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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 02 Dec 2012 05:36:10 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/02/t1354444666ucct1ogfkxg9ebf.htm/, Retrieved Fri, 26 Apr 2024 04:06:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195409, Retrieved Fri, 26 Apr 2024 04:06:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact235

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2012-12-02 10:36:10] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
- RM      [Recursive Partitioning (Regression Trees)] [] [2012-12-17 14:30:52] [b98453cac15ba1066b407e146608df68]
- RM D    [Survey Scores] [] [2012-12-17 14:52:23] [b98453cac15ba1066b407e146608df68]
- RM D    [Cronbach Alpha] [] [2012-12-17 14:54:55] [b98453cac15ba1066b407e146608df68]
- RM      [Multiple Regression] [] [2013-01-04 15:20:15] [59c356eb3816b3d7a7d68ef3165b7ef4]
- RM      [Multiple Regression] [] [2013-01-13 22:23:28] [391561951b5d7f721cfaa4f5575ab127]
- R  D    [Multiple Regression] [] [2013-01-14 10:14:37] [74be16979710d4c4e7c6647856088456]
- R  D    [Multiple Regression] [] [2013-01-15 19:35:02] [456f9f31a5baae2eb9a0b13ee35c0d42]
-    D      [Multiple Regression] [] [2013-01-15 19:38:16] [456f9f31a5baae2eb9a0b13ee35c0d42]
-    D      [Multiple Regression] [] [2013-01-15 19:45:52] [456f9f31a5baae2eb9a0b13ee35c0d42]
-    D        [Multiple Regression] [] [2013-01-15 19:56:35] [456f9f31a5baae2eb9a0b13ee35c0d42]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102	122	88	1	9	8976	102	918	88	792	9
99	114	106	1	3	10494	99	297	106	318	3
97	140	70	1	2	6790	97	194	70	140	2
82	143	70	1	21	5740	82	1722	70	1470	21
77	122	56	1	10	4312	77	770	56	560	10
65	127	50	1	2	3250	65	130	50	100	2
64	113	48	1	4	3072	64	256	48	192	4
62	118	71	1	4	4402	62	248	71	284	4
62	161	61	1	4	3782	62	248	61	244	4
62	134	66	1	5	4092	62	310	66	330	5
61	96	80	1	2	4880	61	122	80	160	2
59	104	37	1	3	2183	59	177	37	111	3
57	135	53	1	3	3021	57	171	53	159	3
56	110	39	1	6	2184	56	336	39	234	6
54	128	40	1	3	2160	54	162	40	120	3
54	142	59	1	4	3186	54	216	59	236	4
53	117	42	1	3	2226	53	159	42	126	3
52	94	33	1	13	1716	52	676	33	429	13
51	135	36	1	3	1836	51	153	36	108	3
51	121	57	1	4	2907	51	204	57	228	4
51	103	38	1	8	1938	51	408	38	304	8
50	118	98	1	8	4900	50	400	98	784	8
50	127	43	1	3	2150	50	150	43	129	3
50	116	73	1	4	3650	50	200	73	292	4
49	129	52	1	2	2548	49	98	52	104	2
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49	135	51	1	4	2499	49	196	51	204	4
48	133	32	1	3	1536	48	144	32	96	3
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47	111	53	1	2	2491	47	94	53	106	2
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42	134	61	1	4	2562	42	168	61	244	4
41	161	54	1	7	2214	41	287	54	378	7
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41	123	49	1	7	2009	41	287	49	343	7
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40	78	52	1	4	2080	40	160	52	208	4
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38	142	43	1	4	1634	38	152	43	172	4
38	94	40	1	31	1520	38	1178	40	1240	31
36	114	38	1	3	1368	36	108	38	114	3
36	108	33	1	3	1188	36	108	33	99	3
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33	76	37	1	3	1221	33	99	37	111	3
33	119	48	1	16	1584	33	528	48	768	16
33	119	33	1	3	1089	33	99	33	99	3
32	124	40	1	3	1280	32	96	40	120	3
32	116	21	1	3	672	32	96	21	63	3
32	118	33	1	2	1056	32	64	33	66	2
31	102	41	1	5	1271	31	155	41	205	5
31	116	35	1	3	1085	31	93	35	105	3
30	103	60	1	4	1800	30	120	60	240	4
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30	108	45	1	2	1350	30	60	45	90	2
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27	110	35	1	4	945	27	108	35	140	4
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25	107	35	1	3	875	25	75	35	105	3
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24	115	23	1	3	552	24	72	23	69	3
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23	83	32	1	2	736	23	46	32	64	2
23	77	28	1	5	644	23	115	28	140	5
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19	8	12	1	2	228	19	38	12	24	2
17	69	27	1	5	459	17	85	27	135	5
17	88	28	1	3	476	17	51	28	84	3
16	107	12	1	5	192	16	80	12	60	5
16	120	21	1	5	336	16	80	21	105	5
5	3	9	1	4	45	5	20	9	36	4
4	1	11	1	2	44	4	8	11	22	2
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156	111	111	0	4	17316	0	624	0	444	0
109	69	137	0	8	14933	0	872	0	1096	0
104	116	112	0	3	11648	0	312	0	336	0
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78	139	99	0	3	7722	0	234	0	297	0
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73	113	95	0	3	6935	0	219	0	285	0
71	99	60	0	4	4260	0	284	0	240	0
67	76	94	0	4	6298	0	268	0	376	0
64	110	70	0	5	4480	0	320	0	350	0
62	121	87	0	2	5394	0	124	0	174	0
61	95	102	0	3	6222	0	183	0	306	0
58	66	69	0	4	4002	0	232	0	276	0
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56	77	55	0	3	3080	0	168	0	165	0
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52	108	90	0	3	4680	0	156	0	270	0
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49	104	87	0	4	4263	0	196	0	348	0
48	113	78	0	4	3744	0	192	0	312	0
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47	89	69	0	4	3243	0	188	0	276	0
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45	96	61	0	6	2745	0	270	0	366	0
45	95	123	0	4	5535	0	180	0	492	0
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45	106	98	0	6	4410	0	270	0	588	0
44	78	38	0	2	1672	0	88	0	76	0
44	115	72	0	3	3168	0	132	0	216	0
44	74	59	0	3	2596	0	132	0	177	0
43	93	78	0	2	3354	0	86	0	156	0
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42	104	97	0	5	4074	0	210	0	485	0
41	86	69	0	3	2829	0	123	0	207	0
41	104	50	0	7	2050	0	287	0	350	0
40	99	66	0	4	2640	0	160	0	264	0
39	101	70	0	3	2730	0	117	0	210	0
39	53	65	0	4	2535	0	156	0	260	0
39	96	69	0	4	2691	0	156	0	276	0
39	58	49	0	3	1911	0	117	0	147	0
39	117	72	0	3	2808	0	117	0	216	0
39	82	74	0	4	2886	0	156	0	296	0
39	57	82	0	5	3198	0	195	0	410	0
38	71	61	0	3	2318	0	114	0	183	0
38	105	72	0	4	2736	0	152	0	288	0
38	60	77	0	6	2926	0	228	0	462	0
38	77	64	0	5	2432	0	190	0	320	0
37	73	23	0	7	851	0	259	0	161	0
37	78	39	0	5	1443	0	185	0	195	0
37	81	87	0	5	3219	0	185	0	435	0
36	101	46	0	3	1656	0	108	0	138	0
36	118	66	0	5	2376	0	180	0	330	0
36	59	57	0	4	2052	0	144	0	228	0
36	101	48	0	9	1728	0	324	0	432	0
36	22	75	0	3	2700	0	108	0	225	0
36	77	35	0	3	1260	0	108	0	105	0
35	100	53	0	3	1855	0	105	0	159	0
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34	42	20	0	15	680	0	510	0	300	0
34	80	66	0	4	2244	0	136	0	264	0
34	48	34	0	6	1156	0	204	0	204	0
34	131	80	0	3	2720	0	102	0	240	0
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33	89	46	0	3	1518	0	99	0	138	0
33	51	20	0	5	660	0	165	0	100	0
33	108	73	0	3	2409	0	99	0	219	0
33	86	57	0	4	1881	0	132	0	228	0
33	105	65	0	7	2145	0	231	0	455	0
33	85	70	0	4	2310	0	132	0	280	0
32	103	53	0	5	1696	0	160	0	265	0
32	83	60	0	7	1920	0	224	0	420	0
32	77	34	0	14	1088	0	448	0	476	0
32	26	18	0	25	576	0	800	0	450	0
32	73	49	0	6	1568	0	192	0	294	0
31	42	27	0	4	837	0	124	0	108	0
31	71	45	0	3	1395	0	93	0	135	0
31	105	9	0	62	279	0	1922	0	558	0
30	73	23	0	5	690	0	150	0	115	0
30	98	61	0	10	1830	0	300	0	610	0
29	108	67	0	4	1943	0	116	0	268	0
29	57	72	0	5	2088	0	145	0	360	0
29	37	58	0	5	1682	0	145	0	290	0
28	70	55	0	4	1540	0	112	0	220	0
28	73	33	0	10	924	0	280	0	330	0
28	47	40	0	5	1120	0	140	0	200	0
28	73	57	0	3	1596	0	84	0	171	0
28	91	61	0	3	1708	0	84	0	183	0
28	110	87	0	17	2436	0	476	0	1479	0
27	78	65	0	4	1755	0	108	0	260	0
27	92	85	0	6	2295	0	162	0	510	0
27	52	85	0	3	2295	0	81	0	255	0
26	88	54	0	4	1404	0	104	0	216	0
26	100	24	0	8	624	0	208	0	192	0
26	33	31	0	3	806	0	78	0	93	0
26	42	64	0	4	1664	0	104	0	256	0
25	81	70	0	4	1750	0	100	0	280	0
25	67	2	0	47	50	0	1175	0	94	0
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24	46	29	0	3	696	0	72	0	87	0
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24	87	42	0	3	1008	0	72	0	126	0
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24	27	52	0	4	1248	0	96	0	208	0
23	14	25	0	12	575	0	276	0	300	0
23	83	38	0	8	874	0	184	0	304	0
23	168	40	0	3	920	0	69	0	120	0
23	67	42	0	8	966	0	184	0	336	0
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22	69	3	0	21	66	0	462	0	63	0
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21	72	68	0	3	1428	0	63	0	204	0
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21	40	36	0	4	756	0	84	0	144	0
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20	31	36	0	3	720	0	60	0	108	0
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20	38	54	0	5	1080	0	100	0	270	0
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19	91	30	0	16	570	0	304	0	480	0
19	58	40	0	10	760	0	190	0	400	0
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18	35	34	0	5	612	0	90	0	170	0
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15	65	34	0	9	510	0	135	0	306	0
15	95	29	0	12	435	0	180	0	348	0
15	29	24	0	10	360	0	150	0	240	0
15	2	24	0	9	360	0	135	0	216	0
14	83	23	0	17	322	0	238	0	391	0
13	11	43	0	6	559	0	78	0	258	0
13	16	28	0	3	364	0	39	0	84	0
12	9	19	0	4	228	0	48	0	76	0
11	46	16	0	19	176	0	209	0	304	0
11	41	40	0	3	440	0	33	0	120	0
10	14	14	0	9	140	0	90	0	126	0
10	63	19	0	7	190	0	70	0	133	0
10	9	22	0	4	220	0	40	0	88	0
10	0	8	0	3	80	0	30	0	24	0
9	58	31	0	46	279	0	414	0	1426	0
8	18	9	0	31	72	0	248	0	279	0
8	42	18	0	21	144	0	168	0	378	0
7	26	9	0	7	63	0	49	0	63	0
7	38	5	0	29	35	0	203	0	145	0
4	1	11	0	5	44	0	20	0	55	0

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 16 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195409&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]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195409&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195409&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
lfm[t] = -16.7481552009584 + 2.12778266408604hours[t] + 0.97740870425418blogs[t] + 48.9800609357086uk[t] + 1.33200224031743spr[t] -0.0174452199791463hours_blogs[t] -0.429689693224509hours_uk[t] -0.0212534366522236hours_spr[t] + 0.0454815184847064blogs_uk[t] -0.00607294105128763blogs_spr[t] -0.188076034336289uk_spr[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
lfm[t] =  -16.7481552009584 +  2.12778266408604hours[t] +  0.97740870425418blogs[t] +  48.9800609357086uk[t] +  1.33200224031743spr[t] -0.0174452199791463hours_blogs[t] -0.429689693224509hours_uk[t] -0.0212534366522236hours_spr[t] +  0.0454815184847064blogs_uk[t] -0.00607294105128763blogs_spr[t] -0.188076034336289uk_spr[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195409&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]lfm[t] =  -16.7481552009584 +  2.12778266408604hours[t] +  0.97740870425418blogs[t] +  48.9800609357086uk[t] +  1.33200224031743spr[t] -0.0174452199791463hours_blogs[t] -0.429689693224509hours_uk[t] -0.0212534366522236hours_spr[t] +  0.0454815184847064blogs_uk[t] -0.00607294105128763blogs_spr[t] -0.188076034336289uk_spr[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195409&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195409&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Estimated Regression Equation
lfm[t] = -16.7481552009584 + 2.12778266408604hours[t] + 0.97740870425418blogs[t] + 48.9800609357086uk[t] + 1.33200224031743spr[t] -0.0174452199791463hours_blogs[t] -0.429689693224509hours_uk[t] -0.0212534366522236hours_spr[t] + 0.0454815184847064blogs_uk[t] -0.00607294105128763blogs_spr[t] -0.188076034336289uk_spr[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-16.74815520095848.366498-2.00180.0463520.023176
hours2.127782664086040.2837997.497500
blogs0.977408704254180.1418946.888300
uk48.98006093570868.4938515.766500
spr1.332002240317430.4765342.79520.0055770.002788
hours_blogs-0.01744521997914630.002454-7.108200
hours_uk-0.4296896932245090.255939-1.67890.0943870.047193
hours_spr-0.02125343665222360.016642-1.27710.2027040.101352
blogs_uk0.04548151848470640.224230.20280.8394240.419712
blogs_spr-0.006072941051287630.013208-0.45980.646050.323025
uk_spr-0.1880760343362890.626052-0.30040.7641020.382051

\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) & -16.7481552009584 & 8.366498 & -2.0018 & 0.046352 & 0.023176 \tabularnewline
hours & 2.12778266408604 & 0.283799 & 7.4975 & 0 & 0 \tabularnewline
blogs & 0.97740870425418 & 0.141894 & 6.8883 & 0 & 0 \tabularnewline
uk & 48.9800609357086 & 8.493851 & 5.7665 & 0 & 0 \tabularnewline
spr & 1.33200224031743 & 0.476534 & 2.7952 & 0.005577 & 0.002788 \tabularnewline
hours_blogs & -0.0174452199791463 & 0.002454 & -7.1082 & 0 & 0 \tabularnewline
hours_uk & -0.429689693224509 & 0.255939 & -1.6789 & 0.094387 & 0.047193 \tabularnewline
hours_spr & -0.0212534366522236 & 0.016642 & -1.2771 & 0.202704 & 0.101352 \tabularnewline
blogs_uk & 0.0454815184847064 & 0.22423 & 0.2028 & 0.839424 & 0.419712 \tabularnewline
blogs_spr & -0.00607294105128763 & 0.013208 & -0.4598 & 0.64605 & 0.323025 \tabularnewline
uk_spr & -0.188076034336289 & 0.626052 & -0.3004 & 0.764102 & 0.382051 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195409&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]-16.7481552009584[/C][C]8.366498[/C][C]-2.0018[/C][C]0.046352[/C][C]0.023176[/C][/ROW]
[ROW][C]hours[/C][C]2.12778266408604[/C][C]0.283799[/C][C]7.4975[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]blogs[/C][C]0.97740870425418[/C][C]0.141894[/C][C]6.8883[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]uk[/C][C]48.9800609357086[/C][C]8.493851[/C][C]5.7665[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]spr[/C][C]1.33200224031743[/C][C]0.476534[/C][C]2.7952[/C][C]0.005577[/C][C]0.002788[/C][/ROW]
[ROW][C]hours_blogs[/C][C]-0.0174452199791463[/C][C]0.002454[/C][C]-7.1082[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]hours_uk[/C][C]-0.429689693224509[/C][C]0.255939[/C][C]-1.6789[/C][C]0.094387[/C][C]0.047193[/C][/ROW]
[ROW][C]hours_spr[/C][C]-0.0212534366522236[/C][C]0.016642[/C][C]-1.2771[/C][C]0.202704[/C][C]0.101352[/C][/ROW]
[ROW][C]blogs_uk[/C][C]0.0454815184847064[/C][C]0.22423[/C][C]0.2028[/C][C]0.839424[/C][C]0.419712[/C][/ROW]
[ROW][C]blogs_spr[/C][C]-0.00607294105128763[/C][C]0.013208[/C][C]-0.4598[/C][C]0.64605[/C][C]0.323025[/C][/ROW]
[ROW][C]uk_spr[/C][C]-0.188076034336289[/C][C]0.626052[/C][C]-0.3004[/C][C]0.764102[/C][C]0.382051[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195409&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195409&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-16.74815520095848.366498-2.00180.0463520.023176
hours2.127782664086040.2837997.497500
blogs0.977408704254180.1418946.888300
uk48.98006093570868.4938515.766500
spr1.332002240317430.4765342.79520.0055770.002788
hours_blogs-0.01744521997914630.002454-7.108200
hours_uk-0.4296896932245090.255939-1.67890.0943870.047193
hours_spr-0.02125343665222360.016642-1.27710.2027040.101352
blogs_uk0.04548151848470640.224230.20280.8394240.419712
blogs_spr-0.006072941051287630.013208-0.45980.646050.323025
uk_spr-0.1880760343362890.626052-0.30040.7641020.382051






Multiple Linear Regression - Regression Statistics
Multiple R0.768464601401128
R-squared0.590537843606595
Adjusted R-squared0.574667217389796
F-TEST (value)37.2094859736237
F-TEST (DF numerator)10
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation23.3788437917057
Sum Squared Residuals141015.14695554

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.768464601401128 \tabularnewline
R-squared & 0.590537843606595 \tabularnewline
Adjusted R-squared & 0.574667217389796 \tabularnewline
F-TEST (value) & 37.2094859736237 \tabularnewline
F-TEST (DF numerator) & 10 \tabularnewline
F-TEST (DF denominator) & 258 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 23.3788437917057 \tabularnewline
Sum Squared Residuals & 141015.14695554 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195409&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.768464601401128[/C][/ROW]
[ROW][C]R-squared[/C][C]0.590537843606595[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.574667217389796[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]37.2094859736237[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]10[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]258[/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]23.3788437917057[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]141015.14695554[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195409&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195409&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Regression Statistics
Multiple R0.768464601401128
R-squared0.590537843606595
Adjusted R-squared0.574667217389796
F-TEST (value)37.2094859736237
F-TEST (DF numerator)10
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation23.3788437917057
Sum Squared Residuals141015.14695554






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1122124.8383455253-2.83834552530045
2114120.887647677126-6.887647677126
3140147.410669795888-7.41066979588818
4143121.439091321921.5609086780997
5122136.716397263265-14.7163972632652
6127135.973106587513-8.97310658751316
7113134.385691144526-21.3856911445255
8118130.925154670032-12.9251546700316
9161131.75520647176529.2447935282351
10134130.7655795950573.23442040494347
1196131.237383850366-35.2373838503656
12104131.17923791625-27.17923791625
13135129.3662206452765.63377935472397
14110127.418804670096-17.4188046700955
15128126.4228288700011.57717112999889
16142127.25072686824814.7492731317525
17117125.646454489643-8.64645448964264
1894122.250545875567-28.2505458755674
19135123.1533965621911.8466034378102
20121125.281508652604-4.28150865260396
21103122.529472807331-19.529472807331
22118127.787067411171-9.78706741117095
23127123.0739646249283.92603537507181
