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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_regression_trees1.wasp
Title produced by softwareRecursive Partitioning (Regression Trees)
Date of computationWed, 14 Dec 2011 09:58:43 -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/2011/Dec/14/t132387480689r26ske805bjtp.htm/, Retrieved Wed, 01 May 2024 15:56:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155022, Retrieved Wed, 01 May 2024 15:56:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Recursive Partitioning (Regression Trees)] [] [2010-12-05 18:59:57] [b98453cac15ba1066b407e146608df68]
- R PD    [Recursive Partitioning (Regression Trees)] [] [2011-12-14 14:58:43] [38f0c551da22b29428835e369961555f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1418	210907	56	396	81	3	79	30	115	94
869	120982	56	297	55	4	58	28	109	103
1530	176508	54	559	50	12	60	38	146	93
2172	179321	89	967	125	2	108	30	116	103
901	123185	40	270	40	1	49	22	68	51
463	52746	25	143	37	3	0	26	101	70
3201	385534	92	1562	63	0	121	25	96	91
371	33170	18	109	44	0	1	18	67	22
1192	101645	63	371	88	0	20	11	44	38
1583	149061	44	656	66	5	43	26	100	93
1439	165446	33	511	57	0	69	25	93	60
1764	237213	84	655	74	0	78	38	140	123
1495	173326	88	465	49	7	86	44	166	148
1373	133131	55	525	52	7	44	30	99	90
2187	258873	60	885	88	3	104	40	139	124
1491	180083	66	497	36	9	63	34	130	70
4041	324799	154	1436	108	0	158	47	181	168
1706	230964	53	612	43	4	102	30	116	115
2152	236785	119	865	75	3	77	31	116	71
1036	135473	41	385	32	0	82	23	88	66
1882	202925	61	567	44	7	115	36	139	134
1929	215147	58	639	85	0	101	36	135	117
2242	344297	75	963	86	1	80	30	108	108
1220	153935	33	398	56	5	50	25	89	84
1289	132943	40	410	50	7	83	39	156	156
2515	174724	92	966	135	0	123	34	129	120
2147	174415	100	801	63	0	73	31	118	114
2352	225548	112	892	81	5	81	31	118	94
1638	223632	73	513	52	0	105	33	125	120
1222	124817	40	469	44	0	47	25	95	81
1812	221698	45	683	113	0	105	33	126	110
1677	210767	60	643	39	3	94	35	135	133
1579	170266	62	535	73	4	44	42	154	122
1731	260561	75	625	48	1	114	43	165	158
807	84853	31	264	33	4	38	30	113	109
2452	294424	77	992	59	2	107	33	127	124
829	101011	34	238	41	0	30	13	52	39
1940	215641	46	818	69	0	71	32	121	92
2662	325107	99	937	64	0	84	36	136	126
186	7176	17	70	1	0	0	0	0	0
1499	167542	66	507	59	2	59	28	108	70
865	106408	30	260	32	1	33	14	46	37
1793	96560	76	503	129	0	42	17	54	38
2527	265769	146	927	37	2	96	32	124	120
2747	269651	67	1269	31	10	106	30	115	93
1324	149112	56	537	65	6	56	35	128	95
2702	175824	107	910	107	0	57	20	80	77
1383	152871	58	532	74	5	59	28	97	90
1179	111665	34	345	54	4	39	28	104	80
2099	116408	61	918	76	1	34	39	59	31
4308	362301	119	1635	715	2	76	34	125	110
918	78800	42	330	57	2	20	26	82	66
1831	183167	66	557	66	0	91	39	149	138
3373	277965	89	1178	106	8	115	39	149	133
1713	150629	44	740	54	3	85	33	122	113
1438	168809	66	452	32	0	76	28	118	100
496	24188	24	218	20	0	8	4	12	7
2253	329267	259	764	71	8	79	39	144	140
744	65029	17	255	21	5	21	18	67	61
1161	101097	64	454	70	3	30	14	52	41
2352	218946	41	866	112	1	76	29	108	96
2144	244052	68	574	66	5	101	44	166	164
4691	341570	168	1276	190	1	94	21	80	78
1112	103597	43	379	66	1	27	16	60	49
2694	233328	132	825	165	5	92	28	107	102
1973	256462	105	798	56	0	123	35	127	124
1769	206161	71	663	61	12	75	28	107	99
3148	311473	112	1069	53	8	128	38	146	129
2474	235800	94	921	127	8	105	23	84	62
