C]137[/C][C]21.8[/C][C]16.7805894113681[/C][C]5.01941058863192[/C][/ROW]
[ROW][C]138[/C][C]29.4[/C][C]26.1692123421551[/C][C]3.23078765784492[/C][/ROW]
[ROW][C]139[/C][C]22.4[/C][C]18.2318941061893[/C][C]4.16810589381072[/C][/ROW]
[ROW][C]140[/C][C]20.4[/C][C]28.488603671709[/C][C]-8.088603671709[/C][/ROW]
[ROW][C]141[/C][C]24.9[/C][C]21.3338471148058[/C][C]3.56615288519418[/C][/ROW]
[ROW][C]142[/C][C]18.3[/C][C]21.0672067930528[/C][C]-2.76720679305279[/C][/ROW]
[ROW][C]143[/C][C]23.3[/C][C]18.713483799741[/C][C]4.58651620025895[/C][/ROW]
[ROW][C]144[/C][C]9.4[/C][C]5.75066095675246[/C][C]3.64933904324754[/C][/ROW]
[ROW][C]145[/C][C]10.3[/C][C]9.29179047635031[/C][C]1.00820952364969[/C][/ROW]
[ROW][C]146[/C][C]14.2[/C][C]12.4686275228939[/C][C]1.73137247710615[/C][/ROW]
[ROW][C]147[/C][C]19.2[/C][C]22.8370105947116[/C][C]-3.63701059471163[/C][/ROW]
[ROW][C]148[/C][C]29.6[/C][C]23.2148783961225[/C][C]6.38512160387749[/C][/ROW]
[ROW][C]149[/C][C]5.3[/C][C]5.97065497901681[/C][C]-0.670654979016813[/C][/ROW]
[ROW][C]150[/C][C]25.2[/C][C]26.2176183728328[/C][C]-1.01761837283281[/C][/ROW]
[ROW][C]151[/C][C]9.4[/C][C]8.75571315178945[/C][C]0.644286848210549[/C][/ROW]
[ROW][C]152[/C][C]19.6[/C][C]22.1666915845716[/C][C]-2.56669158457162[/C][/ROW]
[ROW][C]153[/C][C]10.1[/C][C]4.80178286308688[/C][C]5.29821713691312[/C][/ROW]
[ROW][C]154[/C][C]16.5[/C][C]16.2463947917929[/C][C]0.253605208207122[/C][/ROW]
[ROW][C]155[/C][C]21[/C][C]21.1238865234689[/C][C]-0.123886523468921[/C][/ROW]
[ROW][C]156[/C][C]17.3[/C][C]11.5628913968837[/C][C]5.73710860311627[/C][/ROW]
[ROW][C]157[/C][C]31.2[/C][C]28.3065069996273[/C][C]2.89349300037268[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]15.0998216155703[/C][C]-5.09982161557034[/C][/ROW]
[ROW][C]159[/C][C]12.5[/C][C]11.4972512271511[/C][C]1.00274877284889[/C][/ROW]
[ROW][C]160[/C][C]22.5[/C][C]18.9285875858824[/C][C]3.5714124141176[/C][/ROW]
[ROW][C]161[/C][C]9.4[/C][C]11.7579650770766[/C][C]-2.35796507707663[/C][/ROW]
[ROW][C]162[/C][C]14.6[/C][C]17.5179412643655[/C][C]-2.9179412643655[/C][/ROW]
[ROW][C]163[/C][C]13[/C][C]15.034537989247[/C][C]-2.03453798924697[/C][/ROW]
[ROW][C]164[/C][C]15.1[/C][C]15.0606572571262[/C][C]0.0393427428737826[/C][/ROW]
[ROW][C]165[/C][C]27.3[/C][C]26.7860027180342[/C][C]0.513997281965775[/C][/ROW]
[ROW][C]166[/C][C]19.2[/C][C]18.3839354686455[/C][C]0.816064531354535[/C][/ROW]
[ROW][C]167[/C][C]21.8[/C][C]17.0153055771263[/C][C]4.78469442287371[/C][/ROW]
[ROW][C]168[/C][C]20.3[/C][C]19.0306921006514[/C][C]1.2693078993486[/C][/ROW]
[ROW][C]169[/C][C]34.3[/C][C]36.8538840379084[/C][C]-2.55388403790839[/C][/ROW]
[ROW][C]170[/C][C]16.5[/C][C]20.0490622862441[/C][C]-3.54906228624408[/C][/ROW]
[ROW][C]171[/C][C]3[/C][C]11.1163464919011[/C][C]-8.11634649190106[/C][/ROW]
[ROW][C]172[/C][C]0.7[/C][C]7.63974072244449[/C][C]-6.93974072244449[/C][/ROW]
[ROW][C]173[/C][C]20.5[/C][C]16.5483018503841[/C][C]3.95169814961585[/C][/ROW]
[ROW][C]174[/C][C]16.9[/C][C]16.4345934563173[/C][C]0.465406543682701[/C][/ROW]
[ROW][C]175[/C][C]25.3[/C][C]21.2994679454584[/C][C]4.00053205454165[/C][/ROW]
[ROW][C]176[/C][C]9.9[/C][C]10.7677005593322[/C][C]-0.86770055933225[/C][/ROW]
[ROW][C]177[/C][C]13.1[/C][C]16.1164135491316[/C][C]-3.01641354913162[/C][/ROW]
[ROW][C]178[/C][C]29.9[/C][C]27.8772649795187[/C][C]2.02273502048125[/C][/ROW]
[ROW][C]179[/C][C]22.5[/C][C]20.9181999665676[/C][C]1.58180003343244[/C][/ROW]
[ROW][C]180[/C][C]16.9[/C][C]23.5872809516682[/C][C]-6.68728095166824[/C][/ROW]
[ROW][C]181[/C][C]26.6[/C][C]25.3533225366803[/C][C]1.24667746331972[/C][/ROW]
[ROW][C]182[/C][C]0[/C][C]4.04299487310511[/C][C]-4.04299487310511[/C][/ROW]
[ROW][C]183[/C][C]11.5[/C][C]15.9155116808685[/C][C]-4.41551168086846[/C][/ROW]
[ROW][C]184[/C][C]12.1[/C][C]17.0295610947951[/C][C]-4.92956109479505[/C][/ROW]
[ROW][C]185[/C][C]17.5[/C][C]17.9949640789798[/C][C]-0.494964078979783[/C][/ROW]
[ROW][C]186[/C][C]8.6[/C][C]11.4497888643528[/C][C]-2.84978886435281[/C][/ROW]
[ROW][C]187[/C][C]23.6[/C][C]27.1253321310927[/C][C]-3.52533213109265[/C][/ROW]
[ROW][C]188[/C][C]20.4[/C][C]21.8908310811789[/C][C]-1.49083108117889[/C][/ROW]
[ROW][C]189[/C][C]20.5[/C][C]22.7590427634567[/C][C]-2.25904276345666[/C][/ROW]
[ROW][C]190[/C][C]24.4[/C][C]26.1530105168034[/C][C]-1.75301051680343[/C][/ROW]
[ROW][C]191[/C][C]11.4[/C][C]10.53186401937[/C][C]0.86813598062996[/C][/ROW]
[ROW][C]192[/C][C]38.1[/C][C]30.7188055981424[/C][C]7.38119440185762[/C][/ROW]
[ROW][C]193[/C][C]15.9[/C][C]17.5498420644491[/C][C]-1.64984206444909[/C][/ROW]
[ROW][C]194[/C][C]24.7[/C][C]26.5539637927033[/C][C]-1.8539637927033[/C][/ROW]
[ROW][C]195[/C][C]22.8[/C][C]17.6276663457037[/C][C]5.17233365429633[/C][/ROW]
[ROW][C]196[/C][C]25.5[/C][C]22.5114688699609[/C][C]2.98853113003907[/C][/ROW]
[ROW][C]197[/C][C]22[/C][C]17.4820721163212[/C][C]4.51792788367879[/C][/ROW]
[ROW][C]198[/C][C]17.7[/C][C]19.8104714052382[/C][C]-2.1104714052382[/C][/ROW]
[ROW][C]199[/C][C]6.6[/C][C]6.70491637417965[/C][C]-0.104916374179649[/C][/ROW]
[ROW][C]200[/C][C]23.6[/C][C]18.4562011638055[/C][C]5.1437988361945[/C][/ROW]
[ROW][C]201[/C][C]12.2[/C][C]15.6839738148258[/C][C]-3.48397381482581[/C][/ROW]
[ROW][C]202[/C][C]22.1[/C][C]15.8993196037949[/C][C]6.20068039620507[/C][/ROW]
[ROW][C]203[/C][C]28.7[/C][C]27.3015949362627[/C][C]1.39840506373726[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]14.8369093058723[/C][C]-8.83690930587227[/C][/ROW]
[ROW][C]205[/C][C]34.8[/C][C]34.8990788282207[/C][C]-0.0990788282207168[/C][/ROW]
[ROW][C]206[/C][C]16.6[/C][C]15.256974994356[/C][C]1.34302500564402[/C][/ROW]
[ROW][C]207[/C][C]32.9[/C][C]22.8315196499761[/C][C]10.0684803500239[/C][/ROW]
[ROW][C]208[/C][C]32.8[/C][C]26.7148132409084[/C][C]6.0851867590916[/C][/ROW]
[ROW][C]209[/C][C]9.6[/C][C]13.5631343619174[/C][C]-3.96313436191745[/C][/ROW]
[ROW][C]210[/C][C]10.8[/C][C]14.8494756025136[/C][C]-4.04947560251364[/C][/ROW]
[ROW][C]211[/C][C]7.1[/C][C]12.4333666954267[/C][C]-5.33336669542668[/C][/ROW]
[ROW][C]212[/C][C]27.2[/C][C]25.1319146304935[/C][C]2.06808536950653[/C][/ROW]
[ROW][C]213[/C][C]19.5[/C][C]15.6104244753107[/C][C]3.88957552468933[/C][/ROW]
[ROW][C]214[/C][C]18.7[/C][C]21.2363373508427[/C][C]-2.5363373508427[/C][/ROW]
[ROW][C]215[/C][C]19.5[/C][C]14.8400854652166[/C][C]4.65991453478336[/C][/ROW]
[ROW][C]216[/C][C]47.5[/C][C]57.6573599746697[/C][C]-10.1573599746697[/C][/ROW]
[ROW][C]217[/C][C]13.6[/C][C]11.6352700462731[/C][C]1.96472995372692[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]9.5822790438326[/C][C]-2.0822790438326[/C][/ROW]
[ROW][C]219[/C][C]24.5[/C][C]23.7283898855993[/C][C]0.77161011440069[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]17.3687173565667[/C][C]-2.36871735656672[/C][/ROW]
[ROW][C]221[/C][C]12.4[/C][C]20.3580207930818[/C][C]-7.9580207930818[/C][/ROW]
[ROW][C]222[/C][C]26[/C][C]30.2669757210485[/C][C]-4.2669757210485[/C][/ROW]
[ROW][C]223[/C][C]11.5[/C][C]17.7084286328179[/C][C]-6.20842863281793[/C][/ROW]
[ROW][C]224[/C][C]5.2[/C][C]15.6868365103193[/C][C]-10.4868365103193[/C][/ROW]
[ROW][C]225[/C][C]10.9[/C][C]19.4668148624532[/C][C]-8.56681486245325[/C][/ROW]
[ROW][C]226[/C][C]12.5[/C][C]12.6883831303368[/C][C]-0.188383130336762[/C][/ROW]
[ROW][C]227[/C][C]14.8[/C][C]18.9405825274766[/C][C]-4.14058252747659[/C][/ROW]
[ROW][C]228[/C][C]25.2[/C][C]22.5933082297581[/C][C]2.6066917702419[/C][/ROW]
[ROW][C]229[/C][C]14.9[/C][C]17.1605329621295[/C][C]-2.26053296212948[/C][/ROW]
[ROW][C]230[/C][C]17[/C][C]20.3449711295063[/C][C]-3.34497112950626[/C][/ROW]
[ROW][C]231[/C][C]10.6[/C][C]19.2845024228963[/C][C]-8.68450242289632[/C][/ROW]
[ROW][C]232[/C][C]16.1[/C][C]20.9884924193453[/C][C]-4.88849241934534[/C][/ROW]
[ROW][C]233[/C][C]15.4[/C][C]16.7311001175373[/C][C]-1.33110011753733[/C][/ROW]
[ROW][C]234[/C][C]26.7[/C][C]22.9031023001526[/C][C]3.79689769984742[/C][/ROW]
[ROW][C]235[/C][C]25.8[/C][C]20.7713869655334[/C][C]5.02861303446664[/C][/ROW]
[ROW][C]236[/C][C]18.6[/C][C]21.8876400171782[/C][C]-3.28764001717816[/C][/ROW]
[ROW][C]237[/C][C]24.8[/C][C]21.8082026095979[/C][C]2.99179739040208[/C][/ROW]
[ROW][C]238[/C][C]27.3[/C][C]33.4730902722564[/C][C]-6.17309027225636[/C][/ROW]
[ROW][C]239[/C][C]12.4[/C][C]15.2491930772909[/C][C]-2.84919307729091[/C][/ROW]
[ROW][C]240[/C][C]29.9[/C][C]25.5721871339394[/C][C]4.32781286606062[/C][/ROW]
[ROW][C]241[/C][C]17[/C][C]14.8975448964825[/C][C]2.10245510351754[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]35.7324865140208[/C][C]-0.732486514020806[/C][/ROW]
[ROW][C]243[/C][C]30.4[/C][C]28.1028959500662[/C][C]2.29710404993377[/C][/ROW]
[ROW][C]244[/C][C]32.6[/C][C]33.3382694065437[/C][C]-0.738269406543713[/C][/ROW]
[ROW][C]245[/C][C]29[/C][C]28.7467343738108[/C][C]0.253265626189185[/C][/ROW]
[ROW][C]246[/C][C]15.2[/C][C]14.3447319945064[/C][C]0.855268005493605[/C][/ROW]
[ROW][C]247[/C][C]30.2[/C][C]30.9722160816427[/C][C]-0.772216081642711[/C][/ROW]
[ROW][C]248[/C][C]11[/C][C]14.4187203372517[/C][C]-3.4187203372517[/C][/ROW]
[ROW][C]249[/C][C]33.6[/C][C]26.0329109647771[/C][C]7.56708903522289[/C][/ROW]
[ROW][C]250[/C][C]29.3[/C][C]35.5837217140321[/C][C]-6.2837217140321[/C][/ROW]
[ROW][C]251[/C][C]26[/C][C]25.0034281027273[/C][C]0.996571897272681[/C][/ROW]
[ROW][C]252[/C][C]31.9[/C][C]27.3979694372055[/C][C]4.50203056279448[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190063&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190063&T=4

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.3	15.9199351191195	-3.61993511911949
2	6.1	8.66045668215501	-2.56045668215501
3	25.3	18.6822450779901	6.61775492200987
4	10.4	11.767791802012	-1.36779180201196
5	28.7	27.4821748823409	1.21782511765909
6	20.9	17.4715562795515	3.42844372044848
7	19.2	16.5946891097283	2.60531089027173
8	12.4	14.1586844912188	-1.75868449121883
9	4.1	9.88578105584531	-5.78578105584531