24116126.684206320385-10.6842063203854
25129123.7517621332335.24823786676692
26115123.249616497803-8.24961649780304
27135123.18140920438811.818590795612
28133119.46527897487913.5347210251209
29113121.305588221325-8.30558822132505
30111122.445711817567-11.4457118175666
3192121.714622443479-29.7146224434795
32118120.952550781532-2.95255078153195
33134122.16569846479811.8343015352023
34106120.58069998298-14.5806999829804
35137119.53156961801417.4684303819859
36100118.365845147874-18.3658451478739
37102114.449691327083-12.4496913270826
38134119.58653317078214.4134668292178
39130115.22636365181414.7736363481858
40144115.45651468959428.5434853104061
41120114.395209095445.60479090455954
4291111.005501781914-20.0055017819143
43100111.823529359548-11.8235293595475
44134120.77679036127113.2232096387294
45161118.07824793943642.9217520605639
46128112.80093176519415.1990682348061
47124118.5278029194135.47219708058651
48115116.235261551963-1.2352615519625
49123116.7526198582626.2473801417383
50117114.3791641424622.62083585753837
51111115.731176187033-4.73117618703293
52146111.77718180355934.2228181964409
53101116.993846010685-15.993846010685
54131117.50512098089113.4948790191087
55122113.4641080991778.53589190082296
5678116.97184181591-38.9718418159103
57120110.6462483831279.35375161687267
58115115.947679151226-0.947679151226183
59142112.53886535130129.4611346486994
6094114.053030274241-20.0530302742408
61114108.8121123980275.18788760197259
62108106.9288949963491.07110500365137
63119103.74180890763515.2581910923653
64117106.84507107729910.1549289227009
6586110.470923332013-24.4709233320128
66138110.99340769884927.0065923011507
67119111.8076908381617.19230916183862
68117103.75549816535913.2445018346412
69117104.81161419316312.1883858068374
7076105.468890352662-29.4688903526623
71119112.1514620336156.84853796638514
72119103.7529737915715.2470262084305
73124105.81930391174318.1806960882571
7411697.337241066948418.6627589330516
75118102.43092421155915.569075788441
76102105.818807803554-3.81880780355419
77116102.56343214884613.4365678511536
78103113.714498835815-10.7144988358147
7911799.781377935910117.2186220640899
80108106.1197894302121.88021056978846
8112297.20784898531624.792151014684
8290103.508492346716-13.5084923467156
83133109.03346728796623.966532712034
8411689.02755410574926.9724458942509
8511098.825962781883511.1740372181165
869092.4950325527221-2.49503255272208
877495.266529541419-21.266529541419
887588.0130569535342-13.0130569535342
8910796.42093237903810.579067620962
9090105.566932354856-15.5669323548558
919695.28385057882530.716149421174753
9211588.365348976377126.6346510236229
939187.27912383309213.72087616690787
9477104.971069465181-27.9710694651807
95108108.064837760832-0.064837760832324
968392.1023753862357-9.10237538623572
977791.1195227024038-14.1195227024038
989999.988804571835-0.98880457183501
9911591.005036328011323.9949636719887
1009992.88588483129666.1141151687034
10110687.140916893695718.8590831063043
1027783.2679218577848-6.26792185778482
10311581.345228996020833.6547710039792
1046778.8338248695484-11.8338248695484
105874.1273159326875-66.1273159326875
1066983.8034081554609-14.8034081554609
1078883.27421406638334.72578593361671
10810771.981573340055835.0184266599442
10912078.402191320400841.5978086795992
110353.07535790768-50.07535790768
111151.4927006048578-50.4927006048578
112044.4856366272215-44.4856366272215
113111110.9663560732910.0336439267088813
1146974.0427554882401-5.04275548824014
115116106.1335207155889.8664792844122
116103133.545640565838-30.5456405658383
117139108.48940469204830.5105953079516
118135102.00698619915132.9930138008486
119113108.0619215205884.93807847941153
12099116.486826192967-17.4868261929673
12176105.168368167226-29.1683681672255
122110107.427341196692.57265880330962
123121105.0812972678115.9187027321902
12495102.44642428387-7.44642428386954
12566103.009749480825-37.0097494808254
12611198.819724467070812.1802755329292
12777101.857269275986-24.8572692759855
128101100.1646984426180.835301557381773
12910899.2604737313458.73952626865497
13013597.897336961763837.1026630382362
1317098.3412120095518-28.3412120095518
13212495.925488801471628.0745111985284
1339296.4937418387445-4.49374183874445
13410497.22773172985646.77226827014359
13511395.660979521114917.3390204788851
1369596.9768117774485-1.97681177744849
1378993.7802133527488-4.78021335274883
1388392.6924338679373-9.69243386793731
1399690.76775592069485.23224407930519
14095101.178546088239-6.17854608823875
14111095.445840687240914.5541593127591
14210696.5373937994359.46260620056502
1437885.179563510695-7.17956351069502
14411591.860049646973623.1399503530264
1457489.3692470207411-15.3692470207411
1469392.36194060105350.638059398946499
1478888.1913211066815-0.191321106681506
14810495.60694790301458.39305209698555
1498688.7043425142151-2.7043425142151
15010484.697418277111619.3025817228884
1519987.140947757686911.8590522423131
15210187.262564464992213.7374355350078
1535385.9768099979711-32.9768099979711
1549687.06782344142048.9321765585796
1555881.4072121248063-23.4072121248063
15611787.820217068819429.1797829311806
1578288.431590245732-6.43159024573202
1585790.6187541773057-33.6187541773057
1597183.7532638123682-12.7532638123682
16010587.099370445028817.9006295549712
1616088.6638737224037-28.6638737224037
1627784.9134852185475-7.91348521854753
1637372.45595344585660.544046554143391
1647876.46919232215481.53080767784523
1658190.9445935910825-9.94459359108251
16610176.786106513799624.2138934862004
16711883.741474573725434.2585254262747
1685980.6496089750751-21.6496089750751
16910179.100694539755121.8993054602449
1702286.38980340748-64.38980340748
1717773.1433249334383.85667506656197
17210077.964814551522322.0351854484777
1733980.4050648243337-41.4050648243337
1744270.6007784739723-28.6007784739723
1758081.792641364566-1.79264136456598
1764871.0791094171043-23.0791094171043
17713186.708803705139944.2911962948601
1784680.4859128743811-34.4859128743811
1798973.001479808533615.9985201914663
1805164.0489016615695-13.0489016615695
18110883.355915596822824.6440844031772
1828677.50443483907778.49556516092232
18310581.231525272356323.7684747276437
1848582.41095568866132.58904431133871
18510375.206590249274527.7934097507255
1868378.50320057566794.49679942433205
1877771.82815846096085.17184153903918
1882672.4502832314593-46.4502832314593
1897374.0057205665475-1.00572056654746
1904263.0381984608813-21.0381984608813
1917170.06000727660960.939992723390415
19210591.48890189730313.511098102697
1937360.302130616713612.6978693832864
1949878.022000485511919.9779995144881
19510877.782924930952330.2170750690477
1965780.2973535559315-23.2973535559315
1973774.1214968814965-37.1214968814965
1987071.3331763844828-1.33317638448277
1997364.32985296673438.67014703326569
2004764.8574030469924-17.8574030469924
2017371.87172957161691.12827042838314
2029173.754624458353717.2453755416463
20311088.913283218447521.0867167815525
2047875.07085457197952.92914542802055
2059285.19669350691696.80330649308309
2065284.4708151228731-32.4708151228731
2078868.667071526643319.3329284733567
20810056.215484117421443.7845158825786
2093356.5864717382755-23.5864717382755
2104273.6624837325556-31.6624837325556
2118175.8381275371665.16187246283396
2126774.5894285804791-7.58942858047907
213854.667764023717-46.667764023717
2144652.4590214655222-6.45902146552217
2158374.35662046630668.64337953369341
2168759.485581286332627.5144187136674
2178279.29197730262532.70802269737473
2186363.871179068837-0.871179068836997
2192765.3967541283378-38.3967541283378
2201454.8912582437751-40.8912582437751
2218358.984466071844424.0155339281556
22216857.0383585281675110.961641471832
2236761.09480653713845.90519346286156
2242157.6386140834323-36.6386140834323
2255576.0086524618859-21.0086524618859
2265475.8505511408782-21.8505511408782
22711865.40280757324652.597192426754
2286949.61426903018119.385730969819
2297743.407095720987233.5929042790128
2307270.90545874131131.09454125868868
2315347.19184827978155.80815172021846
2324052.6016245648619-12.6016245648619
23310253.747632142214248.2523678577858
2342570.1149045783677-45.1149045783677
2353150.4985759372074-19.4985759372074
2367750.95855442939326.041445570607
2373862.6417039855273-24.6417039855273
2382363.4089848417581-40.4089848417581
2399154.994180554373236.0058194456268
2405856.37038942142921.62961057857084
2414249.7212461122824-7.72124611228238
2424454.7484313744222-10.7484313744222
2435845.045883381544512.9541166184555
2443547.8221559941631-12.8221559941631
2458839.409959844236748.5900401557633
2462562.6556594764355-37.6556594764355
2473948.9746259918667-9.97462599186671
2484840.45711252650357.54288747349654
2496440.13597221066123.864027789339
2506546.763904768722418.2360952312776
2519545.969791293335649.0302087066644
2522941.0206155229716-12.0206155229716
253240.1531654176684-38.1531654176684
2548345.115041671920837.8849583280792
2551147.957142338546-36.957142338546
2561634.5873987220753-18.5873987220753
257927.2247924757233-18.2247924757233
2584638.24553488185017.75446511814985
2594140.64379586860530.356204131394733
2601425.0810827940745-11.0810827940745
2616326.814418981438736.1855810185613
262926.1381672207492-17.1381672207492
263014.1659765117584-14.1659765117584
2645871.6475085749587-13.6475085749587
2651842.1415952182986-24.1415952182986
2664237.46124908301384.5387509169862
2672613.743954927277212.2560450727228
2683835.8558251460122.14417485398801
26917.64781223382116-6.64781223382116

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 122 & 124.8383455253 & -2.83834552530045 \tabularnewline
2 & 114 & 120.887647677126 & -6.887647677126 \tabularnewline
3 & 140 & 147.410669795888 & -7.41066979588818 \tabularnewline
4 & 143 & 121.4390913219 & 21.5609086780997 \tabularnewline
5 & 122 & 136.716397263265 & -14.7163972632652 \tabularnewline
6 & 127 & 135.973106587513 & -8.97310658751316 \tabularnewline
7 & 113 & 134.385691144526 & -21.3856911445255 \tabularnewline
8 & 118 & 130.925154670032 & -12.9251546700316 \tabularnewline
9 & 161 & 131.755206471765 & 29.2447935282351 \tabularnewline
10 & 134 & 130.765579595057 & 3.23442040494347 \tabularnewline
11 & 96 & 131.237383850366 & -35.2373838503656 \tabularnewline
12 & 104 & 131.17923791625 & -27.17923791625 \tabularnewline
13 & 135 & 129.366220645276 & 5.63377935472397 \tabularnewline
14 & 110 & 127.418804670096 & -17.4188046700955 \tabularnewline
15 & 128 & 126.422828870001 & 1.57717112999889 \tabularnewline
16 & 142 & 127.250726868248 & 14.7492731317525 \tabularnewline
17 & 117 & 125.646454489643 & -8.64645448964264 \tabularnewline
18 & 94 & 122.250545875567 & -28.2505458755674 \tabularnewline
19 & 135 & 123.15339656219 & 11.8466034378102 \tabularnewline
20 & 121 & 125.281508652604 & -4.28150865260396 \tabularnewline
21 & 103 & 122.529472807331 & -19.529472807331 \tabularnewline
22 & 118 & 127.787067411171 & -9.78706741117095 \tabularnewline
23 & 127 & 123.073964624928 & 3.92603537507181 \tabularnewline
24 & 116 & 126.684206320385 & -10.6842063203854 \tabularnewline
25 & 129 & 123.751762133233 & 5.24823786676692 \tabularnewline
26 & 115 & 123.249616497803 & -8.24961649780304 \tabularnewline
27 & 135 & 123.181409204388 & 11.818590795612 \tabularnewline
28 & 133 & 119.465278974879 & 13.5347210251209 \tabularnewline
29 & 113 & 121.305588221325 & -8.30558822132505 \tabularnewline
30 & 111 & 122.445711817567 & -11.4457118175666 \tabularnewline
31 & 92 & 121.714622443479 & -29.7146224434795 \tabularnewline
32 & 118 & 120.952550781532 & -2.95255078153195 \tabularnewline
33 & 134 & 122.165698464798 & 11.8343015352023 \tabularnewline
34 & 106 & 120.58069998298 & -14.5806999829804 \tabularnewline
35 & 137 & 119.531569618014 & 17.4684303819859 \tabularnewline
36 & 100 & 118.365845147874 & -18.3658451478739 \tabularnewline
37 & 102 & 114.449691327083 & -12.4496913270826 \tabularnewline
38 & 134 & 119.586533170782 & 14.4134668292178 \tabularnewline
39 & 130 & 115.226363651814 & 14.7736363481858 \tabularnewline
40 & 144 & 115.456514689594 & 28.5434853104061 \tabularnewline
41 & 120 & 114.39520909544 & 5.60479090455954 \tabularnewline
42 & 91 & 111.005501781914 & -20.0055017819143 \tabularnewline
43 & 100 & 111.823529359548 & -11.8235293595475 \tabularnewline
44 & 134 & 120.776790361271 & 13.2232096387294 \tabularnewline
45 & 161 & 118.078247939436 & 42.9217520605639 \tabularnewline
46 & 128 & 112.800931765194 & 15.1990682348061 \tabularnewline
47 & 124 & 118.527802919413 & 5.47219708058651 \tabularnewline
48 & 115 & 116.235261551963 & -1.2352615519625 \tabularnewline
49 & 123 & 116.752619858262 & 6.2473801417383 \tabularnewline
50 & 117 & 114.379164142462 & 2.62083585753837 \tabularnewline
51 & 111 & 115.731176187033 & -4.73117618703293 \tabularnewline
52 & 146 & 111.777181803559 & 34.2228181964409 \tabularnewline
53 & 101 & 116.993846010685 & -15.993846010685 \tabularnewline
54 & 131 & 117.505120980891 & 13.4948790191087 \tabularnewline
55 & 122 & 113.464108099177 & 8.53589190082296 \tabularnewline
56 & 78 & 116.97184181591 & -38.9718418159103 \tabularnewline
57 & 120 & 110.646248383127 & 9.35375161687267 \tabularnewline
58 & 115 & 115.947679151226 & -0.947679151226183 \tabularnewline
59 & 142 & 112.538865351301 & 29.4611346486994 \tabularnewline
60 & 94 & 114.053030274241 & -20.0530302742408 \tabularnewline
61 & 114 & 108.812112398027 & 5.18788760197259 \tabularnewline
62 & 108 & 106.928894996349 & 1.07110500365137 \tabularnewline
63 & 119 & 103.741808907635 & 15.2581910923653 \tabularnewline
64 & 117 & 106.845071077299 & 10.1549289227009 \tabularnewline
65 & 86 & 110.470923332013 & -24.4709233320128 \tabularnewline
66 & 138 & 110.993407698849 & 27.0065923011507 \tabularnewline
67 & 119 & 111.807690838161 & 7.19230916183862 \tabularnewline
68 & 117 & 103.755498165359 & 13.2445018346412 \tabularnewline
69 & 117 & 104.811614193163 & 12.1883858068374 \tabularnewline
70 & 76 & 105.468890352662 & -29.4688903526623 \tabularnewline
71 & 119 & 112.151462033615 & 6.84853796638514 \tabularnewline
72 & 119 & 103.75297379157 & 15.2470262084305 \tabularnewline
73 & 124 & 105.819303911743 & 18.1806960882571 \tabularnewline
74 & 116 & 97.3372410669484 & 18.6627589330516 \tabularnewline
75 & 118 & 102.430924211559 & 15.569075788441 \tabularnewline
76 & 102 & 105.818807803554 & -3.81880780355419 \tabularnewline
77 & 116 & 102.563432148846 & 13.4365678511536 \tabularnewline
78 & 103 & 113.714498835815 & -10.7144988358147 \tabularnewline
79 & 117 & 99.7813779359101 & 17.2186220640899 \tabularnewline
80 & 108 & 106.119789430212 & 1.88021056978846 \tabularnewline
81 & 122 & 97.207848985316 & 24.792151014684 \tabularnewline
82 & 90 & 103.508492346716 & -13.5084923467156 \tabularnewline
83 & 133 & 109.033467287966 & 23.966532712034 \tabularnewline
84 & 116 & 89.027554105749 & 26.9724458942509 \tabularnewline
85 & 110 & 98.8259627818835 & 11.1740372181165 \tabularnewline
86 & 90 & 92.4950325527221 & -2.49503255272208 \tabularnewline
87 & 74 & 95.266529541419 & -21.266529541419 \tabularnewline
88 & 75 & 88.0130569535342 & -13.0130569535342 \tabularnewline
89 & 107 & 96.420932379038 & 10.579067620962 \tabularnewline
90 & 90 & 105.566932354856 & -15.5669323548558 \tabularnewline
91 & 96 & 95.2838505788253 & 0.716149421174753 \tabularnewline
92 & 115 & 88.3653489763771 & 26.6346510236229 \tabularnewline
93 & 91 & 87.2791238330921 & 3.72087616690787 \tabularnewline
94 & 77 & 104.971069465181 & -27.9710694651807 \tabularnewline
95 & 108 & 108.064837760832 & -0.064837760832324 \tabularnewline
96 & 83 & 92.1023753862357 & -9.10237538623572 \tabularnewline
97 & 77 & 91.1195227024038 & -14.1195227024038 \tabularnewline
98 & 99 & 99.988804571835 & -0.98880457183501 \tabularnewline
99 & 115 & 91.0050363280113 & 23.9949636719887 \tabularnewline
100 & 99 & 92.8858848312966 & 6.1141151687034 \tabularnewline
101 & 106 & 87.1409168936957 & 18.8590831063043 \tabularnewline
102 & 77 & 83.2679218577848 & -6.26792185778482 \tabularnewline
103 & 115 & 81.3452289960208 & 33.6547710039792 \tabularnewline
104 & 67 & 78.8338248695484 & -11.8338248695484 \tabularnewline
105 & 8 & 74.1273159326875 & -66.1273159326875 \tabularnewline
106 & 69 & 83.8034081554609 & -14.8034081554609 \tabularnewline
107 & 88 & 83.2742140663833 & 4.72578593361671 \tabularnewline
108 & 107 & 71.9815733400558 & 35.0184266599442 \tabularnewline
109 & 120 & 78.4021913204008 & 41.5978086795992 \tabularnewline
110 & 3 & 53.07535790768 & -50.07535790768 \tabularnewline
111 & 1 & 51.4927006048578 & -50.4927006048578 \tabularnewline
112 & 0 & 44.4856366272215 & -44.4856366272215 \tabularnewline
113 & 111 & 110.966356073291 & 0.0336439267088813 \tabularnewline
114 & 69 & 74.0427554882401 & -5.04275548824014 \tabularnewline
115 & 116 & 106.133520715588 & 9.8664792844122 \tabularnewline
116 & 103 & 133.545640565838 & -30.5456405658383 \tabularnewline
117 & 139 & 108.489404692048 & 30.5105953079516 \tabularnewline
118 & 135 & 102.006986199151 & 32.9930138008486 \tabularnewline
119 & 113 & 108.061921520588 & 4.93807847941153 \tabularnewline
120 & 99 & 116.486826192967 & -17.4868261929673 \tabularnewline
121 & 76 & 105.168368167226 & -29.1683681672255 \tabularnewline
122 & 110 & 107.42734119669 & 2.57265880330962 \tabularnewline
123 & 121 & 105.08129726781 & 15.9187027321902 \tabularnewline
124 & 95 & 102.44642428387 & -7.44642428386954 \tabularnewline
125 & 66 & 103.009749480825 & -37.0097494808254 \tabularnewline
126 & 111 & 98.8197244670708 & 12.1802755329292 \tabularnewline
127 & 77 & 101.857269275986 & -24.8572692759855 \tabularnewline