2084	177939	82	858	63	8	55	36	141	73
1954	207176	70	711	38	8	56	32	123	114
1226	196553	57	503	50	2	41	29	111	99
1389	174184	53	382	52	0	72	25	98	70
1496	143246	103	464	42	5	67	27	105	104
2269	187559	121	717	76	8	75	36	135	116
1833	187681	62	690	67	2	114	28	107	91
1268	119016	52	462	50	5	118	23	85	74
1943	182192	52	657	53	12	77	40	155	138
893	73566	32	385	39	6	22	23	88	67
1762	194979	62	577	50	7	66	40	155	151
1403	167488	45	619	77	2	69	28	104	72
1425	143756	46	479	57	0	105	34	132	120
1857	275541	63	817	73	4	116	33	127	115
1840	243199	75	752	34	3	88	28	108	105
1502	182999	88	430	39	6	73	34	129	104
1441	135649	46	451	46	2	99	30	116	108
1420	152299	53	537	63	0	62	33	122	98
1416	120221	37	519	35	1	53	22	85	69
2970	346485	90	1000	106	0	118	38	147	111
1317	145790	63	637	43	5	30	26	99	99
1644	193339	78	465	47	2	100	35	87	71
870	80953	25	437	31	0	49	8	28	27
1654	122774	45	711	162	0	24	24	90	69
1054	130585	46	299	57	5	67	29	109	107
937	112611	41	248	36	0	46	20	78	73
3004	286468	144	1162	263	1	57	29	111	107
2008	241066	82	714	78	0	75	45	158	93
2547	148446	91	905	63	1	135	37	141	129
1885	204713	71	649	54	1	68	33	122	69
1626	182079	63	512	63	2	124	33	124	118
1468	140344	53	472	77	6	33	25	93	73
2445	220516	62	905	79	1	98	32	124	119
1964	243060	63	786	110	4	58	29	112	104
1381	162765	32	489	56	2	68	28	108	107
1369	182613	39	479	56	3	81	28	99	99
1659	232138	62	617	43	0	131	31	117	90
2888	265318	117	925	111	10	110	52	199	197
1290	85574	34	351	71	0	37	21	78	36
2845	310839	92	1144	62	9	130	24	91	85
1982	225060	93	669	56	7	93	41	158	139
1904	232317	54	707	74	0	118	33	126	106
1391	144966	144	458	60	0	39	32	122	50
602	43287	14	214	43	4	13	19	71	64
1743	155754	61	599	68	4	74	20	75	31
1559	164709	109	572	53	0	81	31	115	63
2014	201940	38	897	87	0	109	31	119	92
2143	235454	73	819	46	0	151	32	124	106
2146	220801	75	720	105	1	51	18	72	63
874	99466	50	273	32	0	28	23	91	69
1590	92661	61	508	133	1	40	17	45	41
1590	133328	55	506	79	0	56	20	78	56
1210	61361	77	451	51	0	27	12	39	25
2072	125930	75	699	207	4	37	17	68	65
1281	100750	72	407	67	0	83	30	119	93
1401	224549	50	465	47	4	54	31	117	114
834	82316	32	245	34	4	27	10	39	38
1105	102010	53	370	66	3	28	13	50	44
1272	101523	42	316	76	0	59	22	88	87
1944	243511	71	603	65	0	133	42	155	110
391	22938	10	154	9	0	12	1	0	0
761	41566	35	229	42	5	0	9	36	27
1605	152474	65	577	45	0	106	32	123	83
530	61857	25	192	25	4	23	11	32	30
1988	99923	66	617	115	0	44	25	99	80
1386	132487	41	411	97	0	71	36	136	98
2395	317394	86	975	53	1	116	31	117	82
387	21054	16	146	2	0	4	0	0	0
1742	209641	42	705	52	5	62	24	88	60
620	22648	19	184	44	0	12	13	39	28
449	31414	19	200	22	0	18	8	25	9
800	46698	45	274	35	0	14	13	52	33
1684	131698	65	502	74	0	60	19	75	59
1050	91735	35	382	103	0	7	18	71	49
2699	244749	95	964	144	2	98	33	124	115
1606	184510	49	537	60	7	64	40	151	140
1502	79863	37	438	134	1	29	22	71	49
1204	128423	64	369	89	8	32	38	145	120
1138	97839	38	417	42	2	25	24	87	66
568	38214	34	276	52	0	16	8	27	21
1459	151101	32	514	98	2	48	35	131	124
2158	272458	65	822	99	0	100	43	162	152
1111	172494	52	389	52	0	46	43	165	139
1421	108043	62	466	29	1	45	14	54	38
2833	328107	65	1255	125	3	129	41	159	144
1955	250579	83	694	106	0	130	38	147	120
2922	351067	95	1024	95	3	136	45	170	160
1002	158015	29	400	40	0	59	31	119	114
1060	98866	18	397	140	0	25	13	49	39
956	85439	33	350	43	0	32	28	104	78
2186	229242	247	719	128	4	63	31	120	119
3604	351619	139	1277	142	4	95	40	150	141