10	11.7	10.6706676482444	1.02933235175557
11	7.1	9.41442817274954	-2.31442817274954
12	7.8	12.7220441516948	-4.92204415169484
13	20.8	17.8703315980842	2.92966840191576
14	21.2	24.7240559254832	-3.52405592548321
15	22.1	24.2112524780163	-2.11125247801627
16	20.9	22.8692758403064	-1.96927584030642
17	29	23.8693062785825	5.13069372141754
18	22.9	19.5098714428533	3.39012855714671
19	16	16.7715315573044	-0.77153155730443
20	16.5	22.6568857883471	-6.15688578834707
21	19.1	20.4967148773441	-1.39671487734409
22	15.2	19.4831158782399	-4.28311587823991
23	15.6	9.88667914950284	5.71332085049716
24	17.7	11.3946515950854	6.30534840491465
25	14	8.4798023684644	5.5201976315356
26	3.7	8.22621456256947	-4.52621456256947
27	7.9	9.10961026056871	-1.20961026056871
28	22.9	17.6893542222526	5.21064577774744
29	3.7	5.93115895930214	-2.23115895930214
30	8.8	11.1058863131255	-2.30588631312546
31	11.9	13.8415368913955	-1.94153689139553
32	5.7	10.9045007967427	-5.20450079674272
33	11.8	6.49335053340234	5.30664946659766
34	21.3	24.2853912916875	-2.98539129168751
35	32.3	31.9110851399653	0.388914860034695
36	40.1	35.9973581653848	4.10264183461519
37	24.2	23.8989061613896	0.301093838610388
38	28.4	22.4596947735492	5.94030522645076
39	35.2	42.2860334746234	-7.08603347462343
40	32.6	32.0470575974818	0.55294240251817
41	34.5	34.7310312083206	-0.23103120832061
42	32.9	31.7475670637536	1.15243293624635
43	31.6	33.4222038893585	-1.82220388935851
44	32	26.3551367955531	5.64486320444688
45	7.7	10.6728409364813	-2.97284093648126
46	13.9	10.6913180392534	3.20868196074656
47	10.8	8.07263666796648	2.72736333203352
48	5.6	10.0569095365757	-4.45690953657568
49	13.6	17.4763486296056	-3.8763486296056
50	4	5.67412068913163	-1.67412068913163
51	10.2	14.2483855068306	-4.0483855068306
52	6.6	9.25193728759104	-2.65193728759104
53	8	13.3198178917093	-5.31981789170929
54	6.3	10.971615845097	-4.67161584509702
55	3.9	7.38217468460199	-3.48217468460199
56	22.6	23.0885315447135	-0.488531544713525
57	20.4	25.4869596313078	-5.08695963130785
58	28	27.3418809720908	0.658119027909185
59	31.5	28.2960153517564	3.20398464824362
60	24.6	25.8474395826721	-1.24743958267213
61	26.1	25.5028366320646	0.597163367935438
62	29.8	23.7946365962366	6.00536340376343
63	30.7	27.5066215759799	3.19337842402014
64	25.8	27.2502050472702	-1.45020504727024
65	32.3	29.9472061065932	2.35279389340683
66	30	26.3371791136746	3.66282088632537
67	21.5	15.7637098071217	5.73629019287832
68	13.8	15.4897015218144	-1.68970152181436
69	6.3	9.00994077050197	-2.70994077050197
70	12.9	13.8494499763274	-0.949449976327361
71	24.3	19.8941410219652	4.40585897803481
72	8.8	13.0257236162847	-4.22572361628468
73	8.5	11.1000379214003	-2.60003792140026
74	13.5	11.9402555156152	1.55974448438485
75	11.8	16.4930881934111	-4.69308819341111
76	18.5	12.4856909024298	6.01430909757024
77	8.8	9.85099161677834	-1.05099161677833
78	22.2	19.375098875049	2.824901124951
79	21.5	22.7502279583558	-1.25022795835576
80	18.8	24.3382649232555	-5.53826492325547
81	31.4	22.249879143626	9.15012085637403
82	26.8	18.2370459994813	8.56295400051872
83	18.4	22.7821693873353	-4.38216938733533
84	27	21.2425792054131	5.75742079458693
85	27	26.6418037432797	0.358196256720298
86	26.6	20.5691009411103	6.03089905888975
87	14.9	17.6813573013418	-2.78135730134179
88	23.1	22.3503753226859	0.749624677314055
89	8.3	12.9003241142948	-4.60032411429481
90	14.1	14.8894021525257	-0.789402152525685
91	20.5	21.2407679844085	-0.740767984408521
92	18.2	17.6747573477943	0.5252426522057
93	8.5	11.410069501425	-2.91006950142503
94	24.9	21.8591822531791	3.04081774682085
95	9	14.6729796345423	-5.67297963454225
96	17.4	16.0398580531667	1.36014194683334
97	9.6	16.6504881056881	-7.05048810568814
98	11.3	16.4559666574094	-5.15596665740935
99	17.8	17.7779814296476	0.0220185703523795
100	22.2	19.3728911453978	2.82710885460221
101	21.2	18.7049343306496	2.49506566935042
102	20.4	20.0482272617147	0.351772738285287
103	20.1	17.6192113890169	2.48078861098311
104	22.3	17.405848135294	4.89415186470599
105	25.4	23.1396760226298	2.26032397737025
106	18	17.9354625596383	0.0645374403617317
107	19.3	25.1577361431077	-5.85773614310773
108	18.3	21.4747449898227	-3.17474498982269
109	17.3	12.9406689077959	4.35933109220409
110	21.4	20.4799148237805	0.920085176219468
111	19.7	19.3201044458803	0.379895554119744
112	28	31.8338368586555	-3.83383685865547
113	22.1	20.8296950565738	1.27030494342621
114	21.3	20.0100823821335	1.28991761786651
115	26.7	20.4915058452889	6.20849415471114
116	16.7	16.3182672468256	0.381732753174366
117	20.1	17.1728868961251	2.92711310387494
118	13.9	14.5232871495932	-0.623287149593224
119	25.8	18.9910447499522	6.80895525004782
120	18.1	13.8767754045715	4.22322459542847
121	27.9	20.3614805034152	7.53851949658477
122	25.3	22.4103038163856	2.88969618361437
123	14.7	14.5571458071537	0.142854192846301
124	16	16.9782674361003	-0.978267436100324
125	13.8	15.4870452657237	-1.68704526572372
126	17.5	20.4375101915596	-2.93751019155961
127	27.2	21.4402243554154	5.75977564458459
128	17.4	9.4200555870639	7.9799444129361
129	20.8	18.9777732029824	1.82222679701762
130	14.9	14.7991969676981	0.100803032301915
131	18.1	18.5645996711993	-0.464599671199268
132	22.7	20.3319434762316	2.36805652376843
133	23.6	24.3471793048803	-0.747179304880333
134	26.1	21.0019635034233	5.09803649657665
135	24.4	16.1162985857972	8.28370141420284
136	27.1	26.1163216934992	0.983678306500838
137	21.8	16.7805894113681	5.01941058863192
138	29.4	26.1692123421551	3.23078765784492
139	22.4	18.2318941061893	4.16810589381072
140	20.4	28.488603671709	-8.088603671709
141	24.9	21.3338471148058	3.56615288519418
142	18.3	21.0672067930528	-2.76720679305279
143	23.3	18.713483799741	4.58651620025895
144	9.4	5.75066095675246	3.64933904324754
145	10.3	9.29179047635031	1.00820952364969
146	14.2	12.4686275228939	1.73137247710615
147	19.2	22.8370105947116	-3.63701059471163
148	29.6	23.2148783961225	6.38512160387749
149	5.3	5.97065497901681	-0.670654979016813
150	25.2	26.2176183728328	-1.01761837283281
151	9.4	8.75571315178945	0.644286848210549
152	19.6	22.1666915845716	-2.56669158457162
153	10.1	4.80178286308688	5.29821713691312
154	16.5	16.2463947917929	0.253605208207122
155	21	21.1238865234689	-0.123886523468921
156	17.3	11.5628913968837	5.73710860311627
157	31.2	28.3065069996273	2.89349300037268
158	10	15.0998216155703	-5.09982161557034
159	12.5	11.4972512271511	1.00274877284889
160	22.5	18.9285875858824	3.5714124141176
161	9.4	11.7579650770766	-2.35796507707663
162	14.6	17.5179412643655	-2.9179412643655
163	13	15.034537989247	-2.03453798924697
164	15.1	15.0606572571262	0.0393427428737826
165	27.3	26.7860027180342	0.513997281965775
166	19.2	18.3839354686455	0.816064531354535
167	21.8	17.0153055771263	4.78469442287371
168	20.3	19.0306921006514	1.2693078993486
169	34.3	36.8538840379084	-2.55388403790839
170	16.5	20.0490622862441	-3.54906228624408
171	3	11.1163464919011	-8.11634649190106
172	0.7	7.63974072244449	-6.93974072244449
173	20.5	16.5483018503841	3.95169814961585
174	16.9	16.4345934563173	0.465406543682701
175	25.3	21.2994679454584	4.00053205454165
176	9.9	10.7677005593322	-0.86770055933225
177	13.1	16.1164135491316	-3.01641354913162
178	29.9	27.8772649795187	2.02273502048125
179	22.5	20.9181999665676	1.58180003343244
180	16.9	23.5872809516682	-6.68728095166824
181	26.6	25.3533225366803	1.24667746331972
182	0	4.04299487310511	-4.04299487310511
183	11.5	15.9155116808685	-4.41551168086846
184	12.1	17.0295610947951	-4.92956109479505
185	17.5	17.9949640789798	-0.494964078979783
186	8.6	11.4497888643528	-2.84978886435281
187	23.6	27.1253321310927	-3.52533213109265
188	20.4	21.8908310811789	-1.49083108117889
189	20.5	22.7590427634567	-2.25904276345666
190	24.4	26.1530105168034	-1.75301051680343
191	11.4	10.53186401937	0.86813598062996
192	38.1	30.7188055981424	7.38119440185762
193	15.9	17.5498420644491	-1.64984206444909
194	24.7	26.5539637927033	-1.8539637927033
195	22.8	17.6276663457037	5.17233365429633
196	25.5	22.5114688699609	2.98853113003907
197	22	17.4820721163212	4.51792788367879
198	17.7	19.8104714052382	-2.1104714052382
199	6.6	6.70491637417965	-0.104916374179649
200	23.6	18.4562011638055	5.1437988361945
201	12.2	15.6839738148258	-3.48397381482581
202	22.1	15.8993196037949	6.20068039620507
203	28.7	27.3015949362627	1.39840506373726
204	6	14.8369093058723	-8.83690930587227
205	34.8	34.8990788282207	-0.0990788282207168
206	16.6	15.256974994356	1.34302500564402
207	32.9	22.8315196499761	10.0684803500239
208	32.8	26.7148132409084	6.0851867590916
209	9.6	13.5631343619174	-3.96313436191745
210	10.8	14.8494756025136	-4.04947560251364
211	7.1	12.4333666954267	-5.33336669542668
212	27.2	25.1319146304935	2.06808536950653
213	19.5	15.6104244753107	3.88957552468933
214	18.7	21.2363373508427	-2.5363373508427
215	19.5	14.8400854652166	4.65991453478336
216	47.5	57.6573599746697	-10.1573599746697
217	13.6	11.6352700462731	1.96472995372692
218	7.5	9.5822790438326	-2.0822790438326
219	24.5	23.7283898855993	0.77161011440069
220	15	17.3687173565667	-2.36871735656672
221	12.4	20.3580207930818	-7.9580207930818
222	26	30.2669757210485	-4.2669757210485
223	11.5	17.7084286328179	-6.20842863281793
224	5.2	15.6868365103193	-10.4868365103193
225	10.9	19.4668148624532	-8.56681486245325
226	12.5	12.6883831303368	-0.188383130336762
227	14.8	18.9405825274766	-4.14058252747659
228	25.2	22.5933082297581	2.6066917702419
229	14.9	17.1605329621295	-2.26053296212948
230	17	20.3449711295063	-3.34497112950626
231	10.6	19.2845024228963	-8.68450242289632
232	16.1	20.9884924193453	-4.88849241934534
233	15.4	16.7311001175373	-1.33110011753733
234	26.7	22.9031023001526	3.79689769984742
235	25.8	20.7713869655334	5.02861303446664
236	18.6	21.8876400171782	-3.28764001717816
237	24.8	21.8082026095979	2.99179739040208
238	27.3	33.4730902722564	-6.17309027225636
239	12.4	15.2491930772909	-2.84919307729091