128 & 101 & 100.164698442618 & 0.835301557381773 \tabularnewline
129 & 108 & 99.260473731345 & 8.73952626865497 \tabularnewline
130 & 135 & 97.8973369617638 & 37.1026630382362 \tabularnewline
131 & 70 & 98.3412120095518 & -28.3412120095518 \tabularnewline
132 & 124 & 95.9254888014716 & 28.0745111985284 \tabularnewline
133 & 92 & 96.4937418387445 & -4.49374183874445 \tabularnewline
134 & 104 & 97.2277317298564 & 6.77226827014359 \tabularnewline
135 & 113 & 95.6609795211149 & 17.3390204788851 \tabularnewline
136 & 95 & 96.9768117774485 & -1.97681177744849 \tabularnewline
137 & 89 & 93.7802133527488 & -4.78021335274883 \tabularnewline
138 & 83 & 92.6924338679373 & -9.69243386793731 \tabularnewline
139 & 96 & 90.7677559206948 & 5.23224407930519 \tabularnewline
140 & 95 & 101.178546088239 & -6.17854608823875 \tabularnewline
141 & 110 & 95.4458406872409 & 14.5541593127591 \tabularnewline
142 & 106 & 96.537393799435 & 9.46260620056502 \tabularnewline
143 & 78 & 85.179563510695 & -7.17956351069502 \tabularnewline
144 & 115 & 91.8600496469736 & 23.1399503530264 \tabularnewline
145 & 74 & 89.3692470207411 & -15.3692470207411 \tabularnewline
146 & 93 & 92.3619406010535 & 0.638059398946499 \tabularnewline
147 & 88 & 88.1913211066815 & -0.191321106681506 \tabularnewline
148 & 104 & 95.6069479030145 & 8.39305209698555 \tabularnewline
149 & 86 & 88.7043425142151 & -2.7043425142151 \tabularnewline
150 & 104 & 84.6974182771116 & 19.3025817228884 \tabularnewline
151 & 99 & 87.1409477576869 & 11.8590522423131 \tabularnewline
152 & 101 & 87.2625644649922 & 13.7374355350078 \tabularnewline
153 & 53 & 85.9768099979711 & -32.9768099979711 \tabularnewline
154 & 96 & 87.0678234414204 & 8.9321765585796 \tabularnewline
155 & 58 & 81.4072121248063 & -23.4072121248063 \tabularnewline
156 & 117 & 87.8202170688194 & 29.1797829311806 \tabularnewline
157 & 82 & 88.431590245732 & -6.43159024573202 \tabularnewline
158 & 57 & 90.6187541773057 & -33.6187541773057 \tabularnewline
159 & 71 & 83.7532638123682 & -12.7532638123682 \tabularnewline
160 & 105 & 87.0993704450288 & 17.9006295549712 \tabularnewline
161 & 60 & 88.6638737224037 & -28.6638737224037 \tabularnewline
162 & 77 & 84.9134852185475 & -7.91348521854753 \tabularnewline
163 & 73 & 72.4559534458566 & 0.544046554143391 \tabularnewline
164 & 78 & 76.4691923221548 & 1.53080767784523 \tabularnewline
165 & 81 & 90.9445935910825 & -9.94459359108251 \tabularnewline
166 & 101 & 76.7861065137996 & 24.2138934862004 \tabularnewline
167 & 118 & 83.7414745737254 & 34.2585254262747 \tabularnewline
168 & 59 & 80.6496089750751 & -21.6496089750751 \tabularnewline
169 & 101 & 79.1006945397551 & 21.8993054602449 \tabularnewline
170 & 22 & 86.38980340748 & -64.38980340748 \tabularnewline
171 & 77 & 73.143324933438 & 3.85667506656197 \tabularnewline
172 & 100 & 77.9648145515223 & 22.0351854484777 \tabularnewline
173 & 39 & 80.4050648243337 & -41.4050648243337 \tabularnewline
174 & 42 & 70.6007784739723 & -28.6007784739723 \tabularnewline
175 & 80 & 81.792641364566 & -1.79264136456598 \tabularnewline
176 & 48 & 71.0791094171043 & -23.0791094171043 \tabularnewline
177 & 131 & 86.7088037051399 & 44.2911962948601 \tabularnewline
178 & 46 & 80.4859128743811 & -34.4859128743811 \tabularnewline
179 & 89 & 73.0014798085336 & 15.9985201914663 \tabularnewline
180 & 51 & 64.0489016615695 & -13.0489016615695 \tabularnewline
181 & 108 & 83.3559155968228 & 24.6440844031772 \tabularnewline
182 & 86 & 77.5044348390777 & 8.49556516092232 \tabularnewline
183 & 105 & 81.2315252723563 & 23.7684747276437 \tabularnewline
184 & 85 & 82.4109556886613 & 2.58904431133871 \tabularnewline
185 & 103 & 75.2065902492745 & 27.7934097507255 \tabularnewline
186 & 83 & 78.5032005756679 & 4.49679942433205 \tabularnewline
187 & 77 & 71.8281584609608 & 5.17184153903918 \tabularnewline
188 & 26 & 72.4502832314593 & -46.4502832314593 \tabularnewline
189 & 73 & 74.0057205665475 & -1.00572056654746 \tabularnewline
190 & 42 & 63.0381984608813 & -21.0381984608813 \tabularnewline
191 & 71 & 70.0600072766096 & 0.939992723390415 \tabularnewline
192 & 105 & 91.488901897303 & 13.511098102697 \tabularnewline
193 & 73 & 60.3021306167136 & 12.6978693832864 \tabularnewline
194 & 98 & 78.0220004855119 & 19.9779995144881 \tabularnewline
195 & 108 & 77.7829249309523 & 30.2170750690477 \tabularnewline
196 & 57 & 80.2973535559315 & -23.2973535559315 \tabularnewline
197 & 37 & 74.1214968814965 & -37.1214968814965 \tabularnewline
198 & 70 & 71.3331763844828 & -1.33317638448277 \tabularnewline
199 & 73 & 64.3298529667343 & 8.67014703326569 \tabularnewline
200 & 47 & 64.8574030469924 & -17.8574030469924 \tabularnewline
201 & 73 & 71.8717295716169 & 1.12827042838314 \tabularnewline
202 & 91 & 73.7546244583537 & 17.2453755416463 \tabularnewline
203 & 110 & 88.9132832184475 & 21.0867167815525 \tabularnewline
204 & 78 & 75.0708545719795 & 2.92914542802055 \tabularnewline
205 & 92 & 85.1966935069169 & 6.80330649308309 \tabularnewline
206 & 52 & 84.4708151228731 & -32.4708151228731 \tabularnewline
207 & 88 & 68.6670715266433 & 19.3329284733567 \tabularnewline
208 & 100 & 56.2154841174214 & 43.7845158825786 \tabularnewline
209 & 33 & 56.5864717382755 & -23.5864717382755 \tabularnewline
210 & 42 & 73.6624837325556 & -31.6624837325556 \tabularnewline
211 & 81 & 75.838127537166 & 5.16187246283396 \tabularnewline
212 & 67 & 74.5894285804791 & -7.58942858047907 \tabularnewline
213 & 8 & 54.667764023717 & -46.667764023717 \tabularnewline
214 & 46 & 52.4590214655222 & -6.45902146552217 \tabularnewline
215 & 83 & 74.3566204663066 & 8.64337953369341 \tabularnewline
216 & 87 & 59.4855812863326 & 27.5144187136674 \tabularnewline
217 & 82 & 79.2919773026253 & 2.70802269737473 \tabularnewline
218 & 63 & 63.871179068837 & -0.871179068836997 \tabularnewline
219 & 27 & 65.3967541283378 & -38.3967541283378 \tabularnewline
220 & 14 & 54.8912582437751 & -40.8912582437751 \tabularnewline
221 & 83 & 58.9844660718444 & 24.0155339281556 \tabularnewline
222 & 168 & 57.0383585281675 & 110.961641471832 \tabularnewline
223 & 67 & 61.0948065371384 & 5.90519346286156 \tabularnewline
224 & 21 & 57.6386140834323 & -36.6386140834323 \tabularnewline
225 & 55 & 76.0086524618859 & -21.0086524618859 \tabularnewline
226 & 54 & 75.8505511408782 & -21.8505511408782 \tabularnewline
227 & 118 & 65.402807573246 & 52.597192426754 \tabularnewline
228 & 69 & 49.614269030181 & 19.385730969819 \tabularnewline
229 & 77 & 43.4070957209872 & 33.5929042790128 \tabularnewline
230 & 72 & 70.9054587413113 & 1.09454125868868 \tabularnewline
231 & 53 & 47.1918482797815 & 5.80815172021846 \tabularnewline
232 & 40 & 52.6016245648619 & -12.6016245648619 \tabularnewline
233 & 102 & 53.7476321422142 & 48.2523678577858 \tabularnewline
234 & 25 & 70.1149045783677 & -45.1149045783677 \tabularnewline
235 & 31 & 50.4985759372074 & -19.4985759372074 \tabularnewline
236 & 77 & 50.958554429393 & 26.041445570607 \tabularnewline
237 & 38 & 62.6417039855273 & -24.6417039855273 \tabularnewline
238 & 23 & 63.4089848417581 & -40.4089848417581 \tabularnewline
239 & 91 & 54.9941805543732 & 36.0058194456268 \tabularnewline
240 & 58 & 56.3703894214292 & 1.62961057857084 \tabularnewline
241 & 42 & 49.7212461122824 & -7.72124611228238 \tabularnewline
242 & 44 & 54.7484313744222 & -10.7484313744222 \tabularnewline
243 & 58 & 45.0458833815445 & 12.9541166184555 \tabularnewline
244 & 35 & 47.8221559941631 & -12.8221559941631 \tabularnewline
245 & 88 & 39.4099598442367 & 48.5900401557633 \tabularnewline
246 & 25 & 62.6556594764355 & -37.6556594764355 \tabularnewline
247 & 39 & 48.9746259918667 & -9.97462599186671 \tabularnewline
248 & 48 & 40.4571125265035 & 7.54288747349654 \tabularnewline
249 & 64 & 40.135972210661 & 23.864027789339 \tabularnewline
250 & 65 & 46.7639047687224 & 18.2360952312776 \tabularnewline
251 & 95 & 45.9697912933356 & 49.0302087066644 \tabularnewline
252 & 29 & 41.0206155229716 & -12.0206155229716 \tabularnewline
253 & 2 & 40.1531654176684 & -38.1531654176684 \tabularnewline
254 & 83 & 45.1150416719208 & 37.8849583280792 \tabularnewline
255 & 11 & 47.957142338546 & -36.957142338546 \tabularnewline
256 & 16 & 34.5873987220753 & -18.5873987220753 \tabularnewline
257 & 9 & 27.2247924757233 & -18.2247924757233 \tabularnewline
258 & 46 & 38.2455348818501 & 7.75446511814985 \tabularnewline
259 & 41 & 40.6437958686053 & 0.356204131394733 \tabularnewline
260 & 14 & 25.0810827940745 & -11.0810827940745 \tabularnewline
261 & 63 & 26.8144189814387 & 36.1855810185613 \tabularnewline
262 & 9 & 26.1381672207492 & -17.1381672207492 \tabularnewline
263 & 0 & 14.1659765117584 & -14.1659765117584 \tabularnewline
264 & 58 & 71.6475085749587 & -13.6475085749587 \tabularnewline
265 & 18 & 42.1415952182986 & -24.1415952182986 \tabularnewline
266 & 42 & 37.4612490830138 & 4.5387509169862 \tabularnewline
267 & 26 & 13.7439549272772 & 12.2560450727228 \tabularnewline
268 & 38 & 35.855825146012 & 2.14417485398801 \tabularnewline
269 & 1 & 7.64781223382116 & -6.64781223382116 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195409&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]122[/C][C]124.8383455253[/C][C]-2.83834552530045[/C][/ROW]
[ROW][C]2[/C][C]114[/C][C]120.887647677126[/C][C]-6.887647677126[/C][/ROW]
[ROW][C]3[/C][C]140[/C][C]147.410669795888[/C][C]-7.41066979588818[/C][/ROW]
[ROW][C]4[/C][C]143[/C][C]121.4390913219[/C][C]21.5609086780997[/C][/ROW]
[ROW][C]5[/C][C]122[/C][C]136.716397263265[/C][C]-14.7163972632652[/C][/ROW]
[ROW][C]6[/C][C]127[/C][C]135.973106587513[/C][C]-8.97310658751316[/C][/ROW]
[ROW][C]7[/C][C]113[/C][C]134.385691144526[/C][C]-21.3856911445255[/C][/ROW]
[ROW][C]8[/C][C]118[/C][C]130.925154670032[/C][C]-12.9251546700316[/C][/ROW]
[ROW][C]9[/C][C]161[/C][C]131.755206471765[/C][C]29.2447935282351[/C][/ROW]
[ROW][C]10[/C][C]134[/C][C]130.765579595057[/C][C]3.23442040494347[/C][/ROW]
[ROW][C]11[/C][C]96[/C][C]131.237383850366[/C][C]-35.2373838503656[/C][/ROW]
[ROW][C]12[/C][C]104[/C][C]131.17923791625[/C][C]-27.17923791625[/C][/ROW]
[ROW][C]13[/C][C]135[/C][C]129.366220645276[/C][C]5.63377935472397[/C][/ROW]
[ROW][C]14[/C][C]110[/C][C]127.418804670096[/C][C]-17.4188046700955[/C][/ROW]
[ROW][C]15[/C][C]128[/C][C]126.422828870001[/C][C]1.57717112999889[/C][/ROW]
[ROW][C]16[/C][C]142[/C][C]127.250726868248[/C][C]14.7492731317525[/C][/ROW]
[ROW][C]17[/C][C]117[/C][C]125.646454489643[/C][C]-8.64645448964264[/C][/ROW]
[ROW][C]18[/C][C]94[/C][C]122.250545875567[/C][C]-28.2505458755674[/C][/ROW]
[ROW][C]19[/C][C]135[/C][C]123.15339656219[/C][C]11.8466034378102[/C][/ROW]
[ROW][C]20[/C][C]121[/C][C]125.281508652604[/C][C]-4.28150865260396[/C][/ROW]
[ROW][C]21[/C][C]103[/C][C]122.529472807331[/C][C]-19.529472807331[/C][/ROW]
[ROW][C]22[/C][C]118[/C][C]127.787067411171[/C][C]-9.78706741117095[/C][/ROW]
[ROW][C]23[/C][C]127[/C][C]123.073964624928[/C][C]3.92603537507181[/C][/ROW]
[ROW][C]24[/C][C]116[/C][C]126.684206320385[/C][C]-10.6842063203854[/C][/ROW]
[ROW][C]25[/C][C]129[/C][C]123.751762133233[/C][C]5.24823786676692[/C][/ROW]
[ROW][C]26[/C][C]115[/C][C]123.249616497803[/C][C]-8.24961649780304[/C][/ROW]
[ROW][C]27[/C][C]135[/C][C]123.181409204388[/C][C]11.818590795612[/C][/ROW]
[ROW][C]28[/C][C]133[/C][C]119.465278974879[/C][C]13.5347210251209[/C][/ROW]
[ROW][C]29[/C][C]113[/C][C]121.305588221325[/C][C]-8.30558822132505[/C][/ROW]
[ROW][C]30[/C][C]111[/C][C]122.445711817567[/C][C]-11.4457118175666[/C][/ROW]
[ROW][C]31[/C][C]92[/C][C]121.714622443479[/C][C]-29.7146224434795[/C][/ROW]
[ROW][C]32[/C][C]118[/C][C]120.952550781532[/C][C]-2.95255078153195[/C][/ROW]
[ROW][C]33[/C][C]134[/C][C]122.165698464798[/C][C]11.8343015352023[/C][/ROW]
[ROW][C]34[/C][C]106[/C][C]120.58069998298[/C][C]-14.5806999829804[/C][/ROW]
[ROW][C]35[/C][C]137[/C][C]119.531569618014[/C][C]17.4684303819859[/C][/ROW]
[ROW][C]36[/C][C]100[/C][C]118.365845147874[/C][C]-18.3658451478739[/C][/ROW]
[ROW][C]37[/C][C]102[/C][C]114.449691327083[/C][C]-12.4496913270826[/C][/ROW]
[ROW][C]38[/C][C]134[/C][C]119.586533170782[/C][C]14.4134668292178[/C][/ROW]
[ROW][C]39[/C][C]130[/C][C]115.226363651814[/C][C]14.7736363481858[/C][/ROW]
[ROW][C]40[/C][C]144[/C][C]115.456514689594[/C][C]28.5434853104061[/C][/ROW]
[ROW][C]41[/C][C]120[/C][C]114.39520909544[/C][C]5.60479090455954[/C][/ROW]
[ROW][C]42[/C][C]91[/C][C]111.005501781914[/C][C]-20.0055017819143[/C][/ROW]
[ROW][C]43[/C][C]100[/C][C]111.823529359548[/C][C]-11.8235293595475[/C][/ROW]
[ROW][C]44[/C][C]134[/C][C]120.776790361271[/C][C]13.2232096387294[/C][/ROW]
[ROW][C]45[/C][C]161[/C][C]118.078247939436[/C][C]42.9217520605639[/C][/ROW]
[ROW][C]46[/C][C]128[/C][C]112.800931765194[/C][C]15.1990682348061[/C][/ROW]
[ROW][C]47[/C][C]124[/C][C]118.527802919413[/C][C]5.47219708058651[/C][/ROW]
[ROW][C]48[/C][C]115[/C][C]116.235261551963[/C][C]-1.2352615519625[/C][/ROW]
[ROW][C]49[/C][C]123[/C][C]116.752619858262[/C][C]6.2473801417383[/C][/ROW]
[ROW][C]50[/C][C]117[/C][C]114.379164142462[/C][C]2.62083585753837[/C][/ROW]
[ROW][C]51[/C][C]111[/C][C]115.731176187033[/C][C]-4.73117618703293[/C][/ROW]
[ROW][C]52[/C][C]146[/C][C]111.777181803559[/C][C]34.2228181964409[/C][/ROW]
[ROW][C]53[/C][C]101[/C][C]116.993846010685[/C][C]-15.993846010685[/C][/ROW]
[ROW][C]54[/C][C]131[/C][C]117.505120980891[/C][C]13.4948790191087[/C][/ROW]
[ROW][C]55[/C][C]122[/C][C]113.464108099177[/C][C]8.53589190082296[/C][/ROW]
[ROW][C]56[/C][C]78[/C][C]116.97184181591[/C][C]-38.9718418159103[/C][/ROW]
[ROW][C]57[/C][C]120[/C][C]110.646248383127[/C][C]9.35375161687267[/C][/ROW]
[ROW][C]58[/C][C]115[/C][C]115.947679151226[/C][C]-0.947679151226183[/C][/ROW]
[ROW][C]59[/C][C]142[/C][C]112.538865351301[/C][C]29.4611346486994[/C][/ROW]
[ROW][C]60[/C][C]94[/C][C]114.053030274241[/C][C]-20.0530302742408[/C][/ROW]
[ROW][C]61[/C][C]114[/C][C]108.812112398027[/C][C]5.18788760197259[/C][/ROW]
[ROW][C]62[/C][C]108[/C][C]106.928894996349[/C][C]1.07110500365137[/C][/ROW]
[ROW][C]63[/C][C]119[/C][C]103.741808907635[/C][C]15.2581910923653[/C][/ROW]
[ROW][C]64[/C][C]117[/C][C]106.845071077299[/C][C]10.1549289227009[/C][/ROW]
[ROW][C]65[/C][C]86[/C][C]110.470923332013[/C][C]-24.4709233320128[/C][/ROW]
[ROW][C]66[/C][C]138[/C][C]110.993407698849[/C][C]27.0065923011507[/C][/ROW]
[ROW][C]67[/C][C]119[/C][C]111.807690838161[/C][C]7.19230916183862[/C][/ROW]
[ROW][C]68[/C][C]117[/C][C]103.755498165359[/C][C]13.2445018346412[/C][/ROW]
[ROW][C]69[/C][C]117[/C][C]104.811614193163[/C][C]12.1883858068374[/C][/ROW]
[ROW][C]70[/C][C]76[/C][C]105.468890352662[/C][C]-29.4688903526623[/C][/ROW]
[ROW][C]71[/C][C]119[/C][C]112.151462033615[/C][C]6.84853796638514[/C][/ROW]
[ROW][C]72[/C][C]119[/C][C]103.75297379157[/C][C]15.2470262084305[/C][/ROW]
[ROW][C]73[/C][C]124[/C][C]105.819303911743[/C][C]18.1806960882571[/C][/ROW]
[ROW][C]74[/C][C]116[/C][C]97.3372410669484[/C][C]18.6627589330516[/C][/ROW]
[ROW][C]75[/C][C]118[/C][C]102.430924211559[/C][C]15.569075788441[/C][/ROW]
[ROW][C]76[/C][C]102[/C][C]105.818807803554[/C][C]-3.81880780355419[/C][/ROW]
[ROW][C]77[/C][C]116[/C][C]102.563432148846[/C][C]13.4365678511536[/C][/ROW]
[ROW][C]78[/C][C]103[/C][C]113.714498835815[/C][C]-10.7144988358147[/C][/ROW]
[ROW][C]79[/C][C]117[/C][C]99.7813779359101[/C][C]17.2186220640899[/C][/ROW]
[ROW][C]80[/C][C]108[/C][C]106.119789430212[/C][C]1.88021056978846[/C][/ROW]
[ROW][C]81[/C][C]122[/C][C]97.207848985316[/C][C]24.792151014684[/C][/ROW]
[ROW][C]82[/C][C]90[/C][C]103.508492346716[/C][C]-13.5084923467156[/C][/ROW]
[ROW][C]83[/C][C]133[/C][C]109.033467287966[/C][C]23.966532712034[/C][/ROW]
[ROW][C]84[/C][C]116[/C][C]89.027554105749[/C][C]26.9724458942509[/C][/ROW]
[ROW][C]85[/C][C]110[/C][C]98.8259627818835[/C][C]11.1740372181165[/C][/ROW]
[ROW][C]86[/C][C]90[/C][C]92.4950325527221[/C][C]-2.49503255272208[/C][/ROW]
[ROW][C]87[/C][C]74[/C][C]95.266529541419[/C][C]-21.266529541419[/C][/ROW]
[ROW][C]88[/C][C]75[/C][C]88.0130569535342[/C][C]-13.0130569535342[/C][/ROW]
[ROW][C]89[/C][C]107[/C][C]96.420932379038[/C][C]10.579067620962[/C][/ROW]
[ROW][C]90[/C][C]90[/C][C]105.566932354856[/C][C]-15.5669323548558[/C][/ROW]
[ROW][C]91[/C][C]96[/C][C]95.2838505788253[/C][C]0.716149421174753[/C][/ROW]
[ROW][C]92[/C][C]115[/C][C]88.3653489763771[/C][C]26.6346510236229[/C][/ROW]
[ROW][C]93[/C][C]91[/C][C]87.2791238330921[/C][C]3.72087616690787[/C][/ROW]
[ROW][C]94[/C][C]77[/C][C]104.971069465181[/C][C]-27.9710694651807[/C][/ROW]
[ROW][C]95[/C][C]108[/C][C]108.064837760832[/C][C]-0.064837760832324[/C][/ROW]
[ROW][C]96[/C][C]83[/C][C]92.1023753862357[/C][C]-9.10237538623572[/C][/ROW]
[ROW][C]97[/C][C]77[/C][C]91.1195227024038[/C][C]-14.1195227024038[/C][/ROW]
[ROW][C]98[/C][C]99[/C][C]99.988804571835[/C][C]-0.98880457183501[/C][/ROW]
[ROW][C]99[/C][C]115[/C][C]91.0050363280113[/C][C]23.9949636719887[/C][/ROW]
[ROW][C]100[/C][C]99[/C][C]92.8858848312966[/C][C]6.1141151687034[/C][/ROW]
[ROW][C]101[/C][C]106[/C][C]87.1409168936957[/C][C]18.8590831063043[/C][/ROW]
[ROW][C]102[/C][C]77[/C][C]83.2679218577848[/C][C]-6.26792185778482[/C][/ROW]
[ROW][C]103[/C][C]115[/C][C]81.3452289960208[/C][C]33.6547710039792[/C][/ROW]
[ROW][C]104[/C][C]67[/C][C]78.8338248695484[/C][C]-11.8338248695484[/C][/ROW]
[ROW][C]105[/C][C]8[/C][C]74.1273159326875[/C][C]-66.1273159326875[/C][/ROW]
[ROW][C]106[/C][C]69[/C][C]83.8034081554609[/C][C]-14.8034081554609[/C][/ROW]
[ROW][C]107[/C][C]88[/C][C]83.2742140663833[/C][C]4.72578593361671[/C][/ROW]
[ROW][C]108[/C][C]107[/C][C]71.9815733400558[/C][C]35.0184266599442[/C][/ROW]
[ROW][C]109[/C][C]120[/C][C]78.4021913204008[/C][C]41.5978086795992[/C][/ROW]