1035	84207	29	356	73	11	14	30	112	101
1417	120445	118	457	72	0	36	16	59	56
3261	324598	110	1402	128	0	113	37	136	133
1587	131069	67	600	61	4	47	30	107	83
1424	204271	42	480	73	0	92	35	130	116
1701	165543	65	595	148	1	70	32	115	90
1249	141722	94	436	64	0	19	27	107	36
946	116048	64	230	45	0	50	20	75	50
1926	250047	81	651	58	0	41	18	71	61
3352	299775	95	1367	97	9	91	31	120	97
1641	195838	67	564	50	1	111	31	116	98
2035	173260	63	716	37	3	41	21	79	78
2312	254488	83	747	50	10	120	39	150	117
1369	104389	45	467	105	5	135	41	156	148
1577	136084	30	671	69	0	27	13	51	41
2201	199476	70	861	46	2	87	32	118	105
961	92499	32	319	57	0	25	18	71	55
1900	224330	83	612	52	1	131	39	144	132
1254	135781	31	433	98	2	45	14	47	44
1335	74408	67	434	61	4	29	7	28	21
1597	81240	66	503	89	0	58	17	68	50
207	14688	10	85	0	0	4	0	0	0
1645	181633	70	564	48	2	47	30	110	73
2429	271856	103	824	91	1	109	37	147	86
151	7199	5	74	0	0	7	0	0	0
474	46660	20	259	7	0	12	5	15	13
141	17547	5	69	3	0	0	1	4	4
1639	133368	36	535	54	1	37	16	64	57
872	95227	34	239	70	0	37	32	111	48
1318	152601	48	438	36	2	46	24	85	46
1018	98146	40	459	37	0	15	17	68	48
1383	79619	43	426	123	3	42	11	40	32
1314	59194	31	288	247	6	7	24	80	68
1335	139942	42	498	46	0	54	22	88	87
1403	118612	46	454	72	2	54	12	48	43
910	72880	33	376	41	0	14	19	76	67
616	65475	18	225	24	2	16	13	51	46
1407	99643	55	555	45	1	33	17	67	46
771	71965	35	252	33	1	32	15	59	56
766	77272	59	208	27	2	21	16	61	48
473	49289	19	130	36	1	15	24	76	44
1376	135131	66	481	87	0	38	15	60	60
1232	108446	60	389	90	1	22	17	68	65
1521	89746	36	565	114	3	28	18	71	55
572	44296	25	173	31	0	10	20	76	38
1059	77648	47	278	45	0	31	16	62	52
1544	181528	54	609	69	0	32	16	61	60
1230	134019	53	422	51	0	32	18	67	54
1206	124064	40	445	34	1	43	22	88	86
1205	92630	40	387	60	4	27	8	30	24
1255	121848	39	339	45	0	37	17	64	52
613	52915	14	181	54	0	20	18	68	49
721	81872	45	245	25	0	32	16	64	61
1109	58981	36	384	38	7	0	23	91	61
740	53515	28	212	52	2	5	22	88	81
1126	60812	44	399	67	0	26	13	52	43
728	56375	30	229	74	7	10	13	49	40
689	65490	22	224	38	3	27	16	62	40
592	80949	17	203	30	0	11	16	61	56
995	76302	31	333	26	0	29	20	76	68
1613	104011	55	384	67	6	25	22	88	79
2048	98104	54	636	132	2	55	17	66	47
705	67989	21	185	42	0	23	18	71	57
301	30989	14	93	35	0	5	17	68	41
1803	135458	81	581	118	3	43	12	48	29
799	73504	35	248	68	0	23	7	25	3
861	63123	43	304	43	1	34	17	68	60
1186	61254	46	344	76	1	36	14	41	30
1451	74914	30	407	64	0	35	23	90	79
628	31774	23	170	48	1	0	17	66	47
1161	81437	38	312	64	0	37	14	54	40
1463	87186	54	507	56	0	28	15	59	48
742	50090	20	224	71	0	16	17	60	36
979	65745	53	340	75	0	26	21	77	42
675	56653	45	168	39	0	38	18	68	49
1241	158399	39	443	42	0	23	18	72	57
676	46455	20	204	39	0	22	17	67	12
1049	73624	24	367	93	0	30	17	64	40
620	38395	31	210	38	0	16	16	63	43
1081	91899	35	335	60	0	18	15	59	33
1688	139526	151	364	71	0	28	21	84	77
736	52164	52	178	52	0	32	16	64	43
617	51567	30	206	27	2	21	14	56	45
812	70551	31	279	59	0	23	15	54	47
1051	84856	29	387	40	1	29	17	67	43
1656	102538	57	490	79	1	50	15	58	45
705	86678	40	238	44	0	12	15	59	50
945	85709	44	343	65	0	21	10	40	35
554	34662	25	232	10	0	18	6	22	7
1597	150580	77	530	124	0	27	22	83	71
982	99611	35	291	81	0	41	21	81	67
222	19349	11	67	15	0	13	1	2	0
1212	99373	63	397	92	1	12	18	72	62
1143	86230	44	467	42	0	21	17	61	54
435	30837	19	178	10	0	8	4	15	4
532	31706	13	175	24	0	26	10	32	25