240	29.9	25.5721871339394	4.32781286606062
241	17	14.8975448964825	2.10245510351754
242	35	35.7324865140208	-0.732486514020806
243	30.4	28.1028959500662	2.29710404993377
244	32.6	33.3382694065437	-0.738269406543713
245	29	28.7467343738108	0.253265626189185
246	15.2	14.3447319945064	0.855268005493605
247	30.2	30.9722160816427	-0.772216081642711
248	11	14.4187203372517	-3.4187203372517
249	33.6	26.0329109647771	7.56708903522289
250	29.3	35.5837217140321	-6.2837217140321
251	26	25.0034281027273	0.996571897272681
252	31.9	27.3979694372055	4.50203056279448

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
18	0.000127427931555219	0.000254855863110437	0.999872572068445
19	6.23033066595257e-06	1.24606613319051e-05	0.999993769669334
20	3.6191491818827e-07	7.23829836376539e-07	0.999999638085082
21	2.64584378661583e-08	5.29168757323166e-08	0.999999973541562
22	1.04108762120523e-09	2.08217524241046e-09	0.999999998958912
23	2.55410729395196e-10	5.10821458790392e-10	0.999999999744589
24	1.34262454432828e-11	2.68524908865656e-11	0.999999999986574
25	6.16542019451254e-13	1.23308403890251e-12	0.999999999999383
26	3.6189416315068e-14	7.2378832630136e-14	0.999999999999964
27	1.90062479680284e-15	3.80124959360568e-15	0.999999999999998
28	1.6608574150786e-16	3.3217148301572e-16	1
29	7.02343286150802e-18	1.4046865723016e-17	1
30	3.58705225679735e-19	7.17410451359469e-19	1
31	1.5349144820379e-20	3.0698289640758e-20	1
32	7.47823395113745e-22	1.49564679022749e-21	1
33	2.9940018148274e-23	5.98800362965481e-23	1
34	1.12594507116991e-24	2.25189014233983e-24	1
35	1.53813341997565e-24	3.07626683995131e-24	1
36	4.71465498344275e-24	9.42930996688549e-24	1
37	3.02398823079062e-25	6.04797646158124e-25	1
38	2.23714087769587e-26	4.47428175539173e-26	1
39	1.51219006209464e-27	3.02438012418929e-27	1
40	7.29428292565371e-29	1.45885658513074e-28	1
41	4.09844116113918e-30	8.19688232227835e-30	1
42	2.03178603822745e-31	4.0635720764549e-31	1
43	9.4942448633285e-33	1.8988489726657e-32	1
44	6.12928135361992e-34	1.22585627072398e-33	1
45	4.81878689883128e-35	9.63757379766255e-35	1
46	2.25756324341725e-36	4.5151264868345e-36	1
47	1.02845310146813e-37	2.05690620293627e-37	1
48	1.44739014845124e-11	2.89478029690248e-11	0.999999999985526
49	5.18688777677078e-12	1.03737755535416e-11	0.999999999994813
50	1.99926812434125e-12	3.9985362486825e-12	0.999999999998001
51	6.98395887967044e-13	1.39679177593409e-12	0.999999999999302
52	2.2958210839597e-13	4.59164216791941e-13	0.99999999999977
53	8.35855442808583e-14	1.67171088561717e-13	0.999999999999916
54	1.21342561138843e-13	2.42685122277686e-13	0.999999999999879
55	4.24276018302817e-14	8.48552036605633e-14	0.999999999999958
56	1.30172689340735e-14	2.6034537868147e-14	0.999999999999987
57	4.38086846731482e-15	8.76173693462964e-15	0.999999999999996
58	1.31146690878633e-15	2.62293381757267e-15	0.999999999999999
59	4.05331160845596e-16	8.10662321691192e-16	1
60	1.16233491732254e-16	2.32466983464508e-16	1
61	3.76193430149025e-17	7.5238686029805e-17	1
62	1.62093831707261e-17	3.24187663414522e-17	1
63	5.61668139042605e-18	1.12333627808521e-17	1
64	1.53953062651192e-18	3.07906125302384e-18	1
65	4.26121973401096e-19	8.52243946802192e-19	1
66	1.33029800610328e-19	2.66059601220657e-19	1
67	4.73643997363881e-20	9.47287994727762e-20	1
68	1.31532632158714e-20	2.63065264317429e-20	1
69	3.97415018378257e-21	7.94830036756515e-21	1
70	1.05282671919267e-21	2.10565343838535e-21	1
71	4.45503094031622e-22	8.91006188063244e-22	1
72	1.29979290611789e-22	2.59958581223578e-22	1
73	3.94393602579606e-23	7.88787205159211e-23	1
74	1.08443046529128e-23	2.16886093058256e-23	1
75	4.16710867027872e-24	8.33421734055745e-24	1
76	2.44221758086819e-21	4.88443516173639e-21	1
77	6.93782333448249e-22	1.3875646668965e-21	1
78	1.98394623496402e-22	3.96789246992803e-22	1
79	6.11850564689915e-23	1.22370112937983e-22	1
80	2.15148496617773e-23	4.30296993235546e-23	1
81	1.60530727631681e-23	3.21061455263362e-23	1
82	9.94786935371148e-24	1.9895738707423e-23	1
83	3.82199362203697e-24	7.64398724407394e-24	1
84	1.51987199307491e-24	3.03974398614983e-24	1
85	4.29052597315241e-25	8.58105194630481e-25	1
86	2.63160295689058e-25	5.26320591378116e-25	1
87	8.23975026899792e-26	1.64795005379958e-25	1
88	2.85145703923253e-26	5.70291407846506e-26	1
89	9.46099190632506e-27	1.89219838126501e-26	1
90	2.48008923736238e-27	4.96017847472477e-27	1
91	6.48813013335737e-28	1.29762602667147e-27	1
92	1.67976155329365e-28	3.35952310658731e-28	1
93	4.86437685525031e-29	9.72875371050061e-29	1
94	1.59536159391967e-29	3.19072318783934e-29	1
95	6.66940428718951e-30	1.3338808574379e-29	1
96	7.6571285284373e-13	1.53142570568746e-12	0.999999999999234
97	9.76178902096493e-13	1.95235780419299e-12	0.999999999999024
98	6.49312539768782e-13	1.29862507953756e-12	0.999999999999351
99	2.99796386455016e-13	5.99592772910032e-13	0.9999999999997
100	1.39858430751045e-13	2.79716861502091e-13	0.99999999999986
101	6.78050396859239e-14	1.35610079371848e-13	0.999999999999932
102	3.08752902131752e-14	6.17505804263504e-14	0.999999999999969
103	1.50093100905883e-14	3.00186201811767e-14	0.999999999999985
104	9.74619549298292e-15	1.94923909859658e-14	0.99999999999999
105	4.85441617817279e-15	9.70883235634558e-15	0.999999999999995
106	2.12708669844312e-15	4.25417339688624e-15	0.999999999999998
107	1.73290670874748e-15	3.46581341749496e-15	0.999999999999998
108	1.1921071278637e-15	2.3842142557274e-15	0.999999999999999
109	6.64986689016781e-16	1.32997337803356e-15	0.999999999999999
110	2.98091484595664e-16	5.96182969191328e-16	1
111	1.2781181983873e-16	2.55623639677459e-16	1
112	5.71391245835229e-17	1.14278249167046e-16	1
113	2.64364523911667e-17	5.28729047823334e-17	1
114	1.15168822139017e-17	2.30337644278033e-17	1
115	8.77195474308629e-18	1.75439094861726e-17	1
116	3.61077930300136e-18	7.22155860600272e-18	1
117	1.60838054871396e-18	3.21676109742793e-18	1
118	6.68826047639436e-19	1.33765209527887e-18	1
119	7.52520087289492e-19	1.50504017457898e-18	1
120	4.14093349825008e-19	8.28186699650017e-19	1
121	4.4401078073268e-19	8.88021561465359e-19	1
122	2.13146824244111e-19	4.26293648488221e-19	1
123	8.45003056176865e-20	1.69000611235373e-19	1
124	3.31240321957062e-20	6.62480643914124e-20	1
125	1.2896307871485e-20	2.57926157429699e-20	1
126	6.13412814924853e-21	1.22682562984971e-20	1
127	6.11477913739636e-21	1.22295582747927e-20	1
128	6.72801228519865e-21	1.34560245703973e-20	1
129	2.63270291130334e-21	5.26540582260669e-21	1
130	1.00481205791479e-21	2.00962411582959e-21	1
131	4.06304217569985e-22	8.12608435139969e-22	1
132	2.04213091230376e-22	4.08426182460752e-22	1
133	8.10875163909767e-23	1.62175032781953e-22	1
134	6.65973932583131e-23	1.33194786516626e-22	1
135	1.67897192319721e-22	3.35794384639442e-22	1
136	6.54235730952432e-23	1.30847146190486e-22	1
137	6.65700343358902e-23	1.3314006867178e-22	1
138	5.11082901492219e-23	1.02216580298444e-22	1
139	3.2535778620403e-23	6.50715572408059e-23	1
140	7.2532408614429e-23	1.45064817228858e-22	1
141	3.65474090820608e-23	7.30948181641216e-23	1
142	1.62740760082149e-23	3.25481520164298e-23	1
143	1.52345571830783e-23	3.04691143661567e-23	1
144	8.03140500494425e-24	1.60628100098885e-23	1
145	2.98220826916025e-24	5.96441653832051e-24	1
146	1.35701337838469e-24	2.71402675676937e-24	1
147	7.61112671305493e-25	1.52222534261099e-24	1
148	1.42453018077481e-24	2.84906036154962e-24	1
149	5.21816071352311e-25	1.04363214270462e-24	1
150	1.97874271087842e-25	3.95748542175684e-25	1
151	7.16787173565031e-26	1.43357434713006e-25	1
152	4.23785577580256e-26	8.47571155160511e-26	1
153	8.3269891891721e-26	1.66539783783442e-25	1
154	3.24748844377395e-26	6.4949768875479e-26	1
155	1.22327972285506e-26	2.44655944571012e-26	1
156	8.49476442644546e-27	1.69895288528909e-26	1
157	6.56497610229756e-27	1.31299522045951e-26	1
158	4.1225374982279e-27	8.24507499645579e-27	1
159	2.92540325885161e-27	5.85080651770322e-27	1
160	3.64250610258087e-27	7.28501220516175e-27	1
161	1.37565338179151e-27	2.75130676358302e-27	1
162	6.36295561221492e-28	1.27259112244298e-27	1
163	2.51463619074245e-28	5.0292723814849e-28	1
164	8.98201729774404e-29	1.79640345954881e-28	1
165	3.0814183736838e-29	6.16283674736759e-29	1
166	1.44176774910502e-29	2.88353549821005e-29	1
167	2.81945446616384e-29	5.63890893232767e-29	1
168	9.90925082280436e-30	1.98185016456087e-29	1
169	4.79050549892752e-30	9.58101099785503e-30	1
170	1.6778714869524e-30	3.35574297390479e-30	1
171	3.5901891216126e-30	7.18037824322519e-30	1
172	2.27534354529478e-30	4.55068709058956e-30	1
173	1.9102347540604e-30	3.8204695081208e-30	1
174	6.11696738579295e-31	1.22339347715859e-30	1
175	2.42072057764346e-31	4.84144115528692e-31	1
176	9.06648796713906e-32	1.81329759342781e-31	1
177	3.88197464518193e-32	7.76394929036387e-32	1
178	1.49106282553954e-32	2.98212565107908e-32	1
179	1.14032353107631e-32	2.28064706215262e-32	1
180	5.24667591042058e-32	1.04933518208412e-31	1
181	1.7105981191061e-32	3.4211962382122e-32	1
182	1.56928290163152e-31	3.13856580326304e-31	1
183	6.35730739132531e-32	1.27146147826506e-31	1
184	9.61078816949466e-32	1.92215763389893e-31	1
185	2.99398771487355e-32	5.9879754297471e-32	1
186	8.76225475703964e-32	1.75245095140793e-31	1
187	5.63591619315826e-32	1.12718323863165e-31	1
188	2.75762536835221e-32	5.51525073670441e-32	1
189	9.56538257103507e-33	1.91307651420701e-32	1
190	9.06348554658617e-33	1.81269710931723e-32	1
191	2.67867021545687e-33	5.35734043091374e-33	1
192	2.47705278399485e-33	4.95410556798969e-33	1
193	7.67747341443405e-34	1.53549468288681e-33	1
194	3.06756988687329e-34	6.13513977374658e-34	1
195	4.4092192866583e-34	8.8184385733166e-34	1
196	2.55895894053292e-34	5.11791788106584e-34	1
197	9.37584353577028e-33	1.87516870715406e-32	1
198	3.70714502857103e-33	7.41429005714206e-33	1
199	1.49782419466732e-33	2.99564838933464e-33	1