[ROW][C]110[/C][C]3[/C][C]53.07535790768[/C][C]-50.07535790768[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]51.4927006048578[/C][C]-50.4927006048578[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]44.4856366272215[/C][C]-44.4856366272215[/C][/ROW]
[ROW][C]113[/C][C]111[/C][C]110.966356073291[/C][C]0.0336439267088813[/C][/ROW]
[ROW][C]114[/C][C]69[/C][C]74.0427554882401[/C][C]-5.04275548824014[/C][/ROW]
[ROW][C]115[/C][C]116[/C][C]106.133520715588[/C][C]9.8664792844122[/C][/ROW]
[ROW][C]116[/C][C]103[/C][C]133.545640565838[/C][C]-30.5456405658383[/C][/ROW]
[ROW][C]117[/C][C]139[/C][C]108.489404692048[/C][C]30.5105953079516[/C][/ROW]
[ROW][C]118[/C][C]135[/C][C]102.006986199151[/C][C]32.9930138008486[/C][/ROW]
[ROW][C]119[/C][C]113[/C][C]108.061921520588[/C][C]4.93807847941153[/C][/ROW]
[ROW][C]120[/C][C]99[/C][C]116.486826192967[/C][C]-17.4868261929673[/C][/ROW]
[ROW][C]121[/C][C]76[/C][C]105.168368167226[/C][C]-29.1683681672255[/C][/ROW]
[ROW][C]122[/C][C]110[/C][C]107.42734119669[/C][C]2.57265880330962[/C][/ROW]
[ROW][C]123[/C][C]121[/C][C]105.08129726781[/C][C]15.9187027321902[/C][/ROW]
[ROW][C]124[/C][C]95[/C][C]102.44642428387[/C][C]-7.44642428386954[/C][/ROW]
[ROW][C]125[/C][C]66[/C][C]103.009749480825[/C][C]-37.0097494808254[/C][/ROW]
[ROW][C]126[/C][C]111[/C][C]98.8197244670708[/C][C]12.1802755329292[/C][/ROW]
[ROW][C]127[/C][C]77[/C][C]101.857269275986[/C][C]-24.8572692759855[/C][/ROW]
[ROW][C]128[/C][C]101[/C][C]100.164698442618[/C][C]0.835301557381773[/C][/ROW]
[ROW][C]129[/C][C]108[/C][C]99.260473731345[/C][C]8.73952626865497[/C][/ROW]
[ROW][C]130[/C][C]135[/C][C]97.8973369617638[/C][C]37.1026630382362[/C][/ROW]
[ROW][C]131[/C][C]70[/C][C]98.3412120095518[/C][C]-28.3412120095518[/C][/ROW]
[ROW][C]132[/C][C]124[/C][C]95.9254888014716[/C][C]28.0745111985284[/C][/ROW]
[ROW][C]133[/C][C]92[/C][C]96.4937418387445[/C][C]-4.49374183874445[/C][/ROW]
[ROW][C]134[/C][C]104[/C][C]97.2277317298564[/C][C]6.77226827014359[/C][/ROW]
[ROW][C]135[/C][C]113[/C][C]95.6609795211149[/C][C]17.3390204788851[/C][/ROW]
[ROW][C]136[/C][C]95[/C][C]96.9768117774485[/C][C]-1.97681177744849[/C][/ROW]
[ROW][C]137[/C][C]89[/C][C]93.7802133527488[/C][C]-4.78021335274883[/C][/ROW]
[ROW][C]138[/C][C]83[/C][C]92.6924338679373[/C][C]-9.69243386793731[/C][/ROW]
[ROW][C]139[/C][C]96[/C][C]90.7677559206948[/C][C]5.23224407930519[/C][/ROW]
[ROW][C]140[/C][C]95[/C][C]101.178546088239[/C][C]-6.17854608823875[/C][/ROW]
[ROW][C]141[/C][C]110[/C][C]95.4458406872409[/C][C]14.5541593127591[/C][/ROW]
[ROW][C]142[/C][C]106[/C][C]96.537393799435[/C][C]9.46260620056502[/C][/ROW]
[ROW][C]143[/C][C]78[/C][C]85.179563510695[/C][C]-7.17956351069502[/C][/ROW]
[ROW][C]144[/C][C]115[/C][C]91.8600496469736[/C][C]23.1399503530264[/C][/ROW]
[ROW][C]145[/C][C]74[/C][C]89.3692470207411[/C][C]-15.3692470207411[/C][/ROW]
[ROW][C]146[/C][C]93[/C][C]92.3619406010535[/C][C]0.638059398946499[/C][/ROW]
[ROW][C]147[/C][C]88[/C][C]88.1913211066815[/C][C]-0.191321106681506[/C][/ROW]
[ROW][C]148[/C][C]104[/C][C]95.6069479030145[/C][C]8.39305209698555[/C][/ROW]
[ROW][C]149[/C][C]86[/C][C]88.7043425142151[/C][C]-2.7043425142151[/C][/ROW]
[ROW][C]150[/C][C]104[/C][C]84.6974182771116[/C][C]19.3025817228884[/C][/ROW]
[ROW][C]151[/C][C]99[/C][C]87.1409477576869[/C][C]11.8590522423131[/C][/ROW]
[ROW][C]152[/C][C]101[/C][C]87.2625644649922[/C][C]13.7374355350078[/C][/ROW]
[ROW][C]153[/C][C]53[/C][C]85.9768099979711[/C][C]-32.9768099979711[/C][/ROW]
[ROW][C]154[/C][C]96[/C][C]87.0678234414204[/C][C]8.9321765585796[/C][/ROW]
[ROW][C]155[/C][C]58[/C][C]81.4072121248063[/C][C]-23.4072121248063[/C][/ROW]
[ROW][C]156[/C][C]117[/C][C]87.8202170688194[/C][C]29.1797829311806[/C][/ROW]
[ROW][C]157[/C][C]82[/C][C]88.431590245732[/C][C]-6.43159024573202[/C][/ROW]
[ROW][C]158[/C][C]57[/C][C]90.6187541773057[/C][C]-33.6187541773057[/C][/ROW]
[ROW][C]159[/C][C]71[/C][C]83.7532638123682[/C][C]-12.7532638123682[/C][/ROW]
[ROW][C]160[/C][C]105[/C][C]87.0993704450288[/C][C]17.9006295549712[/C][/ROW]
[ROW][C]161[/C][C]60[/C][C]88.6638737224037[/C][C]-28.6638737224037[/C][/ROW]
[ROW][C]162[/C][C]77[/C][C]84.9134852185475[/C][C]-7.91348521854753[/C][/ROW]
[ROW][C]163[/C][C]73[/C][C]72.4559534458566[/C][C]0.544046554143391[/C][/ROW]
[ROW][C]164[/C][C]78[/C][C]76.4691923221548[/C][C]1.53080767784523[/C][/ROW]
[ROW][C]165[/C][C]81[/C][C]90.9445935910825[/C][C]-9.94459359108251[/C][/ROW]
[ROW][C]166[/C][C]101[/C][C]76.7861065137996[/C][C]24.2138934862004[/C][/ROW]
[ROW][C]167[/C][C]118[/C][C]83.7414745737254[/C][C]34.2585254262747[/C][/ROW]
[ROW][C]168[/C][C]59[/C][C]80.6496089750751[/C][C]-21.6496089750751[/C][/ROW]
[ROW][C]169[/C][C]101[/C][C]79.1006945397551[/C][C]21.8993054602449[/C][/ROW]
[ROW][C]170[/C][C]22[/C][C]86.38980340748[/C][C]-64.38980340748[/C][/ROW]
[ROW][C]171[/C][C]77[/C][C]73.143324933438[/C][C]3.85667506656197[/C][/ROW]
[ROW][C]172[/C][C]100[/C][C]77.9648145515223[/C][C]22.0351854484777[/C][/ROW]
[ROW][C]173[/C][C]39[/C][C]80.4050648243337[/C][C]-41.4050648243337[/C][/ROW]
[ROW][C]174[/C][C]42[/C][C]70.6007784739723[/C][C]-28.6007784739723[/C][/ROW]
[ROW][C]175[/C][C]80[/C][C]81.792641364566[/C][C]-1.79264136456598[/C][/ROW]
[ROW][C]176[/C][C]48[/C][C]71.0791094171043[/C][C]-23.0791094171043[/C][/ROW]
[ROW][C]177[/C][C]131[/C][C]86.7088037051399[/C][C]44.2911962948601[/C][/ROW]
[ROW][C]178[/C][C]46[/C][C]80.4859128743811[/C][C]-34.4859128743811[/C][/ROW]
[ROW][C]179[/C][C]89[/C][C]73.0014798085336[/C][C]15.9985201914663[/C][/ROW]
[ROW][C]180[/C][C]51[/C][C]64.0489016615695[/C][C]-13.0489016615695[/C][/ROW]
[ROW][C]181[/C][C]108[/C][C]83.3559155968228[/C][C]24.6440844031772[/C][/ROW]
[ROW][C]182[/C][C]86[/C][C]77.5044348390777[/C][C]8.49556516092232[/C][/ROW]
[ROW][C]183[/C][C]105[/C][C]81.2315252723563[/C][C]23.7684747276437[/C][/ROW]
[ROW][C]184[/C][C]85[/C][C]82.4109556886613[/C][C]2.58904431133871[/C][/ROW]
[ROW][C]185[/C][C]103[/C][C]75.2065902492745[/C][C]27.7934097507255[/C][/ROW]
[ROW][C]186[/C][C]83[/C][C]78.5032005756679[/C][C]4.49679942433205[/C][/ROW]
[ROW][C]187[/C][C]77[/C][C]71.8281584609608[/C][C]5.17184153903918[/C][/ROW]
[ROW][C]188[/C][C]26[/C][C]72.4502832314593[/C][C]-46.4502832314593[/C][/ROW]
[ROW][C]189[/C][C]73[/C][C]74.0057205665475[/C][C]-1.00572056654746[/C][/ROW]
[ROW][C]190[/C][C]42[/C][C]63.0381984608813[/C][C]-21.0381984608813[/C][/ROW]
[ROW][C]191[/C][C]71[/C][C]70.0600072766096[/C][C]0.939992723390415[/C][/ROW]
[ROW][C]192[/C][C]105[/C][C]91.488901897303[/C][C]13.511098102697[/C][/ROW]
[ROW][C]193[/C][C]73[/C][C]60.3021306167136[/C][C]12.6978693832864[/C][/ROW]
[ROW][C]194[/C][C]98[/C][C]78.0220004855119[/C][C]19.9779995144881[/C][/ROW]
[ROW][C]195[/C][C]108[/C][C]77.7829249309523[/C][C]30.2170750690477[/C][/ROW]
[ROW][C]196[/C][C]57[/C][C]80.2973535559315[/C][C]-23.2973535559315[/C][/ROW]
[ROW][C]197[/C][C]37[/C][C]74.1214968814965[/C][C]-37.1214968814965[/C][/ROW]
[ROW][C]198[/C][C]70[/C][C]71.3331763844828[/C][C]-1.33317638448277[/C][/ROW]
[ROW][C]199[/C][C]73[/C][C]64.3298529667343[/C][C]8.67014703326569[/C][/ROW]
[ROW][C]200[/C][C]47[/C][C]64.8574030469924[/C][C]-17.8574030469924[/C][/ROW]
[ROW][C]201[/C][C]73[/C][C]71.8717295716169[/C][C]1.12827042838314[/C][/ROW]
[ROW][C]202[/C][C]91[/C][C]73.7546244583537[/C][C]17.2453755416463[/C][/ROW]
[ROW][C]203[/C][C]110[/C][C]88.9132832184475[/C][C]21.0867167815525[/C][/ROW]
[ROW][C]204[/C][C]78[/C][C]75.0708545719795[/C][C]2.92914542802055[/C][/ROW]
[ROW][C]205[/C][C]92[/C][C]85.1966935069169[/C][C]6.80330649308309[/C][/ROW]
[ROW][C]206[/C][C]52[/C][C]84.4708151228731[/C][C]-32.4708151228731[/C][/ROW]
[ROW][C]207[/C][C]88[/C][C]68.6670715266433[/C][C]19.3329284733567[/C][/ROW]
[ROW][C]208[/C][C]100[/C][C]56.2154841174214[/C][C]43.7845158825786[/C][/ROW]
[ROW][C]209[/C][C]33[/C][C]56.5864717382755[/C][C]-23.5864717382755[/C][/ROW]
[ROW][C]210[/C][C]42[/C][C]73.6624837325556[/C][C]-31.6624837325556[/C][/ROW]
[ROW][C]211[/C][C]81[/C][C]75.838127537166[/C][C]5.16187246283396[/C][/ROW]
[ROW][C]212[/C][C]67[/C][C]74.5894285804791[/C][C]-7.58942858047907[/C][/ROW]
[ROW][C]213[/C][C]8[/C][C]54.667764023717[/C][C]-46.667764023717[/C][/ROW]
[ROW][C]214[/C][C]46[/C][C]52.4590214655222[/C][C]-6.45902146552217[/C][/ROW]
[ROW][C]215[/C][C]83[/C][C]74.3566204663066[/C][C]8.64337953369341[/C][/ROW]
[ROW][C]216[/C][C]87[/C][C]59.4855812863326[/C][C]27.5144187136674[/C][/ROW]
[ROW][C]217[/C][C]82[/C][C]79.2919773026253[/C][C]2.70802269737473[/C][/ROW]
[ROW][C]218[/C][C]63[/C][C]63.871179068837[/C][C]-0.871179068836997[/C][/ROW]
[ROW][C]219[/C][C]27[/C][C]65.3967541283378[/C][C]-38.3967541283378[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]54.8912582437751[/C][C]-40.8912582437751[/C][/ROW]
[ROW][C]221[/C][C]83[/C][C]58.9844660718444[/C][C]24.0155339281556[/C][/ROW]
[ROW][C]222[/C][C]168[/C][C]57.0383585281675[/C][C]110.961641471832[/C][/ROW]
[ROW][C]223[/C][C]67[/C][C]61.0948065371384[/C][C]5.90519346286156[/C][/ROW]
[ROW][C]224[/C][C]21[/C][C]57.6386140834323[/C][C]-36.6386140834323[/C][/ROW]
[ROW][C]225[/C][C]55[/C][C]76.0086524618859[/C][C]-21.0086524618859[/C][/ROW]
[ROW][C]226[/C][C]54[/C][C]75.8505511408782[/C][C]-21.8505511408782[/C][/ROW]
[ROW][C]227[/C][C]118[/C][C]65.402807573246[/C][C]52.597192426754[/C][/ROW]
[ROW][C]228[/C][C]69[/C][C]49.614269030181[/C][C]19.385730969819[/C][/ROW]
[ROW][C]229[/C][C]77[/C][C]43.4070957209872[/C][C]33.5929042790128[/C][/ROW]
[ROW][C]230[/C][C]72[/C][C]70.9054587413113[/C][C]1.09454125868868[/C][/ROW]
[ROW][C]231[/C][C]53[/C][C]47.1918482797815[/C][C]5.80815172021846[/C][/ROW]
[ROW][C]232[/C][C]40[/C][C]52.6016245648619[/C][C]-12.6016245648619[/C][/ROW]
[ROW][C]233[/C][C]102[/C][C]53.7476321422142[/C][C]48.2523678577858[/C][/ROW]
[ROW][C]234[/C][C]25[/C][C]70.1149045783677[/C][C]-45.1149045783677[/C][/ROW]
[ROW][C]235[/C][C]31[/C][C]50.4985759372074[/C][C]-19.4985759372074[/C][/ROW]
[ROW][C]236[/C][C]77[/C][C]50.958554429393[/C][C]26.041445570607[/C][/ROW]
[ROW][C]237[/C][C]38[/C][C]62.6417039855273[/C][C]-24.6417039855273[/C][/ROW]
[ROW][C]238[/C][C]23[/C][C]63.4089848417581[/C][C]-40.4089848417581[/C][/ROW]
[ROW][C]239[/C][C]91[/C][C]54.9941805543732[/C][C]36.0058194456268[/C][/ROW]
[ROW][C]240[/C][C]58[/C][C]56.3703894214292[/C][C]1.62961057857084[/C][/ROW]
[ROW][C]241[/C][C]42[/C][C]49.7212461122824[/C][C]-7.72124611228238[/C][/ROW]
[ROW][C]242[/C][C]44[/C][C]54.7484313744222[/C][C]-10.7484313744222[/C][/ROW]
[ROW][C]243[/C][C]58[/C][C]45.0458833815445[/C][C]12.9541166184555[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]47.8221559941631[/C][C]-12.8221559941631[/C][/ROW]
[ROW][C]245[/C][C]88[/C][C]39.4099598442367[/C][C]48.5900401557633[/C][/ROW]
[ROW][C]246[/C][C]25[/C][C]62.6556594764355[/C][C]-37.6556594764355[/C][/ROW]
[ROW][C]247[/C][C]39[/C][C]48.9746259918667[/C][C]-9.97462599186671[/C][/ROW]
[ROW][C]248[/C][C]48[/C][C]40.4571125265035[/C][C]7.54288747349654[/C][/ROW]
[ROW][C]249[/C][C]64[/C][C]40.135972210661[/C][C]23.864027789339[/C][/ROW]
[ROW][C]250[/C][C]65[/C][C]46.7639047687224[/C][C]18.2360952312776[/C][/ROW]
[ROW][C]251[/C][C]95[/C][C]45.9697912933356[/C][C]49.0302087066644[/C][/ROW]
[ROW][C]252[/C][C]29[/C][C]41.0206155229716[/C][C]-12.0206155229716[/C][/ROW]
[ROW][C]253[/C][C]2[/C][C]40.1531654176684[/C][C]-38.1531654176684[/C][/ROW]
[ROW][C]254[/C][C]83[/C][C]45.1150416719208[/C][C]37.8849583280792[/C][/ROW]
[ROW][C]255[/C][C]11[/C][C]47.957142338546[/C][C]-36.957142338546[/C][/ROW]
[ROW][C]256[/C][C]16[/C][C]34.5873987220753[/C][C]-18.5873987220753[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]27.2247924757233[/C][C]-18.2247924757233[/C][/ROW]
[ROW][C]258[/C][C]46[/C][C]38.2455348818501[/C][C]7.75446511814985[/C][/ROW]
[ROW][C]259[/C][C]41[/C][C]40.6437958686053[/C][C]0.356204131394733[/C][/ROW]
[ROW][C]260[/C][C]14[/C][C]25.0810827940745[/C][C]-11.0810827940745[/C][/ROW]
[ROW][C]261[/C][C]63[/C][C]26.8144189814387[/C][C]36.1855810185613[/C][/ROW]
[ROW][C]262[/C][C]9[/C][C]26.1381672207492[/C][C]-17.1381672207492[/C][/ROW]
[ROW][C]263[/C][C]0[/C][C]14.1659765117584[/C][C]-14.1659765117584[/C][/ROW]
[ROW][C]264[/C][C]58[/C][C]71.6475085749587[/C][C]-13.6475085749587[/C][/ROW]
[ROW][C]265[/C][C]18[/C][C]42.1415952182986[/C][C]-24.1415952182986[/C][/ROW]
[ROW][C]266[/C][C]42[/C][C]37.4612490830138[/C][C]4.5387509169862[/C][/ROW]
[ROW][C]267[/C][C]26[/C][C]13.7439549272772[/C][C]12.2560450727228[/C][/ROW]
[ROW][C]268[/C][C]38[/C][C]35.855825146012[/C][C]2.14417485398801[/C][/ROW]
[ROW][C]269[/C][C]1[/C][C]7.64781223382116[/C][C]-6.64781223382116[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195409&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195409&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1122124.8383455253-2.83834552530045
2114120.887647677126-6.887647677126
3140147.410669795888-7.41066979588818
4143121.439091321921.5609086780997
5122136.716397263265-14.7163972632652
6127135.973106587513-8.97310658751316
7113134.385691144526-21.3856911445255
8118130.925154670032-12.9251546700316
9161131.75520647176529.2447935282351
10134130.7655795950573.23442040494347
1196131.237383850366-35.2373838503656
12104131.17923791625-27.17923791625
13135129.3662206452765.63377935472397
14110127.418804670096-17.4188046700955
15128126.4228288700011.57717112999889
16142127.25072686824814.7492731317525
17117125.646454489643-8.64645448964264
1894122.250545875567-28.2505458755674
19135123.1533965621911.8466034378102
20121125.281508652604-4.28150865260396
21103122.529472807331-19.529472807331
22118127.787067411171-9.78706741117095
23127123.0739646249283.92603537507181
24116126.684206320385-10.6842063203854
25129123.7517621332335.24823786676692
26115123.249616497803-8.24961649780304
27135123.18140920438811.818590795612
28133119.46527897487913.5347210251209
29113121.305588221325-8.30558822132505
30111122.445711817567-11.4457118175666
3192121.714622443479-29.7146224434795
32118120.952550781532-2.95255078153195
33134122.16569846479811.8343015352023
34106120.58069998298-14.5806999829804
35137119.53156961801417.4684303819859
36100118.365845147874-18.3658451478739
37102114.449691327083-12.4496913270826
38134119.58653317078214.4134668292178
39130115.22636365181414.7736363481858
40144115.45651468959428.5434853104061
41120114.395209095445.60479090455954
4291111.005501781914-20.0055017819143
43100111.823529359548-11.8235293595475
44134120.77679036127113.2232096387294
45161118.07824793943642.9217520605639
46128112.80093176519415.1990682348061
47124118.5278029194135.47219708058651
48115116.235261551963-1.2352615519625
49123116.7526198582626.2473801417383
50117114.3791641424622.62083585753837
51111115.731176187033-4.73117618703293
52146111.77718180355934.2228181964409
53101116.993846010685-15.993846010685
54131117.50512098089113.4948790191087
55122113.4641080991778.53589190082296
5678116.97184181591-38.9718418159103
57120110.6462483831279.35375161687267
58115115.947679151226-0.947679151226183
59142112.53886535130129.4611346486994
6094114.053030274241-20.0530302742408
61114108.8121123980275.18788760197259
62108106.9288949963491.07110500365137
63119103.74180890763515.2581910923653
64117106.84507107729910.1549289227009
6586110.470923332013-24.4709233320128
66138110.99340769884927.0065923011507
67119111.8076908381617.19230916183862
68117103.75549816535913.2445018346412
69117104.81161419316312.1883858068374
7076105.468890352662-29.4688903526623
71119112.1514620336156.84853796638514
72119103.7529737915715.2470262084305
73124105.81930391174318.1806960882571
7411697.337241066948418.6627589330516
75118102.43092421155915.569075788441
76102105.818807803554-3.81880780355419
77116102.56343214884613.4365678511536
78103113.714498835815-10.7144988358147
7911799.781377935910117.2186220640899
80108106.1197894302121.88021056978846
8112297.20784898531624.792151014684
8290103.508492346716-13.5084923467156
83133109.03346728796623.966532712034
8411689.02755410574926.9724458942509
8511098.825962781883511.1740372181165
869092.4950325527221-2.49503255272208
877495.266529541419-21.266529541419
887588.0130569535342-13.0130569535342
8910796.42093237903810.579067620962
9090105.566932354856-15.5669323548558
919695.28385057882530.716149421174753
9211588.365348976377126.6346510236229
939187.27912383309213.72087616690787
9477104.971069465181-27.9710694651807
95108108.064837760832-0.064837760832324
968392.1023753862357-9.10237538623572
977791.1195227024038-14.1195227024038
989999.988804571835-0.98880457183501
9911591.005036328011323.9949636719887
1009992.88588483129666.1141151687034
10110687.140916893695718.8590831063043
1027783.2679218577848-6.26792185778482
10311581.345228996020833.6547710039792
1046778.8338248695484-11.8338248695484
105874.1273159326875-66.1273159326875
1066983.8034081554609-14.8034081554609
1078883.27421406638334.72578593361671
10810771.981573340055835.0184266599442
10912078.402191320400841.5978086795992
110353.07535790768-50.07535790768
111151.4927006048578-50.4927006048578
112044.4856366272215-44.4856366272215
113111110.9663560732910.0336439267088813
1146974.0427554882401-5.04275548824014
115116106.1335207155889.8664792844122
116103133.545640565838-30.5456405658383
117139108.48940469204830.5105953079516
118135102.00698619915132.9930138008486
119113108.0619215205884.93807847941153
12099116.486826192967-17.4868261929673
12176105.168368167226-29.1683681672255
122110107.427341196692.57265880330962
123121105.0812972678115.9187027321902
12495102.44642428387-7.44642428386954
12566103.009749480825-37.0097494808254
12611198.819724467070812.1802755329292
12777101.857269275986-24.8572692759855