882	89806	42	299	64	0	27	16	62	40
608	62088	38	154	45	1	13	16	58	38
459	40151	29	106	22	0	16	9	36	19
578	27634	20	189	56	0	2	16	59	17
826	76990	27	194	94	0	42	17	68	67
509	37460	20	135	19	0	5	7	21	14
717	54157	19	201	35	0	37	15	55	30
637	49862	37	207	32	0	17	14	54	54
857	84337	26	280	35	0	38	14	55	35
830	64175	42	260	48	0	37	18	72	59
652	59382	49	227	49	0	29	12	41	24
707	119308	30	239	48	0	32	16	61	58
954	76702	49	333	62	0	35	21	67	42
1461	103425	67	428	96	1	17	19	76	46
672	70344	28	230	45	0	20	16	64	61
778	43410	19	292	63	0	7	1	3	3
1141	104838	49	350	71	1	46	16	63	52
680	62215	27	186	26	0	24	10	40	25
1090	69304	30	326	48	6	40	19	69	40
616	53117	22	155	29	3	3	12	48	32
285	19764	12	75	19	1	10	2	8	4
1145	86680	31	361	45	2	37	14	52	49
733	84105	20	261	45	0	17	17	66	63
888	77945	20	299	67	0	28	19	76	67
849	89113	39	300	30	0	19	14	43	32
1182	91005	29	450	36	3	29	11	39	23
528	40248	16	183	34	1	8	4	14	7
642	64187	27	238	36	0	10	16	61	54
947	50857	21	165	34	0	15	20	71	37
819	56613	19	234	37	1	15	12	44	35
757	62792	35	176	46	0	28	15	60	51
894	72535	14	329	44	0	17	16	64	39

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'George Udny Yule' @ yule.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 & 10 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155022&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155022&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155022&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 time10 seconds
R Server'George Udny Yule' @ yule.wessa.net






Goodness of Fit
Correlation0.9427
R-squared0.8888
RMSE12.9729

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.9427 \tabularnewline
R-squared & 0.8888 \tabularnewline
RMSE & 12.9729 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155022&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.9427[/C][/ROW]
[ROW][C]R-squared[/C][C]0.8888[/C][/ROW]
[ROW][C]RMSE[/C][C]12.9729[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155022&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155022&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:

Goodness of Fit
Correlation0.9427
R-squared0.8888
RMSE12.9729






Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
19492.0163934426231.98360655737704
210392.01639344262310.983606557377
393119.588235294118-26.5882352941177
410392.01639344262310.983606557377
55153.4385964912281-2.43859649122807
67092.016393442623-22.016393442623
79192.016393442623-1.01639344262296
82238.8181818181818-16.8181818181818
93840.4285714285714-2.42857142857143
109392.0163934426230.983606557377044
116072.1-12.1
12123119.5882352941183.41176470588235
13148158.888888888889-10.8888888888889
149092.016393442623-2.01639344262296
15124119.5882352941184.41176470588235
1670119.588235294118-49.5882352941177
17168158.8888888888899.11111111111111
1811592.01639344262322.983606557377
197192.016393442623-21.016393442623
206672.1-6.1
21134119.58823529411814.4117647058823
22117119.588235294118-2.58823529411765
2310892.01639344262315.983606557377
248472.111.9
25156119.58823529411836.4117647058823
26120119.5882352941180.411764705882348
2711492.01639344262321.983606557377
289492.0163934426231.98360655737704
29120119.5882352941180.411764705882348
308192.016393442623-11.016393442623
31110119.588235294118-9.58823529411765
32133119.58823529411813.4117647058823
33122119.5882352941182.41176470588235
34158158.888888888889-0.888888888888886