200	1.70227905902343e-30	3.40455811804685e-30	1
201	5.73162836187843e-31	1.14632567237569e-30	1
202	9.37168186574223e-30	1.87433637314845e-29	1
203	2.92032611276397e-28	5.84065222552795e-28	1
204	1.42823105869137e-26	2.85646211738273e-26	1
205	7.145001859475e-27	1.429000371895e-26	1
206	3.68413035360861e-26	7.36826070721721e-26	1
207	1.64088583052877e-17	3.28177166105755e-17	1
208	7.2459788331065e-16	1.4491957666213e-15	0.999999999999999
209	2.94793713012057e-16	5.89587426024114e-16	1
210	1.25547482291419e-16	2.51094964582837e-16	1
211	4.86161611603356e-17	9.72323223206711e-17	1
212	3.16261553475845e-17	6.3252310695169e-17	1
213	2.87732679077577e-16	5.75465358155154e-16	1
214	1.09334005595711e-16	2.18668011191422e-16	1
215	1.23365933601072e-15	2.46731867202144e-15	0.999999999999999
216	1	1.88619482554936e-29	9.43097412774682e-30
217	1	6.14479450106136e-28	3.07239725053068e-28
218	1	1.05700206822358e-26	5.2850103411179e-27
219	1	3.79687033004673e-25	1.89843516502337e-25
220	1	1.28502187668747e-23	6.42510938343734e-24
221	1	3.20852963292641e-22	1.60426481646321e-22
222	1	8.90378275503835e-21	4.45189137751917e-21
223	1	1.9278591699128e-19	9.639295849564e-20
224	1	1.58349433024276e-19	7.9174716512138e-20
225	1	1.66245820638847e-18	8.31229103194235e-19
226	1	2.06125417771916e-17	1.03062708885958e-17
227	1	9.47517956072592e-16	4.73758978036296e-16
228	0.999999999999978	4.45501937856737e-14	2.22750968928368e-14
229	0.999999999999259	1.48256133519639e-12	7.41280667598194e-13
230	0.999999999975173	4.96539519534087e-11	2.48269759767043e-11
231	0.999999999033206	1.93358799812747e-09	9.66793999063734e-10
232	0.999999960389398	7.92212042883087e-08	3.96106021441543e-08
233	0.999998551752097	2.89649580658653e-06	1.44824790329327e-06
234	0.99998376368619	3.24726276203125e-05	1.62363138101563e-05

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
18 & 0.000127427931555219 & 0.000254855863110437 & 0.999872572068445 \tabularnewline
19 & 6.23033066595257e-06 & 1.24606613319051e-05 & 0.999993769669334 \tabularnewline
20 & 3.6191491818827e-07 & 7.23829836376539e-07 & 0.999999638085082 \tabularnewline
21 & 2.64584378661583e-08 & 5.29168757323166e-08 & 0.999999973541562 \tabularnewline
22 & 1.04108762120523e-09 & 2.08217524241046e-09 & 0.999999998958912 \tabularnewline
23 & 2.55410729395196e-10 & 5.10821458790392e-10 & 0.999999999744589 \tabularnewline
24 & 1.34262454432828e-11 & 2.68524908865656e-11 & 0.999999999986574 \tabularnewline
25 & 6.16542019451254e-13 & 1.23308403890251e-12 & 0.999999999999383 \tabularnewline
26 & 3.6189416315068e-14 & 7.2378832630136e-14 & 0.999999999999964 \tabularnewline
27 & 1.90062479680284e-15 & 3.80124959360568e-15 & 0.999999999999998 \tabularnewline
28 & 1.6608574150786e-16 & 3.3217148301572e-16 & 1 \tabularnewline
29 & 7.02343286150802e-18 & 1.4046865723016e-17 & 1 \tabularnewline
30 & 3.58705225679735e-19 & 7.17410451359469e-19 & 1 \tabularnewline
31 & 1.5349144820379e-20 & 3.0698289640758e-20 & 1 \tabularnewline
32 & 7.47823395113745e-22 & 1.49564679022749e-21 & 1 \tabularnewline
33 & 2.9940018148274e-23 & 5.98800362965481e-23 & 1 \tabularnewline
34 & 1.12594507116991e-24 & 2.25189014233983e-24 & 1 \tabularnewline
35 & 1.53813341997565e-24 & 3.07626683995131e-24 & 1 \tabularnewline
36 & 4.71465498344275e-24 & 9.42930996688549e-24 & 1 \tabularnewline
37 & 3.02398823079062e-25 & 6.04797646158124e-25 & 1 \tabularnewline
38 & 2.23714087769587e-26 & 4.47428175539173e-26 & 1 \tabularnewline
39 & 1.51219006209464e-27 & 3.02438012418929e-27 & 1 \tabularnewline
40 & 7.29428292565371e-29 & 1.45885658513074e-28 & 1 \tabularnewline
41 & 4.09844116113918e-30 & 8.19688232227835e-30 & 1 \tabularnewline
42 & 2.03178603822745e-31 & 4.0635720764549e-31 & 1 \tabularnewline
43 & 9.4942448633285e-33 & 1.8988489726657e-32 & 1 \tabularnewline
44 & 6.12928135361992e-34 & 1.22585627072398e-33 & 1 \tabularnewline
45 & 4.81878689883128e-35 & 9.63757379766255e-35 & 1 \tabularnewline
46 & 2.25756324341725e-36 & 4.5151264868345e-36 & 1 \tabularnewline
47 & 1.02845310146813e-37 & 2.05690620293627e-37 & 1 \tabularnewline
48 & 1.44739014845124e-11 & 2.89478029690248e-11 & 0.999999999985526 \tabularnewline
49 & 5.18688777677078e-12 & 1.03737755535416e-11 & 0.999999999994813 \tabularnewline
50 & 1.99926812434125e-12 & 3.9985362486825e-12 & 0.999999999998001 \tabularnewline
51 & 6.98395887967044e-13 & 1.39679177593409e-12 & 0.999999999999302 \tabularnewline
52 & 2.2958210839597e-13 & 4.59164216791941e-13 & 0.99999999999977 \tabularnewline
53 & 8.35855442808583e-14 & 1.67171088561717e-13 & 0.999999999999916 \tabularnewline
54 & 1.21342561138843e-13 & 2.42685122277686e-13 & 0.999999999999879 \tabularnewline
55 & 4.24276018302817e-14 & 8.48552036605633e-14 & 0.999999999999958 \tabularnewline
56 & 1.30172689340735e-14 & 2.6034537868147e-14 & 0.999999999999987 \tabularnewline
57 & 4.38086846731482e-15 & 8.76173693462964e-15 & 0.999999999999996 \tabularnewline
58 & 1.31146690878633e-15 & 2.62293381757267e-15 & 0.999999999999999 \tabularnewline
59 & 4.05331160845596e-16 & 8.10662321691192e-16 & 1 \tabularnewline
60 & 1.16233491732254e-16 & 2.32466983464508e-16 & 1 \tabularnewline
61 & 3.76193430149025e-17 & 7.5238686029805e-17 & 1 \tabularnewline
62 & 1.62093831707261e-17 & 3.24187663414522e-17 & 1 \tabularnewline
63 & 5.61668139042605e-18 & 1.12333627808521e-17 & 1 \tabularnewline
64 & 1.53953062651192e-18 & 3.07906125302384e-18 & 1 \tabularnewline
65 & 4.26121973401096e-19 & 8.52243946802192e-19 & 1 \tabularnewline
66 & 1.33029800610328e-19 & 2.66059601220657e-19 & 1 \tabularnewline
67 & 4.73643997363881e-20 & 9.47287994727762e-20 & 1 \tabularnewline
68 & 1.31532632158714e-20 & 2.63065264317429e-20 & 1 \tabularnewline
69 & 3.97415018378257e-21 & 7.94830036756515e-21 & 1 \tabularnewline
70 & 1.05282671919267e-21 & 2.10565343838535e-21 & 1 \tabularnewline
71 & 4.45503094031622e-22 & 8.91006188063244e-22 & 1 \tabularnewline
72 & 1.29979290611789e-22 & 2.59958581223578e-22 & 1 \tabularnewline
73 & 3.94393602579606e-23 & 7.88787205159211e-23 & 1 \tabularnewline
74 & 1.08443046529128e-23 & 2.16886093058256e-23 & 1 \tabularnewline
75 & 4.16710867027872e-24 & 8.33421734055745e-24 & 1 \tabularnewline
76 & 2.44221758086819e-21 & 4.88443516173639e-21 & 1 \tabularnewline
77 & 6.93782333448249e-22 & 1.3875646668965e-21 & 1 \tabularnewline
78 & 1.98394623496402e-22 & 3.96789246992803e-22 & 1 \tabularnewline
79 & 6.11850564689915e-23 & 1.22370112937983e-22 & 1 \tabularnewline
80 & 2.15148496617773e-23 & 4.30296993235546e-23 & 1 \tabularnewline
81 & 1.60530727631681e-23 & 3.21061455263362e-23 & 1 \tabularnewline
82 & 9.94786935371148e-24 & 1.9895738707423e-23 & 1 \tabularnewline
83 & 3.82199362203697e-24 & 7.64398724407394e-24 & 1 \tabularnewline
84 & 1.51987199307491e-24 & 3.03974398614983e-24 & 1 \tabularnewline
85 & 4.29052597315241e-25 & 8.58105194630481e-25 & 1 \tabularnewline
86 & 2.63160295689058e-25 & 5.26320591378116e-25 & 1 \tabularnewline
87 & 8.23975026899792e-26 & 1.64795005379958e-25 & 1 \tabularnewline
88 & 2.85145703923253e-26 & 5.70291407846506e-26 & 1 \tabularnewline
89 & 9.46099190632506e-27 & 1.89219838126501e-26 & 1 \tabularnewline
90 & 2.48008923736238e-27 & 4.96017847472477e-27 & 1 \tabularnewline
91 & 6.48813013335737e-28 & 1.29762602667147e-27 & 1 \tabularnewline
92 & 1.67976155329365e-28 & 3.35952310658731e-28 & 1 \tabularnewline
93 & 4.86437685525031e-29 & 9.72875371050061e-29 & 1 \tabularnewline
94 & 1.59536159391967e-29 & 3.19072318783934e-29 & 1 \tabularnewline
95 & 6.66940428718951e-30 & 1.3338808574379e-29 & 1 \tabularnewline
96 & 7.6571285284373e-13 & 1.53142570568746e-12 & 0.999999999999234 \tabularnewline
97 & 9.76178902096493e-13 & 1.95235780419299e-12 & 0.999999999999024 \tabularnewline
98 & 6.49312539768782e-13 & 1.29862507953756e-12 & 0.999999999999351 \tabularnewline
99 & 2.99796386455016e-13 & 5.99592772910032e-13 & 0.9999999999997 \tabularnewline
100 & 1.39858430751045e-13 & 2.79716861502091e-13 & 0.99999999999986 \tabularnewline
101 & 6.78050396859239e-14 & 1.35610079371848e-13 & 0.999999999999932 \tabularnewline
102 & 3.08752902131752e-14 & 6.17505804263504e-14 & 0.999999999999969 \tabularnewline
103 & 1.50093100905883e-14 & 3.00186201811767e-14 & 0.999999999999985 \tabularnewline
104 & 9.74619549298292e-15 & 1.94923909859658e-14 & 0.99999999999999 \tabularnewline
105 & 4.85441617817279e-15 & 9.70883235634558e-15 & 0.999999999999995 \tabularnewline
106 & 2.12708669844312e-15 & 4.25417339688624e-15 & 0.999999999999998 \tabularnewline
107 & 1.73290670874748e-15 & 3.46581341749496e-15 & 0.999999999999998 \tabularnewline
108 & 1.1921071278637e-15 & 2.3842142557274e-15 & 0.999999999999999 \tabularnewline
109 & 6.64986689016781e-16 & 1.32997337803356e-15 & 0.999999999999999 \tabularnewline
110 & 2.98091484595664e-16 & 5.96182969191328e-16 & 1 \tabularnewline
111 & 1.2781181983873e-16 & 2.55623639677459e-16 & 1 \tabularnewline
112 & 5.71391245835229e-17 & 1.14278249167046e-16 & 1 \tabularnewline
113 & 2.64364523911667e-17 & 5.28729047823334e-17 & 1 \tabularnewline
114 & 1.15168822139017e-17 & 2.30337644278033e-17 & 1 \tabularnewline
115 & 8.77195474308629e-18 & 1.75439094861726e-17 & 1 \tabularnewline
116 & 3.61077930300136e-18 & 7.22155860600272e-18 & 1 \tabularnewline
117 & 1.60838054871396e-18 & 3.21676109742793e-18 & 1 \tabularnewline
118 & 6.68826047639436e-19 & 1.33765209527887e-18 & 1 \tabularnewline
119 & 7.52520087289492e-19 & 1.50504017457898e-18 & 1 \tabularnewline
120 & 4.14093349825008e-19 & 8.28186699650017e-19 & 1 \tabularnewline
121 & 4.4401078073268e-19 & 8.88021561465359e-19 & 1 \tabularnewline
122 & 2.13146824244111e-19 & 4.26293648488221e-19 & 1 \tabularnewline
123 & 8.45003056176865e-20 & 1.69000611235373e-19 & 1 \tabularnewline
124 & 3.31240321957062e-20 & 6.62480643914124e-20 & 1 \tabularnewline