128101100.1646984426180.835301557381773
12910899.2604737313458.73952626865497
13013597.897336961763837.1026630382362
1317098.3412120095518-28.3412120095518
13212495.925488801471628.0745111985284
1339296.4937418387445-4.49374183874445
13410497.22773172985646.77226827014359
13511395.660979521114917.3390204788851
1369596.9768117774485-1.97681177744849
1378993.7802133527488-4.78021335274883
1388392.6924338679373-9.69243386793731
1399690.76775592069485.23224407930519
14095101.178546088239-6.17854608823875
14111095.445840687240914.5541593127591
14210696.5373937994359.46260620056502
1437885.179563510695-7.17956351069502
14411591.860049646973623.1399503530264
1457489.3692470207411-15.3692470207411
1469392.36194060105350.638059398946499
1478888.1913211066815-0.191321106681506
14810495.60694790301458.39305209698555
1498688.7043425142151-2.7043425142151
15010484.697418277111619.3025817228884
1519987.140947757686911.8590522423131
15210187.262564464992213.7374355350078
1535385.9768099979711-32.9768099979711
1549687.06782344142048.9321765585796
1555881.4072121248063-23.4072121248063
15611787.820217068819429.1797829311806
1578288.431590245732-6.43159024573202
1585790.6187541773057-33.6187541773057
1597183.7532638123682-12.7532638123682
16010587.099370445028817.9006295549712
1616088.6638737224037-28.6638737224037
1627784.9134852185475-7.91348521854753
1637372.45595344585660.544046554143391
1647876.46919232215481.53080767784523
1658190.9445935910825-9.94459359108251
16610176.786106513799624.2138934862004
16711883.741474573725434.2585254262747
1685980.6496089750751-21.6496089750751
16910179.100694539755121.8993054602449
1702286.38980340748-64.38980340748
1717773.1433249334383.85667506656197
17210077.964814551522322.0351854484777
1733980.4050648243337-41.4050648243337
1744270.6007784739723-28.6007784739723
1758081.792641364566-1.79264136456598
1764871.0791094171043-23.0791094171043
17713186.708803705139944.2911962948601
1784680.4859128743811-34.4859128743811
1798973.001479808533615.9985201914663
1805164.0489016615695-13.0489016615695
18110883.355915596822824.6440844031772
1828677.50443483907778.49556516092232
18310581.231525272356323.7684747276437
1848582.41095568866132.58904431133871
18510375.206590249274527.7934097507255
1868378.50320057566794.49679942433205
1877771.82815846096085.17184153903918
1882672.4502832314593-46.4502832314593
1897374.0057205665475-1.00572056654746
1904263.0381984608813-21.0381984608813
1917170.06000727660960.939992723390415
19210591.48890189730313.511098102697
1937360.302130616713612.6978693832864
1949878.022000485511919.9779995144881
19510877.782924930952330.2170750690477
1965780.2973535559315-23.2973535559315
1973774.1214968814965-37.1214968814965
1987071.3331763844828-1.33317638448277
1997364.32985296673438.67014703326569
2004764.8574030469924-17.8574030469924
2017371.87172957161691.12827042838314
2029173.754624458353717.2453755416463
20311088.913283218447521.0867167815525
2047875.07085457197952.92914542802055
2059285.19669350691696.80330649308309
2065284.4708151228731-32.4708151228731
2078868.667071526643319.3329284733567
20810056.215484117421443.7845158825786
2093356.5864717382755-23.5864717382755
2104273.6624837325556-31.6624837325556
2118175.8381275371665.16187246283396
2126774.5894285804791-7.58942858047907
213854.667764023717-46.667764023717
2144652.4590214655222-6.45902146552217
2158374.35662046630668.64337953369341
2168759.485581286332627.5144187136674
2178279.29197730262532.70802269737473
2186363.871179068837-0.871179068836997
2192765.3967541283378-38.3967541283378
2201454.8912582437751-40.8912582437751
2218358.984466071844424.0155339281556
22216857.0383585281675110.961641471832
2236761.09480653713845.90519346286156
2242157.6386140834323-36.6386140834323
2255576.0086524618859-21.0086524618859
2265475.8505511408782-21.8505511408782
22711865.40280757324652.597192426754
2286949.61426903018119.385730969819
2297743.407095720987233.5929042790128
2307270.90545874131131.09454125868868
2315347.19184827978155.80815172021846
2324052.6016245648619-12.6016245648619
23310253.747632142214248.2523678577858
2342570.1149045783677-45.1149045783677
2353150.4985759372074-19.4985759372074
2367750.95855442939326.041445570607
2373862.6417039855273-24.6417039855273
2382363.4089848417581-40.4089848417581
2399154.994180554373236.0058194456268
2405856.37038942142921.62961057857084
2414249.7212461122824-7.72124611228238
2424454.7484313744222-10.7484313744222
2435845.045883381544512.9541166184555
2443547.8221559941631-12.8221559941631
2458839.409959844236748.5900401557633
2462562.6556594764355-37.6556594764355
2473948.9746259918667-9.97462599186671
2484840.45711252650357.54288747349654
2496440.13597221066123.864027789339
2506546.763904768722418.2360952312776
2519545.969791293335649.0302087066644
2522941.0206155229716-12.0206155229716
253240.1531654176684-38.1531654176684
2548345.115041671920837.8849583280792
2551147.957142338546-36.957142338546
2561634.5873987220753-18.5873987220753
257927.2247924757233-18.2247924757233
2584638.24553488185017.75446511814985
2594140.64379586860530.356204131394733
2601425.0810827940745-11.0810827940745
2616326.814418981438736.1855810185613
262926.1381672207492-17.1381672207492
263014.1659765117584-14.1659765117584
2645871.6475085749587-13.6475085749587
2651842.1415952182986-24.1415952182986
2664237.46124908301384.5387509169862
2672613.743954927277212.2560450727228
2683835.8558251460122.14417485398801
26917.64781223382116-6.64781223382116






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
140.7246770173765130.5506459652469740.275322982623487
150.6128135752299730.7743728495400540.387186424770027
160.5176817984945920.9646364030108170.482318201505408
170.3885051789271360.7770103578542720.611494821072864
180.2848684536432450.569736907286490.715131546356755
190.2431154559153290.4862309118306580.756884544084671
200.1750720642808690.3501441285617370.824927935719131
210.1472072924412050.2944145848824110.852792707558795
220.2309852432165430.4619704864330870.769014756783457
230.16903642305920.3380728461183990.8309635769408
240.119959063269340.2399181265386810.88004093673066
250.08421342259109550.1684268451821910.915786577408904
260.05683435279041480.113668705580830.943165647209585
270.04612576562445420.09225153124890840.953874234375546
280.03133225537461690.06266451074923380.968667744625383
290.02316174317877840.04632348635755690.976838256821222
300.01727415537762570.03454831075525140.982725844622374
310.0278992513972940.0557985027945880.972100748602706
320.01823293574957090.03646587149914170.981767064250429
330.015745304729450.03149060945890010.98425469527055
340.0114840622291760.0229681244583520.988515937770824
350.01049901053025330.02099802106050670.989500989469747
360.009908394613462120.01981678922692420.990091605386538
370.008557890392043920.01711578078408780.991442109607956
380.008001880921881530.01600376184376310.991998119078118
390.009448936673772540.01889787334754510.990551063326227
400.01171264119242560.02342528238485120.988287358807574
410.007799352919613450.01559870583922690.992200647080387
420.01278884221338560.02557768442677120.987211157786614
430.01004514909542930.02009029819085860.989954850904571
440.008060650162188930.01612130032437790.991939349837811
450.02586230205117440.05172460410234870.974137697948826
460.02035098214675120.04070196429350240.979649017853249
470.01451218386197890.02902436772395780.985487816138021
480.01038130763555540.02076261527111080.989618692364445
490.007247446869673520.0144948937393470.992752553130327
500.005195427799888260.01039085559977650.994804572200112
510.003958718818540240.007917437637080480.99604128118146
520.005363163620882680.01072632724176540.994636836379117
530.005536259519967870.01107251903993570.994463740480032
540.004085283689953490.008170567379906980.995914716310046
550.002824495065964850.00564899013192970.997175504934035
560.01002440182630270.02004880365260550.989975598173697
570.007289782010396370.01457956402079270.992710217989604
580.005319796782490730.01063959356498150.994680203217509
590.005733477856291450.01146695571258290.994266522143709
600.004738599316473980.009477198632947970.995261400683526
610.003385729763796080.006771459527592160.996614270236204
620.002564115956076440.005128231912152890.997435884043924
630.001792355035182220.003584710070364440.998207644964818
640.001233718640657290.002467437281314590.998766281359343
650.002121891238485560.004243782476971120.997878108761514
660.002052064897525820.004104129795051630.997947935102474
670.001414342662057460.002828685324114920.998585657337943
680.0009650232160474720.001930046432094940.999034976783952
690.0006525995779168110.001305199155833620.999347400422083
700.001872478892631860.003744957785263710.998127521107368
710.001350724150343150.002701448300686290.998649275849657
720.0009519003587356630.001903800717471330.999048099641264
730.0006951058950392820.001390211790078560.999304894104961
740.0004774664408021140.0009549328816042290.999522533559198
750.000322008655002210.000644017310004420.999677991344998
760.0002503476415200740.0005006952830401490.99974965235848
770.0001660457953850040.0003320915907700080.999833954204615
780.0001361246042485030.0002722492084970060.999863875395752
799.25225993484468e-050.0001850451986968940.999907477400652
806.29984393186404e-050.0001259968786372810.999937001560681
814.46836174325864e-058.93672348651728e-050.999955316382567
825.18134400992013e-050.0001036268801984030.999948186559901
834.80184585212901e-059.60369170425801e-050.999951981541479
844.01063229430512e-058.02126458861025e-050.999959893677057
852.59087723398477e-055.18175446796954e-050.99997409122766
862.4400518801261e-054.88010376025221e-050.999975599481199
875.7240982717935e-050.000114481965435870.999942759017282
888.24871894986418e-050.0001649743789972840.999917512810501
895.44738584356775e-050.0001089477168713550.999945526141564
905.33138979387105e-050.0001066277958774210.999946686102061
913.79239729963593e-057.58479459927186e-050.999962076027004
922.96376702140813e-055.92753404281626e-050.999970362329786
932.18262880808386e-054.36525761616773e-050.999978173711919
943.75812182524299e-057.51624365048598e-050.999962418781748
953.22062926931396e-056.44125853862791e-050.999967793707307
962.87591107838081e-055.75182215676162e-050.999971240889216
973.2723042417842e-056.5446084835684e-050.999967276957582
983.13708633019331e-056.27417266038662e-050.999968629136698
992.59533620330195e-055.19067240660389e-050.999974046637967
1001.71410000390958e-053.42820000781916e-050.999982858999961
1011.24433613284887e-052.48867226569774e-050.999987556638672
1021.58360078593424e-053.16720157186849e-050.999984163992141
1031.62713805597653e-053.25427611195306e-050.99998372861944
1041.89671099421696e-053.79342198843391e-050.999981032890058
1050.001212745961588520.002425491923177040.998787254038412
1060.001181946151021240.002363892302042480.998818053848979
1070.0009060774146515050.001812154829303010.999093922585348
1080.0010646137231390.002129227446278010.998935386276861
1090.001394081116984780.002788162233969560.998605918883015
1100.004471774457857210.008943548915714410.995528225542143
1110.009039414993837890.01807882998767580.990960585006162
1120.01083913628357930.02167827256715860.989160863716421
1130.008538389717089210.01707677943417840.991461610282911
1140.007548660423338580.01509732084667720.992451339576661
1150.005894949132359560.01178989826471910.99410505086764
1160.005473947733611040.01094789546722210.994526052266389
1170.005174540849513190.01034908169902640.994825459150487
1180.004318082884281130.008636165768562270.995681917115719
1190.003333254308114780.006666508616229560.996666745691885
1200.002881332464501610.005762664929003220.997118667535498
1210.003821805473904130.007643610947808250.996178194526096
1220.003936773233575830.007873546467151650.996063226766424
1230.003093503560905110.006187007121810220.996906496439095
1240.002891246430662740.005782492861325480.997108753569337
1250.003321978381514360.006643956763028720.996678021618486
1260.002674840541783830.005349681083567660.997325159458216
1270.002347304215603370.004694608431206740.997652695784397
1280.00204053329816980.00408106659633960.99795946670183
1290.001557721323786250.00311544264757250.998442278676214
1300.002886762553830520.005773525107661040.99711323744617
1310.003489232531844680.006978465063689360.996510767468155
1320.005013124967750310.01002624993550060.99498687503225
1330.003981916345403240.007963832690806490.996018083654597
1340.003061915209567410.006123830419134820.996938084790433
1350.002747514530791630.005495029061583260.997252485469208
1360.002136534267253230.004273068534506470.997863465732747
1370.001624515718764870.003249031437529730.998375484281235
1380.001256749562645420.002513499125290830.998743250437355
1390.001130220791513030.002260441583026070.998869779208487
1400.00107301946523320.00214603893046640.998926980534767
1410.0008607121163688930.001721424232737790.999139287883631
1420.0006366465859029050.001273293171805810.999363353414097
1430.0004700999812028850.0009401999624057690.999529900018797
1440.0004574808108341990.0009149616216683970.999542519189166
1450.000369311427752020.000738622855504040.999630688572248
1460.0002660767842147660.0005321535684295320.999733923215785
1470.0001930813978969530.0003861627957939060.999806918602103
1480.0001376436481591960.0002752872963183930.999862356351841
1499.68980732576338e-050.0001937961465152680.999903101926742
1500.0001046943221467950.0002093886442935910.999895305677853
1518.06341547088579e-050.0001612683094177160.999919365845291
1526.34457061524601e-050.000126891412304920.999936554293848
1538.79761802473512e-050.0001759523604947020.999912023819753
1546.45605481143216e-050.0001291210962286430.999935439451886
1555.84794971108344e-050.0001169589942216690.999941520502889
1567.1504541800709e-050.0001430090836014180.999928495458199
1575.09526996085128e-050.0001019053992170260.999949047300391
1588.11081482272301e-050.000162216296454460.999918891851773
1596.14106562821343e-050.0001228213125642690.999938589343718
1605.19400362378163e-050.0001038800724756330.999948059963762
1616.46325544018118e-050.0001292651088036240.999935367445598
1624.67473855918125e-059.34947711836249e-050.999953252614408
1633.66570775544179e-057.33141551088358e-050.999963342922446
1642.60796762357177e-055.21593524714355e-050.999973920323764
1652.0633280496518e-054.12665609930359e-050.999979366719503
1662.266283467393e-054.53256693478601e-050.999977337165326
1673.26666485532015e-056.53332971064031e-050.999967333351447
1683.04873460759515e-056.0974692151903e-050.999969512653924
1692.86509561403382e-055.73019122806764e-050.99997134904386
1700.0003613754451951360.0007227508903902720.999638624554805
1710.000268093525331450.00053618705066290.999731906474669
1720.0002538590673102690.0005077181346205380.99974614093269
1730.0005523006018267570.001104601203653510.999447699398173
1740.0005824708658913840.001164941731782770.999417529134109
1750.0004373033471278890.0008746066942557790.999562696652872
1760.0004217409881771040.0008434819763542080.999578259011823
1770.0006999717037128460.001399943407425690.999300028296287
1780.001154432487158910.002308864974317820.998845567512841
1790.0009637813668648190.001927562733729640.999036218633135
1800.0007790030305917570.001558006061183510.999220996969408
1810.0007033453622869690.001406690724573940.999296654637713
1820.0005206407443585990.00104128148871720.999479359255641
1830.0004677970999848450.000935594199969690.999532202900015
1840.0003338471030387140.0006676942060774290.999666152896961
1850.000349100640875130.000698201281750260.999650899359125
1860.0002469203162439160.0004938406324878330.999753079683756
1870.0001793403810993710.0003586807621987420.999820659618901
1880.0004068522874235530.0008137045748471050.999593147712576
1890.0002946733561906230.0005893467123812470.999705326643809
1900.0003198910921577130.0006397821843154260.999680108907842
1910.0002297770799672090.0004595541599344170.999770222920033
1920.0002378530061121670.0004757060122243330.999762146993888
1930.0001878081797375990.0003756163594751980.999812191820262
1940.0001488631848391170.0002977263696782340.999851136815161
1950.0001773823014176120.0003547646028352240.999822617698582
1960.0001708368738618030.0003416737477236050.999829163126138
1970.000312531270949880.000625062541899760.99968746872905
1980.0002198569784333660.0004397139568667320.999780143021567
1990.0001587889530371050.0003175779060742110.999841211046963
2000.0001613551808280.0003227103616560010.999838644819172
2010.0001110951232696550.000222190246539310.99988890487673
2028.46707063989261e-050.0001693414127978520.999915329293601
2036.91856760066439e-050.0001383713520132880.999930814323993
2044.58111462498406e-059.16222924996812e-050.99995418885375
2053.68323564115782e-057.36647128231564e-050.999963167643588
2063.91945826166519e-057.83891652333039e-050.999960805417383
2073.20533543662192e-056.41067087324385e-050.999967946645634
2085.50624443351996e-050.0001101248886703990.999944937555665
2097.29362495164073e-050.0001458724990328150.999927063750484
2109.17270076246863e-050.0001834540152493730.999908272992375
2116.19965812895759e-050.0001239931625791520.99993800341871
2124.0178198447871e-058.0356396895742e-050.999959821801552
2130.0002097252884125890.0004194505768251790.999790274711587
2140.0002139350588251790.0004278701176503580.999786064941175
2150.000159076697353410.0003181533947068190.999840923302647
2160.0001375759797583260.0002751519595166530.999862424020242
2170.0001117030748930530.0002234061497861070.999888296925107