3510992.01639344262316.983606557377
36124119.5882352941184.41176470588235
373940.4285714285714-1.42857142857143
389292.016393442623-0.0163934426229559
39126119.5882352941186.41176470588235
4004.41176470588235-4.41176470588235
417092.016393442623-22.016393442623
423740.4285714285714-3.42857142857143
433840.4285714285714-2.42857142857143
44120119.5882352941180.411764705882348
459392.0163934426230.983606557377044
4695119.588235294118-24.5882352941177
477772.14.90000000000001
489092.016393442623-2.01639344262296
498092.016393442623-12.016393442623
503140.4285714285714-9.42857142857143
51110119.588235294118-9.58823529411765
526672.1-6.1
53138119.58823529411818.4117647058823
54133119.58823529411813.4117647058823
5511392.01639344262320.983606557377
5610092.0163934426237.98360655737704
5774.411764705882352.58823529411765
58140119.58823529411820.4117647058823
596153.43859649122817.56140350877193
604140.42857142857140.57142857142857
619692.0163934426233.98360655737704
62164158.8888888888895.11111111111111
637872.15.9
644953.4385964912281-4.43859649122807
6510292.0163934426239.98360655737704
66124119.5882352941184.41176470588235
679992.0163934426236.98360655737704
68129119.5882352941189.41176470588235
696272.1-10.1
7073119.588235294118-46.5882352941177
7111492.01639344262321.983606557377
729992.0163934426236.98360655737704
737092.016393442623-22.016393442623
7410492.01639344262311.983606557377
75116119.588235294118-3.58823529411765
769192.016393442623-1.01639344262296
777472.11.90000000000001
78138119.58823529411818.4117647058823
796772.1-5.09999999999999
80151119.58823529411831.4117647058823
817292.016393442623-20.016393442623
82120119.5882352941180.411764705882348
83115119.588235294118-4.58823529411765
8410592.01639344262312.983606557377
85104119.588235294118-15.5882352941177
8610892.01639344262315.983606557377
879892.0163934426235.98360655737704
886972.1-3.09999999999999
89111119.588235294118-8.58823529411765
909992.0163934426236.98360655737704
917172.1-1.09999999999999
9227270
936972.1-3.09999999999999
9410792.01639344262314.983606557377
957353.438596491228119.5614035087719
9610792.01639344262314.983606557377
9793119.588235294118-26.5882352941177
98129119.5882352941189.41176470588235
996992.016393442623-23.016393442623
100118119.588235294118-1.58823529411765
1017372.10.900000000000006
102119119.588235294118-0.588235294117652
10310492.01639344262311.983606557377
10410792.01639344262314.983606557377
1059992.0163934426236.98360655737704
1069092.016393442623-2.01639344262296
107197158.88888888888938.1111111111111
1083653.4385964912281-17.4385964912281
1098572.112.9
110139119.58823529411819.4117647058823
111106119.588235294118-13.5882352941177
1125092.016393442623-42.016393442623
1136438.818181818181825.1818181818182
1143153.4385964912281-22.4385964912281
1156392.016393442623-29.016393442623
1169292.016393442623-0.0163934426229559
117106119.588235294118-13.5882352941177
1186353.43859649122819.56140350877193
1196972.1-3.09999999999999
1204140.42857142857140.57142857142857
1215653.43859649122812.56140350877193
1222527-2
1236553.438596491228111.5614035087719
1249392.0163934426230.983606557377044
12511492.01639344262321.983606557377
126382711
1274440.42857142857143.57142857142857
1288772.114.9
129110119.588235294118-9.58823529411765
13004.41176470588235-4.41176470588235
13127270
1328392.016393442623-9.01639344262296
13330273