125 & 1.2896307871485e-20 & 2.57926157429699e-20 & 1 \tabularnewline
126 & 6.13412814924853e-21 & 1.22682562984971e-20 & 1 \tabularnewline
127 & 6.11477913739636e-21 & 1.22295582747927e-20 & 1 \tabularnewline
128 & 6.72801228519865e-21 & 1.34560245703973e-20 & 1 \tabularnewline
129 & 2.63270291130334e-21 & 5.26540582260669e-21 & 1 \tabularnewline
130 & 1.00481205791479e-21 & 2.00962411582959e-21 & 1 \tabularnewline
131 & 4.06304217569985e-22 & 8.12608435139969e-22 & 1 \tabularnewline
132 & 2.04213091230376e-22 & 4.08426182460752e-22 & 1 \tabularnewline
133 & 8.10875163909767e-23 & 1.62175032781953e-22 & 1 \tabularnewline
134 & 6.65973932583131e-23 & 1.33194786516626e-22 & 1 \tabularnewline
135 & 1.67897192319721e-22 & 3.35794384639442e-22 & 1 \tabularnewline
136 & 6.54235730952432e-23 & 1.30847146190486e-22 & 1 \tabularnewline
137 & 6.65700343358902e-23 & 1.3314006867178e-22 & 1 \tabularnewline
138 & 5.11082901492219e-23 & 1.02216580298444e-22 & 1 \tabularnewline
139 & 3.2535778620403e-23 & 6.50715572408059e-23 & 1 \tabularnewline
140 & 7.2532408614429e-23 & 1.45064817228858e-22 & 1 \tabularnewline
141 & 3.65474090820608e-23 & 7.30948181641216e-23 & 1 \tabularnewline
142 & 1.62740760082149e-23 & 3.25481520164298e-23 & 1 \tabularnewline
143 & 1.52345571830783e-23 & 3.04691143661567e-23 & 1 \tabularnewline
144 & 8.03140500494425e-24 & 1.60628100098885e-23 & 1 \tabularnewline
145 & 2.98220826916025e-24 & 5.96441653832051e-24 & 1 \tabularnewline
146 & 1.35701337838469e-24 & 2.71402675676937e-24 & 1 \tabularnewline
147 & 7.61112671305493e-25 & 1.52222534261099e-24 & 1 \tabularnewline
148 & 1.42453018077481e-24 & 2.84906036154962e-24 & 1 \tabularnewline
149 & 5.21816071352311e-25 & 1.04363214270462e-24 & 1 \tabularnewline
150 & 1.97874271087842e-25 & 3.95748542175684e-25 & 1 \tabularnewline
151 & 7.16787173565031e-26 & 1.43357434713006e-25 & 1 \tabularnewline
152 & 4.23785577580256e-26 & 8.47571155160511e-26 & 1 \tabularnewline
153 & 8.3269891891721e-26 & 1.66539783783442e-25 & 1 \tabularnewline
154 & 3.24748844377395e-26 & 6.4949768875479e-26 & 1 \tabularnewline
155 & 1.22327972285506e-26 & 2.44655944571012e-26 & 1 \tabularnewline
156 & 8.49476442644546e-27 & 1.69895288528909e-26 & 1 \tabularnewline
157 & 6.56497610229756e-27 & 1.31299522045951e-26 & 1 \tabularnewline
158 & 4.1225374982279e-27 & 8.24507499645579e-27 & 1 \tabularnewline
159 & 2.92540325885161e-27 & 5.85080651770322e-27 & 1 \tabularnewline
160 & 3.64250610258087e-27 & 7.28501220516175e-27 & 1 \tabularnewline
161 & 1.37565338179151e-27 & 2.75130676358302e-27 & 1 \tabularnewline
162 & 6.36295561221492e-28 & 1.27259112244298e-27 & 1 \tabularnewline
163 & 2.51463619074245e-28 & 5.0292723814849e-28 & 1 \tabularnewline
164 & 8.98201729774404e-29 & 1.79640345954881e-28 & 1 \tabularnewline
165 & 3.0814183736838e-29 & 6.16283674736759e-29 & 1 \tabularnewline
166 & 1.44176774910502e-29 & 2.88353549821005e-29 & 1 \tabularnewline
167 & 2.81945446616384e-29 & 5.63890893232767e-29 & 1 \tabularnewline
168 & 9.90925082280436e-30 & 1.98185016456087e-29 & 1 \tabularnewline
169 & 4.79050549892752e-30 & 9.58101099785503e-30 & 1 \tabularnewline
170 & 1.6778714869524e-30 & 3.35574297390479e-30 & 1 \tabularnewline
171 & 3.5901891216126e-30 & 7.18037824322519e-30 & 1 \tabularnewline
172 & 2.27534354529478e-30 & 4.55068709058956e-30 & 1 \tabularnewline
173 & 1.9102347540604e-30 & 3.8204695081208e-30 & 1 \tabularnewline
174 & 6.11696738579295e-31 & 1.22339347715859e-30 & 1 \tabularnewline
175 & 2.42072057764346e-31 & 4.84144115528692e-31 & 1 \tabularnewline
176 & 9.06648796713906e-32 & 1.81329759342781e-31 & 1 \tabularnewline
177 & 3.88197464518193e-32 & 7.76394929036387e-32 & 1 \tabularnewline
178 & 1.49106282553954e-32 & 2.98212565107908e-32 & 1 \tabularnewline
179 & 1.14032353107631e-32 & 2.28064706215262e-32 & 1 \tabularnewline
180 & 5.24667591042058e-32 & 1.04933518208412e-31 & 1 \tabularnewline
181 & 1.7105981191061e-32 & 3.4211962382122e-32 & 1 \tabularnewline
182 & 1.56928290163152e-31 & 3.13856580326304e-31 & 1 \tabularnewline
183 & 6.35730739132531e-32 & 1.27146147826506e-31 & 1 \tabularnewline
184 & 9.61078816949466e-32 & 1.92215763389893e-31 & 1 \tabularnewline
185 & 2.99398771487355e-32 & 5.9879754297471e-32 & 1 \tabularnewline
186 & 8.76225475703964e-32 & 1.75245095140793e-31 & 1 \tabularnewline
187 & 5.63591619315826e-32 & 1.12718323863165e-31 & 1 \tabularnewline
188 & 2.75762536835221e-32 & 5.51525073670441e-32 & 1 \tabularnewline
189 & 9.56538257103507e-33 & 1.91307651420701e-32 & 1 \tabularnewline
190 & 9.06348554658617e-33 & 1.81269710931723e-32 & 1 \tabularnewline
191 & 2.67867021545687e-33 & 5.35734043091374e-33 & 1 \tabularnewline
192 & 2.47705278399485e-33 & 4.95410556798969e-33 & 1 \tabularnewline
193 & 7.67747341443405e-34 & 1.53549468288681e-33 & 1 \tabularnewline
194 & 3.06756988687329e-34 & 6.13513977374658e-34 & 1 \tabularnewline
195 & 4.4092192866583e-34 & 8.8184385733166e-34 & 1 \tabularnewline
196 & 2.55895894053292e-34 & 5.11791788106584e-34 & 1 \tabularnewline
197 & 9.37584353577028e-33 & 1.87516870715406e-32 & 1 \tabularnewline
198 & 3.70714502857103e-33 & 7.41429005714206e-33 & 1 \tabularnewline
199 & 1.49782419466732e-33 & 2.99564838933464e-33 & 1 \tabularnewline
200 & 1.70227905902343e-30 & 3.40455811804685e-30 & 1 \tabularnewline
201 & 5.73162836187843e-31 & 1.14632567237569e-30 & 1 \tabularnewline
202 & 9.37168186574223e-30 & 1.87433637314845e-29 & 1 \tabularnewline
203 & 2.92032611276397e-28 & 5.84065222552795e-28 & 1 \tabularnewline
204 & 1.42823105869137e-26 & 2.85646211738273e-26 & 1 \tabularnewline
205 & 7.145001859475e-27 & 1.429000371895e-26 & 1 \tabularnewline
206 & 3.68413035360861e-26 & 7.36826070721721e-26 & 1 \tabularnewline
207 & 1.64088583052877e-17 & 3.28177166105755e-17 & 1 \tabularnewline
208 & 7.2459788331065e-16 & 1.4491957666213e-15 & 0.999999999999999 \tabularnewline
209 & 2.94793713012057e-16 & 5.89587426024114e-16 & 1 \tabularnewline
210 & 1.25547482291419e-16 & 2.51094964582837e-16 & 1 \tabularnewline
211 & 4.86161611603356e-17 & 9.72323223206711e-17 & 1 \tabularnewline
212 & 3.16261553475845e-17 & 6.3252310695169e-17 & 1 \tabularnewline
213 & 2.87732679077577e-16 & 5.75465358155154e-16 & 1 \tabularnewline
214 & 1.09334005595711e-16 & 2.18668011191422e-16 & 1 \tabularnewline
215 & 1.23365933601072e-15 & 2.46731867202144e-15 & 0.999999999999999 \tabularnewline
216 & 1 & 1.88619482554936e-29 & 9.43097412774682e-30 \tabularnewline
217 & 1 & 6.14479450106136e-28 & 3.07239725053068e-28 \tabularnewline
218 & 1 & 1.05700206822358e-26 & 5.2850103411179e-27 \tabularnewline
219 & 1 & 3.79687033004673e-25 & 1.89843516502337e-25 \tabularnewline
220 & 1 & 1.28502187668747e-23 & 6.42510938343734e-24 \tabularnewline
221 & 1 & 3.20852963292641e-22 & 1.60426481646321e-22 \tabularnewline
222 & 1 & 8.90378275503835e-21 & 4.45189137751917e-21 \tabularnewline
223 & 1 & 1.9278591699128e-19 & 9.639295849564e-20 \tabularnewline
224 & 1 & 1.58349433024276e-19 & 7.9174716512138e-20 \tabularnewline
225 & 1 & 1.66245820638847e-18 & 8.31229103194235e-19 \tabularnewline
226 & 1 & 2.06125417771916e-17 & 1.03062708885958e-17 \tabularnewline
227 & 1 & 9.47517956072592e-16 & 4.73758978036296e-16 \tabularnewline
228 & 0.999999999999978 & 4.45501937856737e-14 & 2.22750968928368e-14 \tabularnewline
229 & 0.999999999999259 & 1.48256133519639e-12 & 7.41280667598194e-13 \tabularnewline
230 & 0.999999999975173 & 4.96539519534087e-11 & 2.48269759767043e-11 \tabularnewline
231 & 0.999999999033206 & 1.93358799812747e-09 & 9.66793999063734e-10 \tabularnewline
232 & 0.999999960389398 & 7.92212042883087e-08 & 3.96106021441543e-08 \tabularnewline
233 & 0.999998551752097 & 2.89649580658653e-06 & 1.44824790329327e-06 \tabularnewline
234 & 0.99998376368619 & 3.24726276203125e-05 & 1.62363138101563e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190063&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]18[/C][C]0.000127427931555219[/C][C]0.000254855863110437[/C][C]0.999872572068445[/C][/ROW]
[ROW][C]19[/C][C]6.23033066595257e-06[/C][C]1.24606613319051e-05[/C][C]0.999993769669334[/C][/ROW]
[ROW][C]20[/C][C]3.6191491818827e-07[/C][C]7.23829836376539e-07[/C][C]0.999999638085082[/C][/ROW]
[ROW][C]21[/C][C]2.64584378661583e-08[/C][C]5.29168757323166e-08[/C][C]0.999999973541562[/C][/ROW]
[ROW][C]22[/C][C]1.04108762120523e-09[/C][C]2.08217524241046e-09[/C][C]0.999999998958912[/C][/ROW]
[ROW][C]23[/C][C]2.55410729395196e-10[/C][C]5.10821458790392e-10[/C][C]0.999999999744589[/C][/ROW]
[ROW][C]24[/C][C]1.34262454432828e-11[/C][C]2.68524908865656e-11[/C][C]0.999999999986574[/C][/ROW]
[ROW][C]25[/C][C]6.16542019451254e-13[/C][C]1.23308403890251e-12[/C][C]0.999999999999383[/C][/ROW]
[ROW][C]26[/C][C]3.6189416315068e-14[/C][C]7.2378832630136e-14[/C][C]0.999999999999964[/C][/ROW]
[ROW][C]27[/C][C]1.90062479680284e-15[/C][C]3.80124959360568e-15[/C][C]0.999999999999998[/C][/ROW]
[ROW][C]28[/C][C]1.6608574150786e-16[/C][C]3.3217148301572e-16[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]7.02343286150802e-18[/C][C]1.4046865723016e-17[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]3.58705225679735e-19[/C][C]7.17410451359469e-19[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]1.5349144820379e-20[/C][C]3.0698289640758e-20[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]7.47823395113745e-22[/C][C]1.49564679022749e-21[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]2.9940018148274e-23[/C][C]5.98800362965481e-23[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]1.12594507116991e-24[/C][C]2.25189014233983e-24[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]1.53813341997565e-24[/C][C]3.07626683995131e-24[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]4.71465498344275e-24[/C][C]9.42930996688549e-24[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]3.02398823079062e-25[/C][C]6.04797646158124e-25[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]2.23714087769587e-26[/C][C]4.47428175539173e-26[/C][C]1[/C][/ROW]