2187.19470580748937e-050.0001438941161497870.999928052941925
2190.000145280121515970.000290560243031940.999854719878484
2200.0007196898523467790.001439379704693560.999280310147653
2210.0005651294458656180.001130258891731240.999434870554134
2220.08338579652254110.1667715930450820.916614203477459
2230.06613626011383410.1322725202276680.933863739886166
2240.1081427901524430.2162855803048850.891857209847557
2250.08988135554498990.179762711089980.91011864445501
2260.07520048962758010.150400979255160.92479951037242
2270.2130570958926370.4261141917852740.786942904107363
2280.2193976284588330.4387952569176660.780602371541167
2290.1956325706629210.3912651413258420.804367429337079
2300.272745869026410.545491738052820.72725413097359
2310.2323552171212720.4647104342425440.767644782878728
2320.206134146324570.412268292649140.79386585367543
2330.3792356680450020.7584713360900040.620764331954998
2340.4098504936905720.8197009873811440.590149506309428
2350.3761461505727950.7522923011455890.623853849427205
2360.3579264765236990.7158529530473980.642073523476301
2370.3072252326467370.6144504652934740.692774767353263
2380.277402415945460.5548048318909210.72259758405454
2390.2450676811419660.4901353622839320.754932318858034
2400.1954906556982570.3909813113965150.804509344301743
2410.1534377980052650.3068755960105310.846562201994735
2420.1173929445990270.2347858891980540.882607055400973
2430.09471732790930440.1894346558186090.905282672090696
2440.0720210843863040.1440421687726080.927978915613696
2450.1540167616828920.3080335233657840.845983238317108
2460.1327378048325340.2654756096650680.867262195167466
2470.1256064296732330.2512128593464670.874393570326766
2480.08926057132906130.1785211426581230.910739428670939
2490.139467189250860.278934378501720.86053281074914
2500.1255396070640940.2510792141281870.874460392935906
2510.3583402315066180.7166804630132360.641659768493382
2520.2601661448081860.5203322896163730.739833855191814
2530.255660195554140.5113203911082810.74433980444586
2540.2623790938456250.524758187691250.737620906154375
2550.165287124430360.3305742488607210.83471287556964

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
14 & 0.724677017376513 & 0.550645965246974 & 0.275322982623487 \tabularnewline
15 & 0.612813575229973 & 0.774372849540054 & 0.387186424770027 \tabularnewline
16 & 0.517681798494592 & 0.964636403010817 & 0.482318201505408 \tabularnewline
17 & 0.388505178927136 & 0.777010357854272 & 0.611494821072864 \tabularnewline
18 & 0.284868453643245 & 0.56973690728649 & 0.715131546356755 \tabularnewline
19 & 0.243115455915329 & 0.486230911830658 & 0.756884544084671 \tabularnewline
20 & 0.175072064280869 & 0.350144128561737 & 0.824927935719131 \tabularnewline
21 & 0.147207292441205 & 0.294414584882411 & 0.852792707558795 \tabularnewline
22 & 0.230985243216543 & 0.461970486433087 & 0.769014756783457 \tabularnewline
23 & 0.1690364230592 & 0.338072846118399 & 0.8309635769408 \tabularnewline
24 & 0.11995906326934 & 0.239918126538681 & 0.88004093673066 \tabularnewline
25 & 0.0842134225910955 & 0.168426845182191 & 0.915786577408904 \tabularnewline
26 & 0.0568343527904148 & 0.11366870558083 & 0.943165647209585 \tabularnewline
27 & 0.0461257656244542 & 0.0922515312489084 & 0.953874234375546 \tabularnewline
28 & 0.0313322553746169 & 0.0626645107492338 & 0.968667744625383 \tabularnewline
29 & 0.0231617431787784 & 0.0463234863575569 & 0.976838256821222 \tabularnewline
30 & 0.0172741553776257 & 0.0345483107552514 & 0.982725844622374 \tabularnewline
31 & 0.027899251397294 & 0.055798502794588 & 0.972100748602706 \tabularnewline
32 & 0.0182329357495709 & 0.0364658714991417 & 0.981767064250429 \tabularnewline
33 & 0.01574530472945 & 0.0314906094589001 & 0.98425469527055 \tabularnewline
34 & 0.011484062229176 & 0.022968124458352 & 0.988515937770824 \tabularnewline
35 & 0.0104990105302533 & 0.0209980210605067 & 0.989500989469747 \tabularnewline
36 & 0.00990839461346212 & 0.0198167892269242 & 0.990091605386538 \tabularnewline
37 & 0.00855789039204392 & 0.0171157807840878 & 0.991442109607956 \tabularnewline
38 & 0.00800188092188153 & 0.0160037618437631 & 0.991998119078118 \tabularnewline
39 & 0.00944893667377254 & 0.0188978733475451 & 0.990551063326227 \tabularnewline
40 & 0.0117126411924256 & 0.0234252823848512 & 0.988287358807574 \tabularnewline
41 & 0.00779935291961345 & 0.0155987058392269 & 0.992200647080387 \tabularnewline
42 & 0.0127888422133856 & 0.0255776844267712 & 0.987211157786614 \tabularnewline
43 & 0.0100451490954293 & 0.0200902981908586 & 0.989954850904571 \tabularnewline
44 & 0.00806065016218893 & 0.0161213003243779 & 0.991939349837811 \tabularnewline
45 & 0.0258623020511744 & 0.0517246041023487 & 0.974137697948826 \tabularnewline
46 & 0.0203509821467512 & 0.0407019642935024 & 0.979649017853249 \tabularnewline
47 & 0.0145121838619789 & 0.0290243677239578 & 0.985487816138021 \tabularnewline
48 & 0.0103813076355554 & 0.0207626152711108 & 0.989618692364445 \tabularnewline
49 & 0.00724744686967352 & 0.014494893739347 & 0.992752553130327 \tabularnewline
50 & 0.00519542779988826 & 0.0103908555997765 & 0.994804572200112 \tabularnewline
51 & 0.00395871881854024 & 0.00791743763708048 & 0.99604128118146 \tabularnewline
52 & 0.00536316362088268 & 0.0107263272417654 & 0.994636836379117 \tabularnewline
53 & 0.00553625951996787 & 0.0110725190399357 & 0.994463740480032 \tabularnewline
54 & 0.00408528368995349 & 0.00817056737990698 & 0.995914716310046 \tabularnewline
55 & 0.00282449506596485 & 0.0056489901319297 & 0.997175504934035 \tabularnewline
56 & 0.0100244018263027 & 0.0200488036526055 & 0.989975598173697 \tabularnewline
57 & 0.00728978201039637 & 0.0145795640207927 & 0.992710217989604 \tabularnewline
58 & 0.00531979678249073 & 0.0106395935649815 & 0.994680203217509 \tabularnewline
59 & 0.00573347785629145 & 0.0114669557125829 & 0.994266522143709 \tabularnewline
60 & 0.00473859931647398 & 0.00947719863294797 & 0.995261400683526 \tabularnewline
61 & 0.00338572976379608 & 0.00677145952759216 & 0.996614270236204 \tabularnewline
62 & 0.00256411595607644 & 0.00512823191215289 & 0.997435884043924 \tabularnewline
63 & 0.00179235503518222 & 0.00358471007036444 & 0.998207644964818 \tabularnewline
64 & 0.00123371864065729 & 0.00246743728131459 & 0.998766281359343 \tabularnewline
65 & 0.00212189123848556 & 0.00424378247697112 & 0.997878108761514 \tabularnewline
66 & 0.00205206489752582 & 0.00410412979505163 & 0.997947935102474 \tabularnewline
67 & 0.00141434266205746 & 0.00282868532411492 & 0.998585657337943 \tabularnewline
68 & 0.000965023216047472 & 0.00193004643209494 & 0.999034976783952 \tabularnewline
69 & 0.000652599577916811 & 0.00130519915583362 & 0.999347400422083 \tabularnewline
70 & 0.00187247889263186 & 0.00374495778526371 & 0.998127521107368 \tabularnewline
71 & 0.00135072415034315 & 0.00270144830068629 & 0.998649275849657 \tabularnewline
72 & 0.000951900358735663 & 0.00190380071747133 & 0.999048099641264 \tabularnewline
73 & 0.000695105895039282 & 0.00139021179007856 & 0.999304894104961 \tabularnewline
74 & 0.000477466440802114 & 0.000954932881604229 & 0.999522533559198 \tabularnewline
75 & 0.00032200865500221 & 0.00064401731000442 & 0.999677991344998 \tabularnewline
76 & 0.000250347641520074 & 0.000500695283040149 & 0.99974965235848 \tabularnewline
77 & 0.000166045795385004 & 0.000332091590770008 & 0.999833954204615 \tabularnewline
78 & 0.000136124604248503 & 0.000272249208497006 & 0.999863875395752 \tabularnewline
79 & 9.25225993484468e-05 & 0.000185045198696894 & 0.999907477400652 \tabularnewline
80 & 6.29984393186404e-05 & 0.000125996878637281 & 0.999937001560681 \tabularnewline
81 & 4.46836174325864e-05 & 8.93672348651728e-05 & 0.999955316382567 \tabularnewline
82 & 5.18134400992013e-05 & 0.000103626880198403 & 0.999948186559901 \tabularnewline
83 & 4.80184585212901e-05 & 9.60369170425801e-05 & 0.999951981541479 \tabularnewline
84 & 4.01063229430512e-05 & 8.02126458861025e-05 & 0.999959893677057 \tabularnewline
85 & 2.59087723398477e-05 & 5.18175446796954e-05 & 0.99997409122766 \tabularnewline
86 & 2.4400518801261e-05 & 4.88010376025221e-05 & 0.999975599481199 \tabularnewline
87 & 5.7240982717935e-05 & 0.00011448196543587 & 0.999942759017282 \tabularnewline
88 & 8.24871894986418e-05 & 0.000164974378997284 & 0.999917512810501 \tabularnewline
89 & 5.44738584356775e-05 & 0.000108947716871355 & 0.999945526141564 \tabularnewline
90 & 5.33138979387105e-05 & 0.000106627795877421 & 0.999946686102061 \tabularnewline
91 & 3.79239729963593e-05 & 7.58479459927186e-05 & 0.999962076027004 \tabularnewline
92 & 2.96376702140813e-05 & 5.92753404281626e-05 & 0.999970362329786 \tabularnewline
93 & 2.18262880808386e-05 & 4.36525761616773e-05 & 0.999978173711919 \tabularnewline
94 & 3.75812182524299e-05 & 7.51624365048598e-05 & 0.999962418781748 \tabularnewline
95 & 3.22062926931396e-05 & 6.44125853862791e-05 & 0.999967793707307 \tabularnewline
96 & 2.87591107838081e-05 & 5.75182215676162e-05 & 0.999971240889216 \tabularnewline
97 & 3.2723042417842e-05 & 6.5446084835684e-05 & 0.999967276957582 \tabularnewline
98 & 3.13708633019331e-05 & 6.27417266038662e-05 & 0.999968629136698 \tabularnewline
99 & 2.59533620330195e-05 & 5.19067240660389e-05 & 0.999974046637967 \tabularnewline
100 & 1.71410000390958e-05 & 3.42820000781916e-05 & 0.999982858999961 \tabularnewline
101 & 1.24433613284887e-05 & 2.48867226569774e-05 & 0.999987556638672 \tabularnewline
102 & 1.58360078593424e-05 & 3.16720157186849e-05 & 0.999984163992141 \tabularnewline
103 & 1.62713805597653e-05 & 3.25427611195306e-05 & 0.99998372861944 \tabularnewline
104 & 1.89671099421696e-05 & 3.79342198843391e-05 & 0.999981032890058 \tabularnewline
105 & 0.00121274596158852 & 0.00242549192317704 & 0.998787254038412 \tabularnewline
106 & 0.00118194615102124 & 0.00236389230204248 & 0.998818053848979 \tabularnewline
107 & 0.000906077414651505 & 0.00181215482930301 & 0.999093922585348 \tabularnewline
108 & 0.001064613723139 & 0.00212922744627801 & 0.998935386276861 \tabularnewline
109 & 0.00139408111698478 & 0.00278816223396956 & 0.998605918883015 \tabularnewline
110 & 0.00447177445785721 & 0.00894354891571441 & 0.995528225542143 \tabularnewline
111 & 0.00903941499383789 & 0.0180788299876758 & 0.990960585006162 \tabularnewline
112 & 0.0108391362835793 & 0.0216782725671586 & 0.989160863716421 \tabularnewline
113 & 0.00853838971708921 & 0.0170767794341784 & 0.991461610282911 \tabularnewline
114 & 0.00754866042333858 & 0.0150973208466772 & 0.992451339576661 \tabularnewline
115 & 0.00589494913235956 & 0.0117898982647191 & 0.99410505086764 \tabularnewline
116 & 0.00547394773361104 & 0.0109478954672221 & 0.994526052266389 \tabularnewline
117 & 0.00517454084951319 & 0.0103490816990264 & 0.994825459150487 \tabularnewline
118 & 0.00431808288428113 & 0.00863616576856227 & 0.995681917115719 \tabularnewline
119 & 0.00333325430811478 & 0.00666650861622956 & 0.996666745691885 \tabularnewline
120 & 0.00288133246450161 & 0.00576266492900322 & 0.997118667535498 \tabularnewline
121 & 0.00382180547390413 & 0.00764361094780825 & 0.996178194526096 \tabularnewline
122 & 0.00393677323357583 & 0.00787354646715165 & 0.996063226766424 \tabularnewline
123 & 0.00309350356090511 & 0.00618700712181022 & 0.996906496439095 \tabularnewline
124 & 0.00289124643066274 & 0.00578249286132548 & 0.997108753569337 \tabularnewline
125 & 0.00332197838151436 & 0.00664395676302872 & 0.996678021618486 \tabularnewline
126 & 0.00267484054178383 & 0.00534968108356766 & 0.997325159458216 \tabularnewline
127 & 0.00234730421560337 & 0.00469460843120674 & 0.997652695784397 \tabularnewline
128 & 0.0020405332981698 & 0.0040810665963396 & 0.99795946670183 \tabularnewline
129 & 0.00155772132378625 & 0.0031154426475725 & 0.998442278676214 \tabularnewline
130 & 0.00288676255383052 & 0.00577352510766104 & 0.99711323744617 \tabularnewline
131 & 0.00348923253184468 & 0.00697846506368936 & 0.996510767468155 \tabularnewline
132 & 0.00501312496775031 & 0.0100262499355006 & 0.99498687503225 \tabularnewline
133 & 0.00398191634540324 & 0.00796383269080649 & 0.996018083654597 \tabularnewline
134 & 0.00306191520956741 & 0.00612383041913482 & 0.996938084790433 \tabularnewline
135 & 0.00274751453079163 & 0.00549502906158326 & 0.997252485469208 \tabularnewline
136 & 0.00213653426725323 & 0.00427306853450647 & 0.997863465732747 \tabularnewline
137 & 0.00162451571876487 & 0.00324903143752973 & 0.998375484281235 \tabularnewline
138 & 0.00125674956264542 & 0.00251349912529083 & 0.998743250437355 \tabularnewline
139 & 0.00113022079151303 & 0.00226044158302607 & 0.998869779208487 \tabularnewline
140 & 0.0010730194652332 & 0.0021460389304664 & 0.998926980534767 \tabularnewline
141 & 0.000860712116368893 & 0.00172142423273779 & 0.999139287883631 \tabularnewline
142 & 0.000636646585902905 & 0.00127329317180581 & 0.999363353414097 \tabularnewline
143 & 0.000470099981202885 & 0.000940199962405769 & 0.999529900018797 \tabularnewline
144 & 0.000457480810834199 & 0.000914961621668397 & 0.999542519189166 \tabularnewline
145 & 0.00036931142775202 & 0.00073862285550404 & 0.999630688572248 \tabularnewline
146 & 0.000266076784214766 & 0.000532153568429532 & 0.999733923215785 \tabularnewline
147 & 0.000193081397896953 & 0.000386162795793906 & 0.999806918602103 \tabularnewline
148 & 0.000137643648159196 & 0.000275287296318393 & 0.999862356351841 \tabularnewline
149 & 9.68980732576338e-05 & 0.000193796146515268 & 0.999903101926742 \tabularnewline
150 & 0.000104694322146795 & 0.000209388644293591 & 0.999895305677853 \tabularnewline
151 & 8.06341547088579e-05 & 0.000161268309417716 & 0.999919365845291 \tabularnewline
152 & 6.34457061524601e-05 & 0.00012689141230492 & 0.999936554293848 \tabularnewline
153 & 8.79761802473512e-05 & 0.000175952360494702 & 0.999912023819753 \tabularnewline
154 & 6.45605481143216e-05 & 0.000129121096228643 & 0.999935439451886 \tabularnewline
155 & 5.84794971108344e-05 & 0.000116958994221669 & 0.999941520502889 \tabularnewline
156 & 7.1504541800709e-05 & 0.000143009083601418 & 0.999928495458199 \tabularnewline
157 & 5.09526996085128e-05 & 0.000101905399217026 & 0.999949047300391 \tabularnewline
158 & 8.11081482272301e-05 & 0.00016221629645446 & 0.999918891851773 \tabularnewline
159 & 6.14106562821343e-05 & 0.000122821312564269 & 0.999938589343718 \tabularnewline
160 & 5.19400362378163e-05 & 0.000103880072475633 & 0.999948059963762 \tabularnewline
161 & 6.46325544018118e-05 & 0.000129265108803624 & 0.999935367445598 \tabularnewline
162 & 4.67473855918125e-05 & 9.34947711836249e-05 & 0.999953252614408 \tabularnewline
163 & 3.66570775544179e-05 & 7.33141551088358e-05 & 0.999963342922446 \tabularnewline
164 & 2.60796762357177e-05 & 5.21593524714355e-05 & 0.999973920323764 \tabularnewline
165 & 2.0633280496518e-05 & 4.12665609930359e-05 & 0.999979366719503 \tabularnewline
166 & 2.266283467393e-05 & 4.53256693478601e-05 & 0.999977337165326 \tabularnewline
167 & 3.26666485532015e-05 & 6.53332971064031e-05 & 0.999967333351447 \tabularnewline
168 & 3.04873460759515e-05 & 6.0974692151903e-05 & 0.999969512653924 \tabularnewline
169 & 2.86509561403382e-05 & 5.73019122806764e-05 & 0.99997134904386 \tabularnewline
170 & 0.000361375445195136 & 0.000722750890390272 & 0.999638624554805 \tabularnewline
171 & 0.00026809352533145 & 0.0005361870506629 & 0.999731906474669 \tabularnewline
172 & 0.000253859067310269 & 0.000507718134620538 & 0.99974614093269 \tabularnewline
173 & 0.000552300601826757 & 0.00110460120365351 & 0.999447699398173 \tabularnewline
174 & 0.000582470865891384 & 0.00116494173178277 & 0.999417529134109 \tabularnewline
175 & 0.000437303347127889 & 0.000874606694255779 & 0.999562696652872 \tabularnewline
176 & 0.000421740988177104 & 0.000843481976354208 & 0.999578259011823 \tabularnewline
177 & 0.000699971703712846 & 0.00139994340742569 & 0.999300028296287 \tabularnewline
178 & 0.00115443248715891 & 0.00230886497431782 & 0.998845567512841 \tabularnewline
179 & 0.000963781366864819 & 0.00192756273372964 & 0.999036218633135 \tabularnewline
180 & 0.000779003030591757 & 0.00155800606118351 & 0.999220996969408 \tabularnewline
181 & 0.000703345362286969 & 0.00140669072457394 & 0.999296654637713 \tabularnewline
182 & 0.000520640744358599 & 0.0010412814887172 & 0.999479359255641 \tabularnewline
183 & 0.000467797099984845 & 0.00093559419996969 & 0.999532202900015 \tabularnewline
184 & 0.000333847103038714 & 0.000667694206077429 & 0.999666152896961 \tabularnewline
185 & 0.00034910064087513 & 0.00069820128175026 & 0.999650899359125 \tabularnewline
186 & 0.000246920316243916 & 0.000493840632487833 & 0.999753079683756 \tabularnewline
187 & 0.000179340381099371 & 0.000358680762198742 & 0.999820659618901 \tabularnewline
188 & 0.000406852287423553 & 0.000813704574847105 & 0.999593147712576 \tabularnewline
189 & 0.000294673356190623 & 0.000589346712381247 & 0.999705326643809 \tabularnewline
190 & 0.000319891092157713 & 0.000639782184315426 & 0.999680108907842 \tabularnewline
191 & 0.000229777079967209 & 0.000459554159934417 & 0.999770222920033 \tabularnewline
192 & 0.000237853006112167 & 0.000475706012224333 & 0.999762146993888 \tabularnewline
193 & 0.000187808179737599 & 0.000375616359475198 & 0.999812191820262 \tabularnewline
194 & 0.000148863184839117 & 0.000297726369678234 & 0.999851136815161 \tabularnewline
195 & 0.000177382301417612 & 0.000354764602835224 & 0.999822617698582 \tabularnewline
196 & 0.000170836873861803 & 0.000341673747723605 & 0.999829163126138 \tabularnewline
197 & 0.00031253127094988 & 0.00062506254189976 & 0.99968746872905 \tabularnewline