1348092.016393442623-12.016393442623
13598119.588235294118-21.5882352941177
1368292.016393442623-10.016393442623
13704.41176470588235-4.41176470588235
1386072.1-12.1
13928271
14094.411764705882354.58823529411765
1413340.4285714285714-7.42857142857143
1425953.43859649122815.56140350877193
1434953.4385964912281-4.43859649122807
144115119.588235294118-4.58823529411765
145140119.58823529411820.4117647058823
1464953.4385964912281-4.43859649122807
147120119.5882352941180.411764705882348
1486672.1-6.1
1492127-6
150124119.5882352941184.41176470588235
151152158.888888888889-6.88888888888889
152139158.888888888889-19.8888888888889
1533840.4285714285714-2.42857142857143
154144158.888888888889-14.8888888888889
155120119.5882352941180.411764705882348
156160158.8888888888891.11111111111111
15711492.01639344262321.983606557377
1583940.4285714285714-1.42857142857143
1597892.016393442623-14.016393442623
16011992.01639344262326.983606557377
161141119.58823529411821.4117647058823
16210192.0163934426238.98360655737704
1635640.428571428571415.5714285714286
164133119.58823529411813.4117647058823
1658392.016393442623-9.01639344262296
166116119.588235294118-3.58823529411765
1679092.016393442623-2.01639344262296
1683692.016393442623-56.016393442623
1695053.4385964912281-3.43859649122807
1706153.43859649122817.56140350877193
1719792.0163934426234.98360655737704
1729892.0163934426235.98360655737704
1737872.15.9
174117119.588235294118-2.58823529411765
175148119.58823529411828.4117647058823
1764140.42857142857140.57142857142857
17710592.01639344262312.983606557377
1785553.43859649122811.56140350877193
179132119.58823529411812.4117647058823
1804440.42857142857143.57142857142857
1812127-6
1825053.4385964912281-3.43859649122807
18304.41176470588235-4.41176470588235
1847392.016393442623-19.016393442623
18586119.588235294118-33.5882352941177
18604.41176470588235-4.41176470588235
187134.411764705882358.58823529411765
18844.41176470588235-0.411764705882353
1895753.43859649122813.56140350877193
1904892.016393442623-44.016393442623
1914672.1-26.1
1924853.4385964912281-5.43859649122807
19332275
1946872.1-4.09999999999999
1958772.114.9
1964340.42857142857142.57142857142857
1976753.438596491228113.5614035087719
1984640.42857142857145.57142857142857
1994653.4385964912281-7.43859649122807
2005640.428571428571415.5714285714286
2014853.4385964912281-5.43859649122807
2024438.81818181818185.18181818181818
2036053.43859649122816.56140350877193
2046553.438596491228111.5614035087719
2055553.43859649122811.56140350877193
2063838.8181818181818-0.81818181818182
2075253.4385964912281-1.43859649122807
2086053.43859649122816.56140350877193
2095453.43859649122810.561403508771932
2108672.113.9
2112427-3
2125253.4385964912281-1.43859649122807
2134953.4385964912281-4.43859649122807
2146153.43859649122817.56140350877193
2156172.1-11.1
2168172.18.9
2174340.42857142857142.57142857142857
2184040.4285714285714-0.428571428571431
2194053.4385964912281-13.4385964912281
2205653.43859649122812.56140350877193
2216853.438596491228114.5614035087719
2227972.16.9
2234753.4385964912281-6.43859649122807
2245753.43859649122813.56140350877193
2254138.81818181818182.18181818181818
2262940.4285714285714-11.4285714285714
22734.41176470588235-1.41176470588235
2286053.43859649122816.56140350877193
22930273
2307972.16.9
2314738.81818181818188.18181818181818
2324040.4285714285714-0.428571428571431