[ROW][C]39[/C][C]1.51219006209464e-27[/C][C]3.02438012418929e-27[/C][C]1[/C][/ROW]
[ROW][C]40[/C][C]7.29428292565371e-29[/C][C]1.45885658513074e-28[/C][C]1[/C][/ROW]
[ROW][C]41[/C][C]4.09844116113918e-30[/C][C]8.19688232227835e-30[/C][C]1[/C][/ROW]
[ROW][C]42[/C][C]2.03178603822745e-31[/C][C]4.0635720764549e-31[/C][C]1[/C][/ROW]
[ROW][C]43[/C][C]9.4942448633285e-33[/C][C]1.8988489726657e-32[/C][C]1[/C][/ROW]
[ROW][C]44[/C][C]6.12928135361992e-34[/C][C]1.22585627072398e-33[/C][C]1[/C][/ROW]
[ROW][C]45[/C][C]4.81878689883128e-35[/C][C]9.63757379766255e-35[/C][C]1[/C][/ROW]
[ROW][C]46[/C][C]2.25756324341725e-36[/C][C]4.5151264868345e-36[/C][C]1[/C][/ROW]
[ROW][C]47[/C][C]1.02845310146813e-37[/C][C]2.05690620293627e-37[/C][C]1[/C][/ROW]
[ROW][C]48[/C][C]1.44739014845124e-11[/C][C]2.89478029690248e-11[/C][C]0.999999999985526[/C][/ROW]
[ROW][C]49[/C][C]5.18688777677078e-12[/C][C]1.03737755535416e-11[/C][C]0.999999999994813[/C][/ROW]
[ROW][C]50[/C][C]1.99926812434125e-12[/C][C]3.9985362486825e-12[/C][C]0.999999999998001[/C][/ROW]
[ROW][C]51[/C][C]6.98395887967044e-13[/C][C]1.39679177593409e-12[/C][C]0.999999999999302[/C][/ROW]
[ROW][C]52[/C][C]2.2958210839597e-13[/C][C]4.59164216791941e-13[/C][C]0.99999999999977[/C][/ROW]
[ROW][C]53[/C][C]8.35855442808583e-14[/C][C]1.67171088561717e-13[/C][C]0.999999999999916[/C][/ROW]
[ROW][C]54[/C][C]1.21342561138843e-13[/C][C]2.42685122277686e-13[/C][C]0.999999999999879[/C][/ROW]
[ROW][C]55[/C][C]4.24276018302817e-14[/C][C]8.48552036605633e-14[/C][C]0.999999999999958[/C][/ROW]
[ROW][C]56[/C][C]1.30172689340735e-14[/C][C]2.6034537868147e-14[/C][C]0.999999999999987[/C][/ROW]
[ROW][C]57[/C][C]4.38086846731482e-15[/C][C]8.76173693462964e-15[/C][C]0.999999999999996[/C][/ROW]
[ROW][C]58[/C][C]1.31146690878633e-15[/C][C]2.62293381757267e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]59[/C][C]4.05331160845596e-16[/C][C]8.10662321691192e-16[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]1.16233491732254e-16[/C][C]2.32466983464508e-16[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]3.76193430149025e-17[/C][C]7.5238686029805e-17[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]1.62093831707261e-17[/C][C]3.24187663414522e-17[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]5.61668139042605e-18[/C][C]1.12333627808521e-17[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]1.53953062651192e-18[/C][C]3.07906125302384e-18[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]4.26121973401096e-19[/C][C]8.52243946802192e-19[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]1.33029800610328e-19[/C][C]2.66059601220657e-19[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]4.73643997363881e-20[/C][C]9.47287994727762e-20[/C][C]1[/C][/ROW]
[ROW][C]68[/C][C]1.31532632158714e-20[/C][C]2.63065264317429e-20[/C][C]1[/C][/ROW]
[ROW][C]69[/C][C]3.97415018378257e-21[/C][C]7.94830036756515e-21[/C][C]1[/C][/ROW]
[ROW][C]70[/C][C]1.05282671919267e-21[/C][C]2.10565343838535e-21[/C][C]1[/C][/ROW]
[ROW][C]71[/C][C]4.45503094031622e-22[/C][C]8.91006188063244e-22[/C][C]1[/C][/ROW]
[ROW][C]72[/C][C]1.29979290611789e-22[/C][C]2.59958581223578e-22[/C][C]1[/C][/ROW]
[ROW][C]73[/C][C]3.94393602579606e-23[/C][C]7.88787205159211e-23[/C][C]1[/C][/ROW]
[ROW][C]74[/C][C]1.08443046529128e-23[/C][C]2.16886093058256e-23[/C][C]1[/C][/ROW]
[ROW][C]75[/C][C]4.16710867027872e-24[/C][C]8.33421734055745e-24[/C][C]1[/C][/ROW]
[ROW][C]76[/C][C]2.44221758086819e-21[/C][C]4.88443516173639e-21[/C][C]1[/C][/ROW]
[ROW][C]77[/C][C]6.93782333448249e-22[/C][C]1.3875646668965e-21[/C][C]1[/C][/ROW]
[ROW][C]78[/C][C]1.98394623496402e-22[/C][C]3.96789246992803e-22[/C][C]1[/C][/ROW]
[ROW][C]79[/C][C]6.11850564689915e-23[/C][C]1.22370112937983e-22[/C][C]1[/C][/ROW]
[ROW][C]80[/C][C]2.15148496617773e-23[/C][C]4.30296993235546e-23[/C][C]1[/C][/ROW]
[ROW][C]81[/C][C]1.60530727631681e-23[/C][C]3.21061455263362e-23[/C][C]1[/C][/ROW]
[ROW][C]82[/C][C]9.94786935371148e-24[/C][C]1.9895738707423e-23[/C][C]1[/C][/ROW]
[ROW][C]83[/C][C]3.82199362203697e-24[/C][C]7.64398724407394e-24[/C][C]1[/C][/ROW]
[ROW][C]84[/C][C]1.51987199307491e-24[/C][C]3.03974398614983e-24[/C][C]1[/C][/ROW]
[ROW][C]85[/C][C]4.29052597315241e-25[/C][C]8.58105194630481e-25[/C][C]1[/C][/ROW]
[ROW][C]86[/C][C]2.63160295689058e-25[/C][C]5.26320591378116e-25[/C][C]1[/C][/ROW]
[ROW][C]87[/C][C]8.23975026899792e-26[/C][C]1.64795005379958e-25[/C][C]1[/C][/ROW]
[ROW][C]88[/C][C]2.85145703923253e-26[/C][C]5.70291407846506e-26[/C][C]1[/C][/ROW]
[ROW][C]89[/C][C]9.46099190632506e-27[/C][C]1.89219838126501e-26[/C][C]1[/C][/ROW]
[ROW][C]90[/C][C]2.48008923736238e-27[/C][C]4.96017847472477e-27[/C][C]1[/C][/ROW]
[ROW][C]91[/C][C]6.48813013335737e-28[/C][C]1.29762602667147e-27[/C][C]1[/C][/ROW]
[ROW][C]92[/C][C]1.67976155329365e-28[/C][C]3.35952310658731e-28[/C][C]1[/C][/ROW]
[ROW][C]93[/C][C]4.86437685525031e-29[/C][C]9.72875371050061e-29[/C][C]1[/C][/ROW]
[ROW][C]94[/C][C]1.59536159391967e-29[/C][C]3.19072318783934e-29[/C][C]1[/C][/ROW]
[ROW][C]95[/C][C]6.66940428718951e-30[/C][C]1.3338808574379e-29[/C][C]1[/C][/ROW]
[ROW][C]96[/C][C]7.6571285284373e-13[/C][C]1.53142570568746e-12[/C][C]0.999999999999234[/C][/ROW]
[ROW][C]97[/C][C]9.76178902096493e-13[/C][C]1.95235780419299e-12[/C][C]0.999999999999024[/C][/ROW]
[ROW][C]98[/C][C]6.49312539768782e-13[/C][C]1.29862507953756e-12[/C][C]0.999999999999351[/C][/ROW]
[ROW][C]99[/C][C]2.99796386455016e-13[/C][C]5.99592772910032e-13[/C][C]0.9999999999997[/C][/ROW]
[ROW][C]100[/C][C]1.39858430751045e-13[/C][C]2.79716861502091e-13[/C][C]0.99999999999986[/C][/ROW]
[ROW][C]101[/C][C]6.78050396859239e-14[/C][C]1.35610079371848e-13[/C][C]0.999999999999932[/C][/ROW]
[ROW][C]102[/C][C]3.08752902131752e-14[/C][C]6.17505804263504e-14[/C][C]0.999999999999969[/C][/ROW]
[ROW][C]103[/C][C]1.50093100905883e-14[/C][C]3.00186201811767e-14[/C][C]0.999999999999985[/C][/ROW]
[ROW][C]104[/C][C]9.74619549298292e-15[/C][C]1.94923909859658e-14[/C][C]0.99999999999999[/C][/ROW]
[ROW][C]105[/C][C]4.85441617817279e-15[/C][C]9.70883235634558e-15[/C][C]0.999999999999995[/C][/ROW]
[ROW][C]106[/C][C]2.12708669844312e-15[/C][C]4.25417339688624e-15[/C][C]0.999999999999998[/C][/ROW]
[ROW][C]107[/C][C]1.73290670874748e-15[/C][C]3.46581341749496e-15[/C][C]0.999999999999998[/C][/ROW]
[ROW][C]108[/C][C]1.1921071278637e-15[/C][C]2.3842142557274e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]109[/C][C]6.64986689016781e-16[/C][C]1.32997337803356e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]110[/C][C]2.98091484595664e-16[/C][C]5.96182969191328e-16[/C][C]1[/C][/ROW]
[ROW][C]111[/C][C]1.2781181983873e-16[/C][C]2.55623639677459e-16[/C][C]1[/C][/ROW]
[ROW][C]112[/C][C]5.71391245835229e-17[/C][C]1.14278249167046e-16[/C][C]1[/C][/ROW]
[ROW][C]113[/C][C]2.64364523911667e-17[/C][C]5.28729047823334e-17[/C][C]1[/C][/ROW]
[ROW][C]114[/C][C]1.15168822139017e-17[/C][C]2.30337644278033e-17[/C][C]1[/C][/ROW]
[ROW][C]115[/C][C]8.77195474308629e-18[/C][C]1.75439094861726e-17[/C][C]1[/C][/ROW]
[ROW][C]116[/C][C]3.61077930300136e-18[/C][C]7.22155860600272e-18[/C][C]1[/C][/ROW]
[ROW][C]117[/C][C]1.60838054871396e-18[/C][C]3.21676109742793e-18[/C][C]1[/C][/ROW]
[ROW][C]118[/C][C]6.68826047639436e-19[/C][C]1.33765209527887e-18[/C][C]1[/C][/ROW]
[ROW][C]119[/C][C]7.52520087289492e-19[/C][C]1.50504017457898e-18[/C][C]1[/C][/ROW]
[ROW][C]120[/C][C]4.14093349825008e-19[/C][C]8.28186699650017e-19[/C][C]1[/C][/ROW]
[ROW][C]121[/C][C]4.4401078073268e-19[/C][C]8.88021561465359e-19[/C][C]1[/C][/ROW]
[ROW][C]122[/C][C]2.13146824244111e-19[/C][C]4.26293648488221e-19[/C][C]1[/C][/ROW]
[ROW][C]123[/C][C]8.45003056176865e-20[/C][C]1.69000611235373e-19[/C][C]1[/C][/ROW]
[ROW][C]124[/C][C]3.31240321957062e-20[/C][C]6.62480643914124e-20[/C][C]1[/C][/ROW]
[ROW][C]125[/C][C]1.2896307871485e-20[/C][C]2.57926157429699e-20[/C][C]1[/C][/ROW]
[ROW][C]126[/C][C]6.13412814924853e-21[/C][C]1.22682562984971e-20[/C][C]1[/C][/ROW]
[ROW][C]127[/C][C]6.11477913739636e-21[/C][C]1.22295582747927e-20[/C][C]1[/C][/ROW]
[ROW][C]128[/C][C]6.72801228519865e-21[/C][C]1.34560245703973e-20[/C][C]1[/C][/ROW]
[ROW][C]129[/C][C]2.63270291130334e-21[/C][C]5.26540582260669e-21[/C][C]1[/C][/ROW]
[ROW][C]130[/C][C]1.00481205791479e-21[/C][C]2.00962411582959e-21[/C][C]1[/C][/ROW]
[ROW][C]131[/C][C]4.06304217569985e-22[/C][C]8.12608435139969e-22[/C][C]1[/C][/ROW]
[ROW][C]132[/C][C]2.04213091230376e-22[/C][C]4.08426182460752e-22[/C][C]1[/C][/ROW]
[ROW][C]133[/C][C]8.10875163909767e-23[/C][C]1.62175032781953e-22[/C][C]1[/C][/ROW]
[ROW][C]134[/C][C]6.65973932583131e-23[/C][C]1.33194786516626e-22[/C][C]1[/C][/ROW]
[ROW][C]135[/C][C]1.67897192319721e-22[/C][C]3.35794384639442e-22[/C][C]1[/C][/ROW]
[ROW][C]136[/C][C]6.54235730952432e-23[/C][C]1.30847146190486e-22[/C][C]1[/C][/ROW]
[ROW][C]137[/C][C]6.65700343358902e-23[/C][C]1.3314006867178e-22[/C][C]1[/C][/ROW]
[ROW][C]138[/C][C]5.11082901492219e-23[/C][C]1.02216580298444e-22[/C][C]1[/C][/ROW]
[ROW][C]139[/C][C]3.2535778620403e-23[/C][C]6.50715572408059e-23[/C][C]1[/C][/ROW]
[ROW][C]140[/C][C]7.2532408614429e-23[/C][C]1.45064817228858e-22[/C][C]1[/C][/ROW]
[ROW][C]141[/C][C]3.65474090820608e-23[/C][C]7.30948181641216e-23[/C][C]1[/C][/ROW]
[ROW][C]142[/C][C]1.62740760082149e-23[/C][C]3.25481520164298e-23[/C][C]1[/C][/ROW]
[ROW][C]143[/C][C]1.52345571830783e-23[/C][C]3.04691143661567e-23[/C][C]1[/C][/ROW]
[ROW][C]144[/C][C]8.03140500494425e-24[/C][C]1.60628100098885e-23[/C][C]1[/C][/ROW]
[ROW][C]145[/C][C]2.98220826916025e-24[/C][C]5.96441653832051e-24[/C][C]1[/C][/ROW]
[ROW][C]146[/C][C]1.35701337838469e-24[/C][C]2.71402675676937e-24[/C][C]1[/C][/ROW]
[ROW][C]147[/C][C]7.61112671305493e-25[/C][C]1.52222534261099e-24[/C][C]1[/C][/ROW]