198 & 0.000219856978433366 & 0.000439713956866732 & 0.999780143021567 \tabularnewline
199 & 0.000158788953037105 & 0.000317577906074211 & 0.999841211046963 \tabularnewline
200 & 0.000161355180828 & 0.000322710361656001 & 0.999838644819172 \tabularnewline
201 & 0.000111095123269655 & 0.00022219024653931 & 0.99988890487673 \tabularnewline
202 & 8.46707063989261e-05 & 0.000169341412797852 & 0.999915329293601 \tabularnewline
203 & 6.91856760066439e-05 & 0.000138371352013288 & 0.999930814323993 \tabularnewline
204 & 4.58111462498406e-05 & 9.16222924996812e-05 & 0.99995418885375 \tabularnewline
205 & 3.68323564115782e-05 & 7.36647128231564e-05 & 0.999963167643588 \tabularnewline
206 & 3.91945826166519e-05 & 7.83891652333039e-05 & 0.999960805417383 \tabularnewline
207 & 3.20533543662192e-05 & 6.41067087324385e-05 & 0.999967946645634 \tabularnewline
208 & 5.50624443351996e-05 & 0.000110124888670399 & 0.999944937555665 \tabularnewline
209 & 7.29362495164073e-05 & 0.000145872499032815 & 0.999927063750484 \tabularnewline
210 & 9.17270076246863e-05 & 0.000183454015249373 & 0.999908272992375 \tabularnewline
211 & 6.19965812895759e-05 & 0.000123993162579152 & 0.99993800341871 \tabularnewline
212 & 4.0178198447871e-05 & 8.0356396895742e-05 & 0.999959821801552 \tabularnewline
213 & 0.000209725288412589 & 0.000419450576825179 & 0.999790274711587 \tabularnewline
214 & 0.000213935058825179 & 0.000427870117650358 & 0.999786064941175 \tabularnewline
215 & 0.00015907669735341 & 0.000318153394706819 & 0.999840923302647 \tabularnewline
216 & 0.000137575979758326 & 0.000275151959516653 & 0.999862424020242 \tabularnewline
217 & 0.000111703074893053 & 0.000223406149786107 & 0.999888296925107 \tabularnewline
218 & 7.19470580748937e-05 & 0.000143894116149787 & 0.999928052941925 \tabularnewline
219 & 0.00014528012151597 & 0.00029056024303194 & 0.999854719878484 \tabularnewline
220 & 0.000719689852346779 & 0.00143937970469356 & 0.999280310147653 \tabularnewline
221 & 0.000565129445865618 & 0.00113025889173124 & 0.999434870554134 \tabularnewline
222 & 0.0833857965225411 & 0.166771593045082 & 0.916614203477459 \tabularnewline
223 & 0.0661362601138341 & 0.132272520227668 & 0.933863739886166 \tabularnewline
224 & 0.108142790152443 & 0.216285580304885 & 0.891857209847557 \tabularnewline
225 & 0.0898813555449899 & 0.17976271108998 & 0.91011864445501 \tabularnewline
226 & 0.0752004896275801 & 0.15040097925516 & 0.92479951037242 \tabularnewline
227 & 0.213057095892637 & 0.426114191785274 & 0.786942904107363 \tabularnewline
228 & 0.219397628458833 & 0.438795256917666 & 0.780602371541167 \tabularnewline
229 & 0.195632570662921 & 0.391265141325842 & 0.804367429337079 \tabularnewline
230 & 0.27274586902641 & 0.54549173805282 & 0.72725413097359 \tabularnewline
231 & 0.232355217121272 & 0.464710434242544 & 0.767644782878728 \tabularnewline
232 & 0.20613414632457 & 0.41226829264914 & 0.79386585367543 \tabularnewline
233 & 0.379235668045002 & 0.758471336090004 & 0.620764331954998 \tabularnewline
234 & 0.409850493690572 & 0.819700987381144 & 0.590149506309428 \tabularnewline
235 & 0.376146150572795 & 0.752292301145589 & 0.623853849427205 \tabularnewline
236 & 0.357926476523699 & 0.715852953047398 & 0.642073523476301 \tabularnewline
237 & 0.307225232646737 & 0.614450465293474 & 0.692774767353263 \tabularnewline
238 & 0.27740241594546 & 0.554804831890921 & 0.72259758405454 \tabularnewline
239 & 0.245067681141966 & 0.490135362283932 & 0.754932318858034 \tabularnewline
240 & 0.195490655698257 & 0.390981311396515 & 0.804509344301743 \tabularnewline
241 & 0.153437798005265 & 0.306875596010531 & 0.846562201994735 \tabularnewline
242 & 0.117392944599027 & 0.234785889198054 & 0.882607055400973 \tabularnewline
243 & 0.0947173279093044 & 0.189434655818609 & 0.905282672090696 \tabularnewline
244 & 0.072021084386304 & 0.144042168772608 & 0.927978915613696 \tabularnewline
245 & 0.154016761682892 & 0.308033523365784 & 0.845983238317108 \tabularnewline
246 & 0.132737804832534 & 0.265475609665068 & 0.867262195167466 \tabularnewline
247 & 0.125606429673233 & 0.251212859346467 & 0.874393570326766 \tabularnewline
248 & 0.0892605713290613 & 0.178521142658123 & 0.910739428670939 \tabularnewline
249 & 0.13946718925086 & 0.27893437850172 & 0.86053281074914 \tabularnewline
250 & 0.125539607064094 & 0.251079214128187 & 0.874460392935906 \tabularnewline
251 & 0.358340231506618 & 0.716680463013236 & 0.641659768493382 \tabularnewline
252 & 0.260166144808186 & 0.520332289616373 & 0.739833855191814 \tabularnewline
253 & 0.25566019555414 & 0.511320391108281 & 0.74433980444586 \tabularnewline
254 & 0.262379093845625 & 0.52475818769125 & 0.737620906154375 \tabularnewline
255 & 0.16528712443036 & 0.330574248860721 & 0.83471287556964 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195409&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]14[/C][C]0.724677017376513[/C][C]0.550645965246974[/C][C]0.275322982623487[/C][/ROW]
[ROW][C]15[/C][C]0.612813575229973[/C][C]0.774372849540054[/C][C]0.387186424770027[/C][/ROW]
[ROW][C]16[/C][C]0.517681798494592[/C][C]0.964636403010817[/C][C]0.482318201505408[/C][/ROW]
[ROW][C]17[/C][C]0.388505178927136[/C][C]0.777010357854272[/C][C]0.611494821072864[/C][/ROW]
[ROW][C]18[/C][C]0.284868453643245[/C][C]0.56973690728649[/C][C]0.715131546356755[/C][/ROW]
[ROW][C]19[/C][C]0.243115455915329[/C][C]0.486230911830658[/C][C]0.756884544084671[/C][/ROW]
[ROW][C]20[/C][C]0.175072064280869[/C][C]0.350144128561737[/C][C]0.824927935719131[/C][/ROW]
[ROW][C]21[/C][C]0.147207292441205[/C][C]0.294414584882411[/C][C]0.852792707558795[/C][/ROW]
[ROW][C]22[/C][C]0.230985243216543[/C][C]0.461970486433087[/C][C]0.769014756783457[/C][/ROW]
[ROW][C]23[/C][C]0.1690364230592[/C][C]0.338072846118399[/C][C]0.8309635769408[/C][/ROW]
[ROW][C]24[/C][C]0.11995906326934[/C][C]0.239918126538681[/C][C]0.88004093673066[/C][/ROW]
[ROW][C]25[/C][C]0.0842134225910955[/C][C]0.168426845182191[/C][C]0.915786577408904[/C][/ROW]
[ROW][C]26[/C][C]0.0568343527904148[/C][C]0.11366870558083[/C][C]0.943165647209585[/C][/ROW]
[ROW][C]27[/C][C]0.0461257656244542[/C][C]0.0922515312489084[/C][C]0.953874234375546[/C][/ROW]
[ROW][C]28[/C][C]0.0313322553746169[/C][C]0.0626645107492338[/C][C]0.968667744625383[/C][/ROW]
[ROW][C]29[/C][C]0.0231617431787784[/C][C]0.0463234863575569[/C][C]0.976838256821222[/C][/ROW]
[ROW][C]30[/C][C]0.0172741553776257[/C][C]0.0345483107552514[/C][C]0.982725844622374[/C][/ROW]
[ROW][C]31[/C][C]0.027899251397294[/C][C]0.055798502794588[/C][C]0.972100748602706[/C][/ROW]
[ROW][C]32[/C][C]0.0182329357495709[/C][C]0.0364658714991417[/C][C]0.981767064250429[/C][/ROW]
[ROW][C]33[/C][C]0.01574530472945[/C][C]0.0314906094589001[/C][C]0.98425469527055[/C][/ROW]
[ROW][C]34[/C][C]0.011484062229176[/C][C]0.022968124458352[/C][C]0.988515937770824[/C][/ROW]
[ROW][C]35[/C][C]0.0104990105302533[/C][C]0.0209980210605067[/C][C]0.989500989469747[/C][/ROW]
[ROW][C]36[/C][C]0.00990839461346212[/C][C]0.0198167892269242[/C][C]0.990091605386538[/C][/ROW]
[ROW][C]37[/C][C]0.00855789039204392[/C][C]0.0171157807840878[/C][C]0.991442109607956[/C][/ROW]
[ROW][C]38[/C][C]0.00800188092188153[/C][C]0.0160037618437631[/C][C]0.991998119078118[/C][/ROW]
[ROW][C]39[/C][C]0.00944893667377254[/C][C]0.0188978733475451[/C][C]0.990551063326227[/C][/ROW]
[ROW][C]40[/C][C]0.0117126411924256[/C][C]0.0234252823848512[/C][C]0.988287358807574[/C][/ROW]
[ROW][C]41[/C][C]0.00779935291961345[/C][C]0.0155987058392269[/C][C]0.992200647080387[/C][/ROW]
[ROW][C]42[/C][C]0.0127888422133856[/C][C]0.0255776844267712[/C][C]0.987211157786614[/C][/ROW]
[ROW][C]43[/C][C]0.0100451490954293[/C][C]0.0200902981908586[/C][C]0.989954850904571[/C][/ROW]
[ROW][C]44[/C][C]0.00806065016218893[/C][C]0.0161213003243779[/C][C]0.991939349837811[/C][/ROW]
[ROW][C]45[/C][C]0.0258623020511744[/C][C]0.0517246041023487[/C][C]0.974137697948826[/C][/ROW]
[ROW][C]46[/C][C]0.0203509821467512[/C][C]0.0407019642935024[/C][C]0.979649017853249[/C][/ROW]
[ROW][C]47[/C][C]0.0145121838619789[/C][C]0.0290243677239578[/C][C]0.985487816138021[/C][/ROW]
[ROW][C]48[/C][C]0.0103813076355554[/C][C]0.0207626152711108[/C][C]0.989618692364445[/C][/ROW]
[ROW][C]49[/C][C]0.00724744686967352[/C][C]0.014494893739347[/C][C]0.992752553130327[/C][/ROW]
[ROW][C]50[/C][C]0.00519542779988826[/C][C]0.0103908555997765[/C][C]0.994804572200112[/C][/ROW]
[ROW][C]51[/C][C]0.00395871881854024[/C][C]0.00791743763708048[/C][C]0.99604128118146[/C][/ROW]
[ROW][C]52[/C][C]0.00536316362088268[/C][C]0.0107263272417654[/C][C]0.994636836379117[/C][/ROW]
[ROW][C]53[/C][C]0.00553625951996787[/C][C]0.0110725190399357[/C][C]0.994463740480032[/C][/ROW]
[ROW][C]54[/C][C]0.00408528368995349[/C][C]0.00817056737990698[/C][C]0.995914716310046[/C][/ROW]
[ROW][C]55[/C][C]0.00282449506596485[/C][C]0.0056489901319297[/C][C]0.997175504934035[/C][/ROW]
[ROW][C]56[/C][C]0.0100244018263027[/C][C]0.0200488036526055[/C][C]0.989975598173697[/C][/ROW]
[ROW][C]57[/C][C]0.00728978201039637[/C][C]0.0145795640207927[/C][C]0.992710217989604[/C][/ROW]
[ROW][C]58[/C][C]0.00531979678249073[/C][C]0.0106395935649815[/C][C]0.994680203217509[/C][/ROW]
[ROW][C]59[/C][C]0.00573347785629145[/C][C]0.0114669557125829[/C][C]0.994266522143709[/C][/ROW]
[ROW][C]60[/C][C]0.00473859931647398[/C][C]0.00947719863294797[/C][C]0.995261400683526[/C][/ROW]
[ROW][C]61[/C][C]0.00338572976379608[/C][C]0.00677145952759216[/C][C]0.996614270236204[/C][/ROW]
[ROW][C]62[/C][C]0.00256411595607644[/C][C]0.00512823191215289[/C][C]0.997435884043924[/C][/ROW]
[ROW][C]63[/C][C]0.00179235503518222[/C][C]0.00358471007036444[/C][C]0.998207644964818[/C][/ROW]
[ROW][C]64[/C][C]0.00123371864065729[/C][C]0.00246743728131459[/C][C]0.998766281359343[/C][/ROW]
[ROW][C]65[/C][C]0.00212189123848556[/C][C]0.00424378247697112[/C][C]0.997878108761514[/C][/ROW]
[ROW][C]66[/C][C]0.00205206489752582[/C][C]0.00410412979505163[/C][C]0.997947935102474[/C][/ROW]
[ROW][C]67[/C][C]0.00141434266205746[/C][C]0.00282868532411492[/C][C]0.998585657337943[/C][/ROW]
[ROW][C]68[/C][C]0.000965023216047472[/C][C]0.00193004643209494[/C][C]0.999034976783952[/C][/ROW]
[ROW][C]69[/C][C]0.000652599577916811[/C][C]0.00130519915583362[/C][C]0.999347400422083[/C][/ROW]
[ROW][C]70[/C][C]0.00187247889263186[/C][C]0.00374495778526371[/C][C]0.998127521107368[/C][/ROW]
[ROW][C]71[/C][C]0.00135072415034315[/C][C]0.00270144830068629[/C][C]0.998649275849657[/C][/ROW]
[ROW][C]72[/C][C]0.000951900358735663[/C][C]0.00190380071747133[/C][C]0.999048099641264[/C][/ROW]
[ROW][C]73[/C][C]0.000695105895039282[/C][C]0.00139021179007856[/C][C]0.999304894104961[/C][/ROW]
[ROW][C]74[/C][C]0.000477466440802114[/C][C]0.000954932881604229[/C][C]0.999522533559198[/C][/ROW]
[ROW][C]75[/C][C]0.00032200865500221[/C][C]0.00064401731000442[/C][C]0.999677991344998[/C][/ROW]
[ROW][C]76[/C][C]0.000250347641520074[/C][C]0.000500695283040149[/C][C]0.99974965235848[/C][/ROW]
[ROW][C]77[/C][C]0.000166045795385004[/C][C]0.000332091590770008[/C][C]0.999833954204615[/C][/ROW]
[ROW][C]78[/C][C]0.000136124604248503[/C][C]0.000272249208497006[/C][C]0.999863875395752[/C][/ROW]
[ROW][C]79[/C][C]9.25225993484468e-05[/C][C]0.000185045198696894[/C][C]0.999907477400652[/C][/ROW]
[ROW][C]80[/C][C]6.29984393186404e-05[/C][C]0.000125996878637281[/C][C]0.999937001560681[/C][/ROW]
[ROW][C]81[/C][C]4.46836174325864e-05[/C][C]8.93672348651728e-05[/C][C]0.999955316382567[/C][/ROW]
[ROW][C]82[/C][C]5.18134400992013e-05[/C][C]0.000103626880198403[/C][C]0.999948186559901[/C][/ROW]
[ROW][C]83[/C][C]4.80184585212901e-05[/C][C]9.60369170425801e-05[/C][C]0.999951981541479[/C][/ROW]
[ROW][C]84[/C][C]4.01063229430512e-05[/C][C]8.02126458861025e-05[/C][C]0.999959893677057[/C][/ROW]
[ROW][C]85[/C][C]2.59087723398477e-05[/C][C]5.18175446796954e-05[/C][C]0.99997409122766[/C][/ROW]
[ROW][C]86[/C][C]2.4400518801261e-05[/C][C]4.88010376025221e-05[/C][C]0.999975599481199[/C][/ROW]
[ROW][C]87[/C][C]5.7240982717935e-05[/C][C]0.00011448196543587[/C][C]0.999942759017282[/C][/ROW]
[ROW][C]88[/C][C]8.24871894986418e-05[/C][C]0.000164974378997284[/C][C]0.999917512810501[/C][/ROW]
[ROW][C]89[/C][C]5.44738584356775e-05[/C][C]0.000108947716871355[/C][C]0.999945526141564[/C][/ROW]
[ROW][C]90[/C][C]5.33138979387105e-05[/C][C]0.000106627795877421[/C][C]0.999946686102061[/C][/ROW]
[ROW][C]91[/C][C]3.79239729963593e-05[/C][C]7.58479459927186e-05[/C][C]0.999962076027004[/C][/ROW]
[ROW][C]92[/C][C]2.96376702140813e-05[/C][C]5.92753404281626e-05[/C][C]0.999970362329786[/C][/ROW]
[ROW][C]93[/C][C]2.18262880808386e-05[/C][C]4.36525761616773e-05[/C][C]0.999978173711919[/C][/ROW]
[ROW][C]94[/C][C]3.75812182524299e-05[/C][C]7.51624365048598e-05[/C][C]0.999962418781748[/C][/ROW]
[ROW][C]95[/C][C]3.22062926931396e-05[/C][C]6.44125853862791e-05[/C][C]0.999967793707307[/C][/ROW]
[ROW][C]96[/C][C]2.87591107838081e-05[/C][C]5.75182215676162e-05[/C][C]0.999971240889216[/C][/ROW]
[ROW][C]97[/C][C]3.2723042417842e-05[/C][C]6.5446084835684e-05[/C][C]0.999967276957582[/C][/ROW]
[ROW][C]98[/C][C]3.13708633019331e-05[/C][C]6.27417266038662e-05[/C][C]0.999968629136698[/C][/ROW]
[ROW][C]99[/C][C]2.59533620330195e-05[/C][C]5.19067240660389e-05[/C][C]0.999974046637967[/C][/ROW]
[ROW][C]100[/C][C]1.71410000390958e-05[/C][C]3.42820000781916e-05[/C][C]0.999982858999961[/C][/ROW]
[ROW][C]101[/C][C]1.24433613284887e-05[/C][C]2.48867226569774e-05[/C][C]0.999987556638672[/C][/ROW]
[ROW][C]102[/C][C]1.58360078593424e-05[/C][C]3.16720157186849e-05[/C][C]0.999984163992141[/C][/ROW]
[ROW][C]103[/C][C]1.62713805597653e-05[/C][C]3.25427611195306e-05[/C][C]0.99998372861944[/C][/ROW]
[ROW][C]104[/C][C]1.89671099421696e-05[/C][C]3.79342198843391e-05[/C][C]0.999981032890058[/C][/ROW]
[ROW][C]105[/C][C]0.00121274596158852[/C][C]0.00242549192317704[/C][C]0.998787254038412[/C][/ROW]
[ROW][C]106[/C][C]0.00118194615102124[/C][C]0.00236389230204248[/C][C]0.998818053848979[/C][/ROW]
[ROW][C]107[/C][C]0.000906077414651505[/C][C]0.00181215482930301[/C][C]0.999093922585348[/C][/ROW]
[ROW][C]108[/C][C]0.001064613723139[/C][C]0.00212922744627801[/C][C]0.998935386276861[/C][/ROW]
[ROW][C]109[/C][C]0.00139408111698478[/C][C]0.00278816223396956[/C][C]0.998605918883015[/C][/ROW]
[ROW][C]110[/C][C]0.00447177445785721[/C][C]0.00894354891571441[/C][C]0.995528225542143[/C][/ROW]
[ROW][C]111[/C][C]0.00903941499383789[/C][C]0.0180788299876758[/C][C]0.990960585006162[/C][/ROW]
[ROW][C]112[/C][C]0.0108391362835793[/C][C]0.0216782725671586[/C][C]0.989160863716421[/C][/ROW]
[ROW][C]113[/C][C]0.00853838971708921[/C][C]0.0170767794341784[/C][C]0.991461610282911[/C][/ROW]
[ROW][C]114[/C][C]0.00754866042333858[/C][C]0.0150973208466772[/C][C]0.992451339576661[/C][/ROW]
[ROW][C]115[/C][C]0.00589494913235956[/C][C]0.0117898982647191[/C][C]0.99410505086764[/C][/ROW]
[ROW][C]116[/C][C]0.00547394773361104[/C][C]0.0109478954672221[/C][C]0.994526052266389[/C][/ROW]
[ROW][C]117[/C][C]0.00517454084951319[/C][C]0.0103490816990264[/C][C]0.994825459150487[/C][/ROW]
[ROW][C]118[/C][C]0.00431808288428113[/C][C]0.00863616576856227[/C][C]0.995681917115719[/C][/ROW]
[ROW][C]119[/C][C]0.00333325430811478[/C][C]0.00666650861622956[/C][C]0.996666745691885[/C][/ROW]
[ROW][C]120[/C][C]0.00288133246450161[/C][C]0.00576266492900322[/C][C]0.997118667535498[/C][/ROW]
[ROW][C]121[/C][C]0.00382180547390413[/C][C]0.00764361094780825[/C][C]0.996178194526096[/C][/ROW]
[ROW][C]122[/C][C]0.00393677323357583[/C][C]0.00787354646715165[/C][C]0.996063226766424[/C][/ROW]
[ROW][C]123[/C][C]0.00309350356090511[/C][C]0.00618700712181022[/C][C]0.996906496439095[/C][/ROW]
[ROW][C]124[/C][C]0.00289124643066274[/C][C]0.00578249286132548[/C][C]0.997108753569337[/C][/ROW]
[ROW][C]125[/C][C]0.00332197838151436[/C][C]0.00664395676302872[/C][C]0.996678021618486[/C][/ROW]
[ROW][C]126[/C][C]0.00267484054178383[/C][C]0.00534968108356766[/C][C]0.997325159458216[/C][/ROW]
[ROW][C]127[/C][C]0.00234730421560337[/C][C]0.00469460843120674[/C][C]0.997652695784397[/C][/ROW]
[ROW][C]128[/C][C]0.0020405332981698[/C][C]0.0040810665963396[/C][C]0.99795946670183[/C][/ROW]
[ROW][C]129[/C][C]0.00155772132378625[/C][C]0.0031154426475725[/C][C]0.998442278676214[/C][/ROW]
[ROW][C]130[/C][C]0.00288676255383052[/C][C]0.00577352510766104[/C][C]0.99711323744617[/C][/ROW]
[ROW][C]131[/C][C]0.00348923253184468[/C][C]0.00697846506368936[/C][C]0.996510767468155[/C][/ROW]
[ROW][C]132[/C][C]0.00501312496775031[/C][C]0.0100262499355006[/C][C]0.99498687503225[/C][/ROW]
[ROW][C]133[/C][C]0.00398191634540324[/C][C]0.00796383269080649[/C][C]0.996018083654597[/C][/ROW]
[ROW][C]134[/C][C]0.00306191520956741[/C][C]0.00612383041913482[/C][C]0.996938084790433[/C][/ROW]
[ROW][C]135[/C][C]0.00274751453079163[/C][C]0.00549502906158326[/C][C]0.997252485469208[/C][/ROW]
[ROW][C]136[/C][C]0.00213653426725323[/C][C]0.00427306853450647[/C][C]0.997863465732747[/C][/ROW]
[ROW][C]137[/C][C]0.00162451571876487[/C][C]0.00324903143752973[/C][C]0.998375484281235[/C][/ROW]
[ROW][C]138[/C][C]0.00125674956264542[/C][C]0.00251349912529083[/C][C]0.998743250437355[/C][/ROW]
[ROW][C]139[/C][C]0.00113022079151303[/C][C]0.00226044158302607[/C][C]0.998869779208487[/C][/ROW]
[ROW][C]140[/C][C]0.0010730194652332[/C][C]0.0021460389304664[/C][C]0.998926980534767[/C][/ROW]
[ROW][C]141[/C][C]0.000860712116368893[/C][C]0.00172142423273779[/C][C]0.999139287883631[/C][/ROW]
[ROW][C]142[/C][C]0.000636646585902905[/C][C]0.00127329317180581[/C][C]0.999363353414097[/C][/ROW]
[ROW][C]143[/C][C]0.000470099981202885[/C][C]0.000940199962405769[/C][C]0.999529900018797[/C][/ROW]