[ROW][C]148[/C][C]1.42453018077481e-24[/C][C]2.84906036154962e-24[/C][C]1[/C][/ROW]
[ROW][C]149[/C][C]5.21816071352311e-25[/C][C]1.04363214270462e-24[/C][C]1[/C][/ROW]
[ROW][C]150[/C][C]1.97874271087842e-25[/C][C]3.95748542175684e-25[/C][C]1[/C][/ROW]
[ROW][C]151[/C][C]7.16787173565031e-26[/C][C]1.43357434713006e-25[/C][C]1[/C][/ROW]
[ROW][C]152[/C][C]4.23785577580256e-26[/C][C]8.47571155160511e-26[/C][C]1[/C][/ROW]
[ROW][C]153[/C][C]8.3269891891721e-26[/C][C]1.66539783783442e-25[/C][C]1[/C][/ROW]
[ROW][C]154[/C][C]3.24748844377395e-26[/C][C]6.4949768875479e-26[/C][C]1[/C][/ROW]
[ROW][C]155[/C][C]1.22327972285506e-26[/C][C]2.44655944571012e-26[/C][C]1[/C][/ROW]
[ROW][C]156[/C][C]8.49476442644546e-27[/C][C]1.69895288528909e-26[/C][C]1[/C][/ROW]
[ROW][C]157[/C][C]6.56497610229756e-27[/C][C]1.31299522045951e-26[/C][C]1[/C][/ROW]
[ROW][C]158[/C][C]4.1225374982279e-27[/C][C]8.24507499645579e-27[/C][C]1[/C][/ROW]
[ROW][C]159[/C][C]2.92540325885161e-27[/C][C]5.85080651770322e-27[/C][C]1[/C][/ROW]
[ROW][C]160[/C][C]3.64250610258087e-27[/C][C]7.28501220516175e-27[/C][C]1[/C][/ROW]
[ROW][C]161[/C][C]1.37565338179151e-27[/C][C]2.75130676358302e-27[/C][C]1[/C][/ROW]
[ROW][C]162[/C][C]6.36295561221492e-28[/C][C]1.27259112244298e-27[/C][C]1[/C][/ROW]
[ROW][C]163[/C][C]2.51463619074245e-28[/C][C]5.0292723814849e-28[/C][C]1[/C][/ROW]
[ROW][C]164[/C][C]8.98201729774404e-29[/C][C]1.79640345954881e-28[/C][C]1[/C][/ROW]
[ROW][C]165[/C][C]3.0814183736838e-29[/C][C]6.16283674736759e-29[/C][C]1[/C][/ROW]
[ROW][C]166[/C][C]1.44176774910502e-29[/C][C]2.88353549821005e-29[/C][C]1[/C][/ROW]
[ROW][C]167[/C][C]2.81945446616384e-29[/C][C]5.63890893232767e-29[/C][C]1[/C][/ROW]
[ROW][C]168[/C][C]9.90925082280436e-30[/C][C]1.98185016456087e-29[/C][C]1[/C][/ROW]
[ROW][C]169[/C][C]4.79050549892752e-30[/C][C]9.58101099785503e-30[/C][C]1[/C][/ROW]
[ROW][C]170[/C][C]1.6778714869524e-30[/C][C]3.35574297390479e-30[/C][C]1[/C][/ROW]
[ROW][C]171[/C][C]3.5901891216126e-30[/C][C]7.18037824322519e-30[/C][C]1[/C][/ROW]
[ROW][C]172[/C][C]2.27534354529478e-30[/C][C]4.55068709058956e-30[/C][C]1[/C][/ROW]
[ROW][C]173[/C][C]1.9102347540604e-30[/C][C]3.8204695081208e-30[/C][C]1[/C][/ROW]
[ROW][C]174[/C][C]6.11696738579295e-31[/C][C]1.22339347715859e-30[/C][C]1[/C][/ROW]
[ROW][C]175[/C][C]2.42072057764346e-31[/C][C]4.84144115528692e-31[/C][C]1[/C][/ROW]
[ROW][C]176[/C][C]9.06648796713906e-32[/C][C]1.81329759342781e-31[/C][C]1[/C][/ROW]
[ROW][C]177[/C][C]3.88197464518193e-32[/C][C]7.76394929036387e-32[/C][C]1[/C][/ROW]
[ROW][C]178[/C][C]1.49106282553954e-32[/C][C]2.98212565107908e-32[/C][C]1[/C][/ROW]
[ROW][C]179[/C][C]1.14032353107631e-32[/C][C]2.28064706215262e-32[/C][C]1[/C][/ROW]
[ROW][C]180[/C][C]5.24667591042058e-32[/C][C]1.04933518208412e-31[/C][C]1[/C][/ROW]
[ROW][C]181[/C][C]1.7105981191061e-32[/C][C]3.4211962382122e-32[/C][C]1[/C][/ROW]
[ROW][C]182[/C][C]1.56928290163152e-31[/C][C]3.13856580326304e-31[/C][C]1[/C][/ROW]
[ROW][C]183[/C][C]6.35730739132531e-32[/C][C]1.27146147826506e-31[/C][C]1[/C][/ROW]
[ROW][C]184[/C][C]9.61078816949466e-32[/C][C]1.92215763389893e-31[/C][C]1[/C][/ROW]
[ROW][C]185[/C][C]2.99398771487355e-32[/C][C]5.9879754297471e-32[/C][C]1[/C][/ROW]
[ROW][C]186[/C][C]8.76225475703964e-32[/C][C]1.75245095140793e-31[/C][C]1[/C][/ROW]
[ROW][C]187[/C][C]5.63591619315826e-32[/C][C]1.12718323863165e-31[/C][C]1[/C][/ROW]
[ROW][C]188[/C][C]2.75762536835221e-32[/C][C]5.51525073670441e-32[/C][C]1[/C][/ROW]
[ROW][C]189[/C][C]9.56538257103507e-33[/C][C]1.91307651420701e-32[/C][C]1[/C][/ROW]
[ROW][C]190[/C][C]9.06348554658617e-33[/C][C]1.81269710931723e-32[/C][C]1[/C][/ROW]
[ROW][C]191[/C][C]2.67867021545687e-33[/C][C]5.35734043091374e-33[/C][C]1[/C][/ROW]
[ROW][C]192[/C][C]2.47705278399485e-33[/C][C]4.95410556798969e-33[/C][C]1[/C][/ROW]
[ROW][C]193[/C][C]7.67747341443405e-34[/C][C]1.53549468288681e-33[/C][C]1[/C][/ROW]
[ROW][C]194[/C][C]3.06756988687329e-34[/C][C]6.13513977374658e-34[/C][C]1[/C][/ROW]
[ROW][C]195[/C][C]4.4092192866583e-34[/C][C]8.8184385733166e-34[/C][C]1[/C][/ROW]
[ROW][C]196[/C][C]2.55895894053292e-34[/C][C]5.11791788106584e-34[/C][C]1[/C][/ROW]
[ROW][C]197[/C][C]9.37584353577028e-33[/C][C]1.87516870715406e-32[/C][C]1[/C][/ROW]
[ROW][C]198[/C][C]3.70714502857103e-33[/C][C]7.41429005714206e-33[/C][C]1[/C][/ROW]
[ROW][C]199[/C][C]1.49782419466732e-33[/C][C]2.99564838933464e-33[/C][C]1[/C][/ROW]
[ROW][C]200[/C][C]1.70227905902343e-30[/C][C]3.40455811804685e-30[/C][C]1[/C][/ROW]
[ROW][C]201[/C][C]5.73162836187843e-31[/C][C]1.14632567237569e-30[/C][C]1[/C][/ROW]
[ROW][C]202[/C][C]9.37168186574223e-30[/C][C]1.87433637314845e-29[/C][C]1[/C][/ROW]
[ROW][C]203[/C][C]2.92032611276397e-28[/C][C]5.84065222552795e-28[/C][C]1[/C][/ROW]
[ROW][C]204[/C][C]1.42823105869137e-26[/C][C]2.85646211738273e-26[/C][C]1[/C][/ROW]
[ROW][C]205[/C][C]7.145001859475e-27[/C][C]1.429000371895e-26[/C][C]1[/C][/ROW]
[ROW][C]206[/C][C]3.68413035360861e-26[/C][C]7.36826070721721e-26[/C][C]1[/C][/ROW]
[ROW][C]207[/C][C]1.64088583052877e-17[/C][C]3.28177166105755e-17[/C][C]1[/C][/ROW]
[ROW][C]208[/C][C]7.2459788331065e-16[/C][C]1.4491957666213e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]209[/C][C]2.94793713012057e-16[/C][C]5.89587426024114e-16[/C][C]1[/C][/ROW]
[ROW][C]210[/C][C]1.25547482291419e-16[/C][C]2.51094964582837e-16[/C][C]1[/C][/ROW]
[ROW][C]211[/C][C]4.86161611603356e-17[/C][C]9.72323223206711e-17[/C][C]1[/C][/ROW]
[ROW][C]212[/C][C]3.16261553475845e-17[/C][C]6.3252310695169e-17[/C][C]1[/C][/ROW]
[ROW][C]213[/C][C]2.87732679077577e-16[/C][C]5.75465358155154e-16[/C][C]1[/C][/ROW]
[ROW][C]214[/C][C]1.09334005595711e-16[/C][C]2.18668011191422e-16[/C][C]1[/C][/ROW]
[ROW][C]215[/C][C]1.23365933601072e-15[/C][C]2.46731867202144e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]216[/C][C]1[/C][C]1.88619482554936e-29[/C][C]9.43097412774682e-30[/C][/ROW]
[ROW][C]217[/C][C]1[/C][C]6.14479450106136e-28[/C][C]3.07239725053068e-28[/C][/ROW]
[ROW][C]218[/C][C]1[/C][C]1.05700206822358e-26[/C][C]5.2850103411179e-27[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]3.79687033004673e-25[/C][C]1.89843516502337e-25[/C][/ROW]
[ROW][C]220[/C][C]1[/C][C]1.28502187668747e-23[/C][C]6.42510938343734e-24[/C][/ROW]
[ROW][C]221[/C][C]1[/C][C]3.20852963292641e-22[/C][C]1.60426481646321e-22[/C][/ROW]
[ROW][C]222[/C][C]1[/C][C]8.90378275503835e-21[/C][C]4.45189137751917e-21[/C][/ROW]
[ROW][C]223[/C][C]1[/C][C]1.9278591699128e-19[/C][C]9.639295849564e-20[/C][/ROW]
[ROW][C]224[/C][C]1[/C][C]1.58349433024276e-19[/C][C]7.9174716512138e-20[/C][/ROW]
[ROW][C]225[/C][C]1[/C][C]1.66245820638847e-18[/C][C]8.31229103194235e-19[/C][/ROW]
[ROW][C]226[/C][C]1[/C][C]2.06125417771916e-17[/C][C]1.03062708885958e-17[/C][/ROW]
[ROW][C]227[/C][C]1[/C][C]9.47517956072592e-16[/C][C]4.73758978036296e-16[/C][/ROW]
[ROW][C]228[/C][C]0.999999999999978[/C][C]4.45501937856737e-14[/C][C]2.22750968928368e-14[/C][/ROW]
[ROW][C]229[/C][C]0.999999999999259[/C][C]1.48256133519639e-12[/C][C]7.41280667598194e-13[/C][/ROW]
[ROW][C]230[/C][C]0.999999999975173[/C][C]4.96539519534087e-11[/C][C]2.48269759767043e-11[/C][/ROW]
[ROW][C]231[/C][C]0.999999999033206[/C][C]1.93358799812747e-09[/C][C]9.66793999063734e-10[/C][/ROW]
[ROW][C]232[/C][C]0.999999960389398[/C][C]7.92212042883087e-08[/C][C]3.96106021441543e-08[/C][/ROW]
[ROW][C]233[/C][C]0.999998551752097[/C][C]2.89649580658653e-06[/C][C]1.44824790329327e-06[/C][/ROW]
[ROW][C]234[/C][C]0.99998376368619[/C][C]3.24726276203125e-05[/C][C]1.62363138101563e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190063&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190063&T=5

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
18	0.000127427931555219	0.000254855863110437	0.999872572068445
19	6.23033066595257e-06	1.24606613319051e-05	0.999993769669334
20	3.6191491818827e-07	7.23829836376539e-07	0.999999638085082
21	2.64584378661583e-08	5.29168757323166e-08	0.999999973541562
22	1.04108762120523e-09	2.08217524241046e-09	0.999999998958912
23	2.55410729395196e-10	5.10821458790392e-10	0.999999999744589
24	1.34262454432828e-11	2.68524908865656e-11	0.999999999986574
25	6.16542019451254e-13	1.23308403890251e-12	0.999999999999383
26	3.6189416315068e-14	7.2378832630136e-14	0.999999999999964
27	1.90062479680284e-15	3.80124959360568e-15	0.999999999999998
28	1.6608574150786e-16	3.3217148301572e-16	1
29	7.02343286150802e-18	1.4046865723016e-17	1
30	3.58705225679735e-19	7.17410451359469e-19	1
31	1.5349144820379e-20	3.0698289640758e-20	1
32	7.47823395113745e-22	1.49564679022749e-21	1
33	2.9940018148274e-23	5.98800362965481e-23	1
34	1.12594507116991e-24	2.25189014233983e-24	1
35	1.53813341997565e-24	3.07626683995131e-24	1
36	4.71465498344275e-24	9.42930996688549e-24	1
37	3.02398823079062e-25	6.04797646158124e-25	1
38	2.23714087769587e-26	4.47428175539173e-26	1
39	1.51219006209464e-27	3.02438012418929e-27	1
40	7.29428292565371e-29	1.45885658513074e-28	1
41	4.09844116113918e-30	8.19688232227835e-30	1
42	2.03178603822745e-31	4.0635720764549e-31	1
43	9.4942448633285e-33	1.8988489726657e-32	1
44	6.12928135361992e-34	1.22585627072398e-33	1
45	4.81878689883128e-35	9.63757379766255e-35	1
46	2.25756324341725e-36	4.5151264868345e-36	1
47	1.02845310146813e-37	2.05690620293627e-37	1
48	1.44739014845124e-11	2.89478029690248e-11	0.999999999985526
49	5.18688777677078e-12	1.03737755535416e-11	0.999999999994813
50	1.99926812434125e-12	3.9985362486825e-12	0.999999999998001
51	6.98395887967044e-13	1.39679177593409e-12	0.999999999999302
52	2.2958210839597e-13	4.59164216791941e-13	0.99999999999977
53	8.35855442808583e-14	1.67171088561717e-13	0.999999999999916
54	1.21342561138843e-13	2.42685122277686e-13	0.999999999999879
55	4.24276018302817e-14	8.48552036605633e-14	0.999999999999958
56	1.30172689340735e-14	2.6034537868147e-14	0.999999999999987
57	4.38086846731482e-15	8.76173693462964e-15	0.999999999999996