[ROW][C]144[/C][C]0.000457480810834199[/C][C]0.000914961621668397[/C][C]0.999542519189166[/C][/ROW]
[ROW][C]145[/C][C]0.00036931142775202[/C][C]0.00073862285550404[/C][C]0.999630688572248[/C][/ROW]
[ROW][C]146[/C][C]0.000266076784214766[/C][C]0.000532153568429532[/C][C]0.999733923215785[/C][/ROW]
[ROW][C]147[/C][C]0.000193081397896953[/C][C]0.000386162795793906[/C][C]0.999806918602103[/C][/ROW]
[ROW][C]148[/C][C]0.000137643648159196[/C][C]0.000275287296318393[/C][C]0.999862356351841[/C][/ROW]
[ROW][C]149[/C][C]9.68980732576338e-05[/C][C]0.000193796146515268[/C][C]0.999903101926742[/C][/ROW]
[ROW][C]150[/C][C]0.000104694322146795[/C][C]0.000209388644293591[/C][C]0.999895305677853[/C][/ROW]
[ROW][C]151[/C][C]8.06341547088579e-05[/C][C]0.000161268309417716[/C][C]0.999919365845291[/C][/ROW]
[ROW][C]152[/C][C]6.34457061524601e-05[/C][C]0.00012689141230492[/C][C]0.999936554293848[/C][/ROW]
[ROW][C]153[/C][C]8.79761802473512e-05[/C][C]0.000175952360494702[/C][C]0.999912023819753[/C][/ROW]
[ROW][C]154[/C][C]6.45605481143216e-05[/C][C]0.000129121096228643[/C][C]0.999935439451886[/C][/ROW]
[ROW][C]155[/C][C]5.84794971108344e-05[/C][C]0.000116958994221669[/C][C]0.999941520502889[/C][/ROW]
[ROW][C]156[/C][C]7.1504541800709e-05[/C][C]0.000143009083601418[/C][C]0.999928495458199[/C][/ROW]
[ROW][C]157[/C][C]5.09526996085128e-05[/C][C]0.000101905399217026[/C][C]0.999949047300391[/C][/ROW]
[ROW][C]158[/C][C]8.11081482272301e-05[/C][C]0.00016221629645446[/C][C]0.999918891851773[/C][/ROW]
[ROW][C]159[/C][C]6.14106562821343e-05[/C][C]0.000122821312564269[/C][C]0.999938589343718[/C][/ROW]
[ROW][C]160[/C][C]5.19400362378163e-05[/C][C]0.000103880072475633[/C][C]0.999948059963762[/C][/ROW]
[ROW][C]161[/C][C]6.46325544018118e-05[/C][C]0.000129265108803624[/C][C]0.999935367445598[/C][/ROW]
[ROW][C]162[/C][C]4.67473855918125e-05[/C][C]9.34947711836249e-05[/C][C]0.999953252614408[/C][/ROW]
[ROW][C]163[/C][C]3.66570775544179e-05[/C][C]7.33141551088358e-05[/C][C]0.999963342922446[/C][/ROW]
[ROW][C]164[/C][C]2.60796762357177e-05[/C][C]5.21593524714355e-05[/C][C]0.999973920323764[/C][/ROW]
[ROW][C]165[/C][C]2.0633280496518e-05[/C][C]4.12665609930359e-05[/C][C]0.999979366719503[/C][/ROW]
[ROW][C]166[/C][C]2.266283467393e-05[/C][C]4.53256693478601e-05[/C][C]0.999977337165326[/C][/ROW]
[ROW][C]167[/C][C]3.26666485532015e-05[/C][C]6.53332971064031e-05[/C][C]0.999967333351447[/C][/ROW]
[ROW][C]168[/C][C]3.04873460759515e-05[/C][C]6.0974692151903e-05[/C][C]0.999969512653924[/C][/ROW]
[ROW][C]169[/C][C]2.86509561403382e-05[/C][C]5.73019122806764e-05[/C][C]0.99997134904386[/C][/ROW]
[ROW][C]170[/C][C]0.000361375445195136[/C][C]0.000722750890390272[/C][C]0.999638624554805[/C][/ROW]
[ROW][C]171[/C][C]0.00026809352533145[/C][C]0.0005361870506629[/C][C]0.999731906474669[/C][/ROW]
[ROW][C]172[/C][C]0.000253859067310269[/C][C]0.000507718134620538[/C][C]0.99974614093269[/C][/ROW]
[ROW][C]173[/C][C]0.000552300601826757[/C][C]0.00110460120365351[/C][C]0.999447699398173[/C][/ROW]
[ROW][C]174[/C][C]0.000582470865891384[/C][C]0.00116494173178277[/C][C]0.999417529134109[/C][/ROW]
[ROW][C]175[/C][C]0.000437303347127889[/C][C]0.000874606694255779[/C][C]0.999562696652872[/C][/ROW]
[ROW][C]176[/C][C]0.000421740988177104[/C][C]0.000843481976354208[/C][C]0.999578259011823[/C][/ROW]
[ROW][C]177[/C][C]0.000699971703712846[/C][C]0.00139994340742569[/C][C]0.999300028296287[/C][/ROW]
[ROW][C]178[/C][C]0.00115443248715891[/C][C]0.00230886497431782[/C][C]0.998845567512841[/C][/ROW]
[ROW][C]179[/C][C]0.000963781366864819[/C][C]0.00192756273372964[/C][C]0.999036218633135[/C][/ROW]
[ROW][C]180[/C][C]0.000779003030591757[/C][C]0.00155800606118351[/C][C]0.999220996969408[/C][/ROW]
[ROW][C]181[/C][C]0.000703345362286969[/C][C]0.00140669072457394[/C][C]0.999296654637713[/C][/ROW]
[ROW][C]182[/C][C]0.000520640744358599[/C][C]0.0010412814887172[/C][C]0.999479359255641[/C][/ROW]
[ROW][C]183[/C][C]0.000467797099984845[/C][C]0.00093559419996969[/C][C]0.999532202900015[/C][/ROW]
[ROW][C]184[/C][C]0.000333847103038714[/C][C]0.000667694206077429[/C][C]0.999666152896961[/C][/ROW]
[ROW][C]185[/C][C]0.00034910064087513[/C][C]0.00069820128175026[/C][C]0.999650899359125[/C][/ROW]
[ROW][C]186[/C][C]0.000246920316243916[/C][C]0.000493840632487833[/C][C]0.999753079683756[/C][/ROW]
[ROW][C]187[/C][C]0.000179340381099371[/C][C]0.000358680762198742[/C][C]0.999820659618901[/C][/ROW]
[ROW][C]188[/C][C]0.000406852287423553[/C][C]0.000813704574847105[/C][C]0.999593147712576[/C][/ROW]
[ROW][C]189[/C][C]0.000294673356190623[/C][C]0.000589346712381247[/C][C]0.999705326643809[/C][/ROW]
[ROW][C]190[/C][C]0.000319891092157713[/C][C]0.000639782184315426[/C][C]0.999680108907842[/C][/ROW]
[ROW][C]191[/C][C]0.000229777079967209[/C][C]0.000459554159934417[/C][C]0.999770222920033[/C][/ROW]
[ROW][C]192[/C][C]0.000237853006112167[/C][C]0.000475706012224333[/C][C]0.999762146993888[/C][/ROW]
[ROW][C]193[/C][C]0.000187808179737599[/C][C]0.000375616359475198[/C][C]0.999812191820262[/C][/ROW]
[ROW][C]194[/C][C]0.000148863184839117[/C][C]0.000297726369678234[/C][C]0.999851136815161[/C][/ROW]
[ROW][C]195[/C][C]0.000177382301417612[/C][C]0.000354764602835224[/C][C]0.999822617698582[/C][/ROW]
[ROW][C]196[/C][C]0.000170836873861803[/C][C]0.000341673747723605[/C][C]0.999829163126138[/C][/ROW]
[ROW][C]197[/C][C]0.00031253127094988[/C][C]0.00062506254189976[/C][C]0.99968746872905[/C][/ROW]
[ROW][C]198[/C][C]0.000219856978433366[/C][C]0.000439713956866732[/C][C]0.999780143021567[/C][/ROW]
[ROW][C]199[/C][C]0.000158788953037105[/C][C]0.000317577906074211[/C][C]0.999841211046963[/C][/ROW]
[ROW][C]200[/C][C]0.000161355180828[/C][C]0.000322710361656001[/C][C]0.999838644819172[/C][/ROW]
[ROW][C]201[/C][C]0.000111095123269655[/C][C]0.00022219024653931[/C][C]0.99988890487673[/C][/ROW]
[ROW][C]202[/C][C]8.46707063989261e-05[/C][C]0.000169341412797852[/C][C]0.999915329293601[/C][/ROW]
[ROW][C]203[/C][C]6.91856760066439e-05[/C][C]0.000138371352013288[/C][C]0.999930814323993[/C][/ROW]
[ROW][C]204[/C][C]4.58111462498406e-05[/C][C]9.16222924996812e-05[/C][C]0.99995418885375[/C][/ROW]
[ROW][C]205[/C][C]3.68323564115782e-05[/C][C]7.36647128231564e-05[/C][C]0.999963167643588[/C][/ROW]
[ROW][C]206[/C][C]3.91945826166519e-05[/C][C]7.83891652333039e-05[/C][C]0.999960805417383[/C][/ROW]
[ROW][C]207[/C][C]3.20533543662192e-05[/C][C]6.41067087324385e-05[/C][C]0.999967946645634[/C][/ROW]
[ROW][C]208[/C][C]5.50624443351996e-05[/C][C]0.000110124888670399[/C][C]0.999944937555665[/C][/ROW]
[ROW][C]209[/C][C]7.29362495164073e-05[/C][C]0.000145872499032815[/C][C]0.999927063750484[/C][/ROW]
[ROW][C]210[/C][C]9.17270076246863e-05[/C][C]0.000183454015249373[/C][C]0.999908272992375[/C][/ROW]
[ROW][C]211[/C][C]6.19965812895759e-05[/C][C]0.000123993162579152[/C][C]0.99993800341871[/C][/ROW]
[ROW][C]212[/C][C]4.0178198447871e-05[/C][C]8.0356396895742e-05[/C][C]0.999959821801552[/C][/ROW]
[ROW][C]213[/C][C]0.000209725288412589[/C][C]0.000419450576825179[/C][C]0.999790274711587[/C][/ROW]
[ROW][C]214[/C][C]0.000213935058825179[/C][C]0.000427870117650358[/C][C]0.999786064941175[/C][/ROW]
[ROW][C]215[/C][C]0.00015907669735341[/C][C]0.000318153394706819[/C][C]0.999840923302647[/C][/ROW]
[ROW][C]216[/C][C]0.000137575979758326[/C][C]0.000275151959516653[/C][C]0.999862424020242[/C][/ROW]
[ROW][C]217[/C][C]0.000111703074893053[/C][C]0.000223406149786107[/C][C]0.999888296925107[/C][/ROW]
[ROW][C]218[/C][C]7.19470580748937e-05[/C][C]0.000143894116149787[/C][C]0.999928052941925[/C][/ROW]
[ROW][C]219[/C][C]0.00014528012151597[/C][C]0.00029056024303194[/C][C]0.999854719878484[/C][/ROW]
[ROW][C]220[/C][C]0.000719689852346779[/C][C]0.00143937970469356[/C][C]0.999280310147653[/C][/ROW]
[ROW][C]221[/C][C]0.000565129445865618[/C][C]0.00113025889173124[/C][C]0.999434870554134[/C][/ROW]
[ROW][C]222[/C][C]0.0833857965225411[/C][C]0.166771593045082[/C][C]0.916614203477459[/C][/ROW]
[ROW][C]223[/C][C]0.0661362601138341[/C][C]0.132272520227668[/C][C]0.933863739886166[/C][/ROW]
[ROW][C]224[/C][C]0.108142790152443[/C][C]0.216285580304885[/C][C]0.891857209847557[/C][/ROW]
[ROW][C]225[/C][C]0.0898813555449899[/C][C]0.17976271108998[/C][C]0.91011864445501[/C][/ROW]
[ROW][C]226[/C][C]0.0752004896275801[/C][C]0.15040097925516[/C][C]0.92479951037242[/C][/ROW]
[ROW][C]227[/C][C]0.213057095892637[/C][C]0.426114191785274[/C][C]0.786942904107363[/C][/ROW]
[ROW][C]228[/C][C]0.219397628458833[/C][C]0.438795256917666[/C][C]0.780602371541167[/C][/ROW]
[ROW][C]229[/C][C]0.195632570662921[/C][C]0.391265141325842[/C][C]0.804367429337079[/C][/ROW]
[ROW][C]230[/C][C]0.27274586902641[/C][C]0.54549173805282[/C][C]0.72725413097359[/C][/ROW]
[ROW][C]231[/C][C]0.232355217121272[/C][C]0.464710434242544[/C][C]0.767644782878728[/C][/ROW]
[ROW][C]232[/C][C]0.20613414632457[/C][C]0.41226829264914[/C][C]0.79386585367543[/C][/ROW]
[ROW][C]233[/C][C]0.379235668045002[/C][C]0.758471336090004[/C][C]0.620764331954998[/C][/ROW]
[ROW][C]234[/C][C]0.409850493690572[/C][C]0.819700987381144[/C][C]0.590149506309428[/C][/ROW]
[ROW][C]235[/C][C]0.376146150572795[/C][C]0.752292301145589[/C][C]0.623853849427205[/C][/ROW]
[ROW][C]236[/C][C]0.357926476523699[/C][C]0.715852953047398[/C][C]0.642073523476301[/C][/ROW]
[ROW][C]237[/C][C]0.307225232646737[/C][C]0.614450465293474[/C][C]0.692774767353263[/C][/ROW]
[ROW][C]238[/C][C]0.27740241594546[/C][C]0.554804831890921[/C][C]0.72259758405454[/C][/ROW]
[ROW][C]239[/C][C]0.245067681141966[/C][C]0.490135362283932[/C][C]0.754932318858034[/C][/ROW]
[ROW][C]240[/C][C]0.195490655698257[/C][C]0.390981311396515[/C][C]0.804509344301743[/C][/ROW]
[ROW][C]241[/C][C]0.153437798005265[/C][C]0.306875596010531[/C][C]0.846562201994735[/C][/ROW]
[ROW][C]242[/C][C]0.117392944599027[/C][C]0.234785889198054[/C][C]0.882607055400973[/C][/ROW]
[ROW][C]243[/C][C]0.0947173279093044[/C][C]0.189434655818609[/C][C]0.905282672090696[/C][/ROW]
[ROW][C]244[/C][C]0.072021084386304[/C][C]0.144042168772608[/C][C]0.927978915613696[/C][/ROW]
[ROW][C]245[/C][C]0.154016761682892[/C][C]0.308033523365784[/C][C]0.845983238317108[/C][/ROW]
[ROW][C]246[/C][C]0.132737804832534[/C][C]0.265475609665068[/C][C]0.867262195167466[/C][/ROW]
[ROW][C]247[/C][C]0.125606429673233[/C][C]0.251212859346467[/C][C]0.874393570326766[/C][/ROW]
[ROW][C]248[/C][C]0.0892605713290613[/C][C]0.178521142658123[/C][C]0.910739428670939[/C][/ROW]
[ROW][C]249[/C][C]0.13946718925086[/C][C]0.27893437850172[/C][C]0.86053281074914[/C][/ROW]
[ROW][C]250[/C][C]0.125539607064094[/C][C]0.251079214128187[/C][C]0.874460392935906[/C][/ROW]
[ROW][C]251[/C][C]0.358340231506618[/C][C]0.716680463013236[/C][C]0.641659768493382[/C][/ROW]
[ROW][C]252[/C][C]0.260166144808186[/C][C]0.520332289616373[/C][C]0.739833855191814[/C][/ROW]
[ROW][C]253[/C][C]0.25566019555414[/C][C]0.511320391108281[/C][C]0.74433980444586[/C][/ROW]
[ROW][C]254[/C][C]0.262379093845625[/C][C]0.52475818769125[/C][C]0.737620906154375[/C][/ROW]
[ROW][C]255[/C][C]0.16528712443036[/C][C]0.330574248860721[/C][C]0.83471287556964[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195409&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195409&T=5

As an alternative you can also use a QR Code:  
QR Code


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
140.7246770173765130.5506459652469740.275322982623487
150.6128135752299730.7743728495400540.387186424770027
160.5176817984945920.9646364030108170.482318201505408
170.3885051789271360.7770103578542720.611494821072864
180.2848684536432450.569736907286490.715131546356755
190.2431154559153290.4862309118306580.756884544084671
200.1750720642808690.3501441285617370.824927935719131
210.1472072924412050.2944145848824110.852792707558795
220.2309852432165430.4619704864330870.769014756783457
230.16903642305920.3380728461183990.8309635769408
240.119959063269340.2399181265386810.88004093673066
250.08421342259109550.1684268451821910.915786577408904
260.05683435279041480.113668705580830.943165647209585
270.04612576562445420.09225153124890840.953874234375546
280.03133225537461690.06266451074923380.968667744625383
290.02316174317877840.04632348635755690.976838256821222
300.01727415537762570.03454831075525140.982725844622374
310.0278992513972940.0557985027945880.972100748602706
320.01823293574957090.03646587149914170.981767064250429
330.015745304729450.03149060945890010.98425469527055
340.0114840622291760.0229681244583520.988515937770824
350.01049901053025330.02099802106050670.989500989469747
360.009908394613462120.01981678922692420.990091605386538
370.008557890392043920.01711578078408780.991442109607956
380.008001880921881530.01600376184376310.991998119078118
390.009448936673772540.01889787334754510.990551063326227
400.01171264119242560.02342528238485120.988287358807574
410.007799352919613450.01559870583922690.992200647080387
420.01278884221338560.02557768442677120.987211157786614
430.01004514909542930.02009029819085860.989954850904571
440.008060650162188930.01612130032437790.991939349837811
450.02586230205117440.05172460410234870.974137697948826
460.02035098214675120.04070196429350240.979649017853249
470.01451218386197890.02902436772395780.985487816138021
480.01038130763555540.02076261527111080.989618692364445
490.007247446869673520.0144948937393470.992752553130327
500.005195427799888260.01039085559977650.994804572200112
510.003958718818540240.007917437637080480.99604128118146
520.005363163620882680.01072632724176540.994636836379117
530.005536259519967870.01107251903993570.994463740480032
540.004085283689953490.008170567379906980.995914716310046
550.002824495065964850.00564899013192970.997175504934035
560.01002440182630270.02004880365260550.989975598173697
570.007289782010396370.01457956402079270.992710217989604
580.005319796782490730.01063959356498150.994680203217509
590.005733477856291450.01146695571258290.994266522143709
600.004738599316473980.009477198632947970.995261400683526
610.003385729763796080.006771459527592160.996614270236204
620.002564115956076440.005128231912152890.997435884043924
630.001792355035182220.003584710070364440.998207644964818
640.001233718640657290.002467437281314590.998766281359343
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1880.0004068522874235530.0008137045748471050.999593147712576
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1900.0003198910921577130.0006397821843154260.999680108907842
1910.0002297770799672090.0004595541599344170.999770222920033
1920.0002378530061121670.0004757060122243330.999762146993888
1930.0001878081797375990.0003756163594751980.999812191820262
1940.0001488631848391170.0002977263696782340.999851136815161
1950.0001773823014176120.0003547646028352240.999822617698582
1960.0001708368738618030.0003416737477236050.999829163126138
1970.000312531270949880.000625062541899760.99968746872905
1980.0002198569784333660.0004397139568667320.999780143021567
1990.0001587889530371050.0003175779060742110.999841211046963
2000.0001613551808280.0003227103616560010.999838644819172
2010.0001110951232696550.000222190246539310.99988890487673
2028.46707063989261e-050.0001693414127978520.999915329293601
2036.91856760066439e-050.0001383713520132880.999930814323993
2044.58111462498406e-059.16222924996812e-050.99995418885375
2053.68323564115782e-057.36647128231564e-050.999963167643588
2063.91945826166519e-057.83891652333039e-050.999960805417383
2073.20533543662192e-056.41067087324385e-050.999967946645634
2085.50624443351996e-050.0001101248886703990.999944937555665
2097.29362495164073e-050.0001458724990328150.999927063750484
2109.17270076246863e-050.0001834540152493730.999908272992375
2116.19965812895759e-050.0001239931625791520.99993800341871
2124.0178198447871e-058.0356396895742e-050.999959821801552
2130.0002097252884125890.0004194505768251790.999790274711587
2140.0002139350588251790.0004278701176503580.999786064941175
2150.000159076697353410.0003181533947068190.999840923302647
2160.0001375759797583260.0002751519595166530.999862424020242
2170.0001117030748930530.0002234061497861070.999888296925107
2187.19470580748937e-050.0001438941161497870.999928052941925
2190.000145280121515970.000290560243031940.999854719878484
2200.0007196898523467790.001439379704693560.999280310147653
2210.0005651294458656180.001130258891731240.999434870554134
2220.08338579652254110.1667715930450820.916614203477459
2230.06613626011383410.1322725202276680.933863739886166
2240.1081427901524430.2162855803048850.891857209847557
2250.08988135554498990.179762711089980.91011864445501
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2550.165287124430360.3305742488607210.83471287556964






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1570.648760330578512NOK
5% type I error level1910.789256198347107NOK
10% type I error level1950.805785123966942NOK

\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 & 157 & 0.648760330578512 & NOK \tabularnewline
5% type I error level & 191 & 0.789256198347107 & NOK \tabularnewline
10% type I error level & 195 & 0.805785123966942 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195409&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]157[/C][C]0.648760330578512[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]191[/C][C]0.789256198347107[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]195[/C][C]0.805785123966942[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195409&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195409&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1570.648760330578512NOK
5% type I error level1910.789256198347107NOK
10% type I error level1950.805785123966942NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

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')
}