58	1.31146690878633e-15	2.62293381757267e-15	0.999999999999999
59	4.05331160845596e-16	8.10662321691192e-16	1
60	1.16233491732254e-16	2.32466983464508e-16	1
61	3.76193430149025e-17	7.5238686029805e-17	1
62	1.62093831707261e-17	3.24187663414522e-17	1
63	5.61668139042605e-18	1.12333627808521e-17	1
64	1.53953062651192e-18	3.07906125302384e-18	1
65	4.26121973401096e-19	8.52243946802192e-19	1
66	1.33029800610328e-19	2.66059601220657e-19	1
67	4.73643997363881e-20	9.47287994727762e-20	1
68	1.31532632158714e-20	2.63065264317429e-20	1
69	3.97415018378257e-21	7.94830036756515e-21	1
70	1.05282671919267e-21	2.10565343838535e-21	1
71	4.45503094031622e-22	8.91006188063244e-22	1
72	1.29979290611789e-22	2.59958581223578e-22	1
73	3.94393602579606e-23	7.88787205159211e-23	1
74	1.08443046529128e-23	2.16886093058256e-23	1
75	4.16710867027872e-24	8.33421734055745e-24	1
76	2.44221758086819e-21	4.88443516173639e-21	1
77	6.93782333448249e-22	1.3875646668965e-21	1
78	1.98394623496402e-22	3.96789246992803e-22	1
79	6.11850564689915e-23	1.22370112937983e-22	1
80	2.15148496617773e-23	4.30296993235546e-23	1
81	1.60530727631681e-23	3.21061455263362e-23	1
82	9.94786935371148e-24	1.9895738707423e-23	1
83	3.82199362203697e-24	7.64398724407394e-24	1
84	1.51987199307491e-24	3.03974398614983e-24	1
85	4.29052597315241e-25	8.58105194630481e-25	1
86	2.63160295689058e-25	5.26320591378116e-25	1
87	8.23975026899792e-26	1.64795005379958e-25	1
88	2.85145703923253e-26	5.70291407846506e-26	1
89	9.46099190632506e-27	1.89219838126501e-26	1
90	2.48008923736238e-27	4.96017847472477e-27	1
91	6.48813013335737e-28	1.29762602667147e-27	1
92	1.67976155329365e-28	3.35952310658731e-28	1
93	4.86437685525031e-29	9.72875371050061e-29	1
94	1.59536159391967e-29	3.19072318783934e-29	1
95	6.66940428718951e-30	1.3338808574379e-29	1
96	7.6571285284373e-13	1.53142570568746e-12	0.999999999999234
97	9.76178902096493e-13	1.95235780419299e-12	0.999999999999024
98	6.49312539768782e-13	1.29862507953756e-12	0.999999999999351
99	2.99796386455016e-13	5.99592772910032e-13	0.9999999999997
100	1.39858430751045e-13	2.79716861502091e-13	0.99999999999986
101	6.78050396859239e-14	1.35610079371848e-13	0.999999999999932
102	3.08752902131752e-14	6.17505804263504e-14	0.999999999999969
103	1.50093100905883e-14	3.00186201811767e-14	0.999999999999985
104	9.74619549298292e-15	1.94923909859658e-14	0.99999999999999
105	4.85441617817279e-15	9.70883235634558e-15	0.999999999999995
106	2.12708669844312e-15	4.25417339688624e-15	0.999999999999998
107	1.73290670874748e-15	3.46581341749496e-15	0.999999999999998
108	1.1921071278637e-15	2.3842142557274e-15	0.999999999999999
109	6.64986689016781e-16	1.32997337803356e-15	0.999999999999999
110	2.98091484595664e-16	5.96182969191328e-16	1
111	1.2781181983873e-16	2.55623639677459e-16	1
112	5.71391245835229e-17	1.14278249167046e-16	1
113	2.64364523911667e-17	5.28729047823334e-17	1
114	1.15168822139017e-17	2.30337644278033e-17	1
115	8.77195474308629e-18	1.75439094861726e-17	1
116	3.61077930300136e-18	7.22155860600272e-18	1
117	1.60838054871396e-18	3.21676109742793e-18	1
118	6.68826047639436e-19	1.33765209527887e-18	1
119	7.52520087289492e-19	1.50504017457898e-18	1
120	4.14093349825008e-19	8.28186699650017e-19	1
121	4.4401078073268e-19	8.88021561465359e-19	1
122	2.13146824244111e-19	4.26293648488221e-19	1
123	8.45003056176865e-20	1.69000611235373e-19	1
124	3.31240321957062e-20	6.62480643914124e-20	1
125	1.2896307871485e-20	2.57926157429699e-20	1
126	6.13412814924853e-21	1.22682562984971e-20	1
127	6.11477913739636e-21	1.22295582747927e-20	1
128	6.72801228519865e-21	1.34560245703973e-20	1
129	2.63270291130334e-21	5.26540582260669e-21	1
130	1.00481205791479e-21	2.00962411582959e-21	1
131	4.06304217569985e-22	8.12608435139969e-22	1
132	2.04213091230376e-22	4.08426182460752e-22	1
133	8.10875163909767e-23	1.62175032781953e-22	1
134	6.65973932583131e-23	1.33194786516626e-22	1
135	1.67897192319721e-22	3.35794384639442e-22	1
136	6.54235730952432e-23	1.30847146190486e-22	1
137	6.65700343358902e-23	1.3314006867178e-22	1
138	5.11082901492219e-23	1.02216580298444e-22	1
139	3.2535778620403e-23	6.50715572408059e-23	1
140	7.2532408614429e-23	1.45064817228858e-22	1
141	3.65474090820608e-23	7.30948181641216e-23	1
142	1.62740760082149e-23	3.25481520164298e-23	1
143	1.52345571830783e-23	3.04691143661567e-23	1
144	8.03140500494425e-24	1.60628100098885e-23	1
145	2.98220826916025e-24	5.96441653832051e-24	1
146	1.35701337838469e-24	2.71402675676937e-24	1
147	7.61112671305493e-25	1.52222534261099e-24	1
148	1.42453018077481e-24	2.84906036154962e-24	1
149	5.21816071352311e-25	1.04363214270462e-24	1
150	1.97874271087842e-25	3.95748542175684e-25	1
151	7.16787173565031e-26	1.43357434713006e-25	1
152	4.23785577580256e-26	8.47571155160511e-26	1
153	8.3269891891721e-26	1.66539783783442e-25	1
154	3.24748844377395e-26	6.4949768875479e-26	1
155	1.22327972285506e-26	2.44655944571012e-26	1
156	8.49476442644546e-27	1.69895288528909e-26	1
157	6.56497610229756e-27	1.31299522045951e-26	1
158	4.1225374982279e-27	8.24507499645579e-27	1
159	2.92540325885161e-27	5.85080651770322e-27	1
160	3.64250610258087e-27	7.28501220516175e-27	1
161	1.37565338179151e-27	2.75130676358302e-27	1
162	6.36295561221492e-28	1.27259112244298e-27	1
163	2.51463619074245e-28	5.0292723814849e-28	1
164	8.98201729774404e-29	1.79640345954881e-28	1
165	3.0814183736838e-29	6.16283674736759e-29	1
166	1.44176774910502e-29	2.88353549821005e-29	1
167	2.81945446616384e-29	5.63890893232767e-29	1
168	9.90925082280436e-30	1.98185016456087e-29	1
169	4.79050549892752e-30	9.58101099785503e-30	1
170	1.6778714869524e-30	3.35574297390479e-30	1
171	3.5901891216126e-30	7.18037824322519e-30	1
172	2.27534354529478e-30	4.55068709058956e-30	1
173	1.9102347540604e-30	3.8204695081208e-30	1
174	6.11696738579295e-31	1.22339347715859e-30	1
175	2.42072057764346e-31	4.84144115528692e-31	1
176	9.06648796713906e-32	1.81329759342781e-31	1
177	3.88197464518193e-32	7.76394929036387e-32	1
178	1.49106282553954e-32	2.98212565107908e-32	1
179	1.14032353107631e-32	2.28064706215262e-32	1
180	5.24667591042058e-32	1.04933518208412e-31	1
181	1.7105981191061e-32	3.4211962382122e-32	1
182	1.56928290163152e-31	3.13856580326304e-31	1
183	6.35730739132531e-32	1.27146147826506e-31	1
184	9.61078816949466e-32	1.92215763389893e-31	1
185	2.99398771487355e-32	5.9879754297471e-32	1
186	8.76225475703964e-32	1.75245095140793e-31	1
187	5.63591619315826e-32	1.12718323863165e-31	1
188	2.75762536835221e-32	5.51525073670441e-32	1
189	9.56538257103507e-33	1.91307651420701e-32	1
190	9.06348554658617e-33	1.81269710931723e-32	1
191	2.67867021545687e-33	5.35734043091374e-33	1
192	2.47705278399485e-33	4.95410556798969e-33	1
193	7.67747341443405e-34	1.53549468288681e-33	1
194	3.06756988687329e-34	6.13513977374658e-34	1
195	4.4092192866583e-34	8.8184385733166e-34	1
196	2.55895894053292e-34	5.11791788106584e-34	1
197	9.37584353577028e-33	1.87516870715406e-32	1
198	3.70714502857103e-33	7.41429005714206e-33	1
199	1.49782419466732e-33	2.99564838933464e-33	1
200	1.70227905902343e-30	3.40455811804685e-30	1
201	5.73162836187843e-31	1.14632567237569e-30	1
202	9.37168186574223e-30	1.87433637314845e-29	1
203	2.92032611276397e-28	5.84065222552795e-28	1
204	1.42823105869137e-26	2.85646211738273e-26	1
205	7.145001859475e-27	1.429000371895e-26	1
206	3.68413035360861e-26	7.36826070721721e-26	1
207	1.64088583052877e-17	3.28177166105755e-17	1
208	7.2459788331065e-16	1.4491957666213e-15	0.999999999999999
209	2.94793713012057e-16	5.89587426024114e-16	1
210	1.25547482291419e-16	2.51094964582837e-16	1
211	4.86161611603356e-17	9.72323223206711e-17	1
212	3.16261553475845e-17	6.3252310695169e-17	1
213	2.87732679077577e-16	5.75465358155154e-16	1
214	1.09334005595711e-16	2.18668011191422e-16	1
215	1.23365933601072e-15	2.46731867202144e-15	0.999999999999999
216	1	1.88619482554936e-29	9.43097412774682e-30
217	1	6.14479450106136e-28	3.07239725053068e-28
218	1	1.05700206822358e-26	5.2850103411179e-27
219	1	3.79687033004673e-25	1.89843516502337e-25
220	1	1.28502187668747e-23	6.42510938343734e-24
221	1	3.20852963292641e-22	1.60426481646321e-22
222	1	8.90378275503835e-21	4.45189137751917e-21
223	1	1.9278591699128e-19	9.639295849564e-20
224	1	1.58349433024276e-19	7.9174716512138e-20
225	1	1.66245820638847e-18	8.31229103194235e-19
226	1	2.06125417771916e-17	1.03062708885958e-17
227	1	9.47517956072592e-16	4.73758978036296e-16
228	0.999999999999978	4.45501937856737e-14	2.22750968928368e-14
229	0.999999999999259	1.48256133519639e-12	7.41280667598194e-13
230	0.999999999975173	4.96539519534087e-11	2.48269759767043e-11
231	0.999999999033206	1.93358799812747e-09	9.66793999063734e-10
232	0.999999960389398	7.92212042883087e-08	3.96106021441543e-08
233	0.999998551752097	2.89649580658653e-06	1.44824790329327e-06
234	0.99998376368619	3.24726276203125e-05	1.62363138101563e-05

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	217	1	NOK
5% type I error level	217	1	NOK
10% type I error level	217	1	NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 217 & 1 & NOK \tabularnewline
5% type I error level & 217 & 1 & NOK \tabularnewline
10% type I error level & 217 & 1 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190063&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]217[/C][C]1[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]217[/C][C]1[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]217[/C][C]1[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190063&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190063&T=6

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	217	1	NOK
5% type I error level	217	1	NOK
10% type I error level	217	1	NOK

Figure 1

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

R code (references can be found in the software module):

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code