2334840.42857142857147.57142857142857
2343638.8181818181818-2.81818181818182
2354253.4385964912281-11.4385964912281
2364953.4385964912281-4.43859649122807
2375753.43859649122813.56140350877193
2381238.8181818181818-26.8181818181818
2394053.4385964912281-13.4385964912281
2404338.81818181818184.18181818181818
2413340.4285714285714-7.42857142857143
2427772.14.90000000000001
2434338.81818181818184.18181818181818
2444540.42857142857144.57142857142857
2454740.42857142857146.57142857142857
2464353.4385964912281-10.4385964912281
2474540.42857142857144.57142857142857
2485040.42857142857149.57142857142857
24935278
25074.411764705882352.58823529411765
2517172.1-1.09999999999999
2526772.1-5.09999999999999
25304.41176470588235-4.41176470588235
2546253.43859649122818.56140350877193
2555453.43859649122810.561403508771932
25644.41176470588235-0.411764705882353
2572527-2
2584053.4385964912281-13.4385964912281
2593840.4285714285714-2.42857142857143
2601927-8
2611740.4285714285714-23.4285714285714
2626753.438596491228113.5614035087719
263144.411764705882359.58823529411765
2643040.4285714285714-10.4285714285714
2655440.428571428571413.5714285714286
2663540.4285714285714-5.42857142857143
2675953.43859649122815.56140350877193
2682427-3
2695853.43859649122814.56140350877193
2704253.4385964912281-11.4385964912281
2714653.4385964912281-7.43859649122807
2726153.43859649122817.56140350877193
27334.41176470588235-1.41176470588235
2745253.4385964912281-1.43859649122807
2752527-2
2764053.4385964912281-13.4385964912281
2773240.4285714285714-8.42857142857143
27844.41176470588235-0.411764705882353
2794940.42857142857148.57142857142857
2806353.43859649122819.56140350877193
2816753.438596491228113.5614035087719
28232275
2832327-4
28474.411764705882352.58823529411765
2855453.43859649122810.561403508771932
2863738.8181818181818-1.81818181818182
2873540.4285714285714-5.42857142857143
2885153.4385964912281-2.43859649122807
2893953.4385964912281-14.4385964912281

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 94 & 92.016393442623 & 1.98360655737704 \tabularnewline
2 & 103 & 92.016393442623 & 10.983606557377 \tabularnewline
3 & 93 & 119.588235294118 & -26.5882352941177 \tabularnewline
4 & 103 & 92.016393442623 & 10.983606557377 \tabularnewline
5 & 51 & 53.4385964912281 & -2.43859649122807 \tabularnewline
6 & 70 & 92.016393442623 & -22.016393442623 \tabularnewline
7 & 91 & 92.016393442623 & -1.01639344262296 \tabularnewline
8 & 22 & 38.8181818181818 & -16.8181818181818 \tabularnewline
9 & 38 & 40.4285714285714 & -2.42857142857143 \tabularnewline
10 & 93 & 92.016393442623 & 0.983606557377044 \tabularnewline
11 & 60 & 72.1 & -12.1 \tabularnewline
12 & 123 & 119.588235294118 & 3.41176470588235 \tabularnewline
13 & 148 & 158.888888888889 & -10.8888888888889 \tabularnewline
14 & 90 & 92.016393442623 & -2.01639344262296 \tabularnewline
15 & 124 & 119.588235294118 & 4.41176470588235 \tabularnewline
16 & 70 & 119.588235294118 & -49.5882352941177 \tabularnewline
17 & 168 & 158.888888888889 & 9.11111111111111 \tabularnewline
18 & 115 & 92.016393442623 & 22.983606557377 \tabularnewline
19 & 71 & 92.016393442623 & -21.016393442623 \tabularnewline
20 & 66 & 72.1 & -6.1 \tabularnewline
21 & 134 & 119.588235294118 & 14.4117647058823 \tabularnewline
22 & 117 & 119.588235294118 & -2.58823529411765 \tabularnewline
23 & 108 & 92.016393442623 & 15.983606557377 \tabularnewline
24 & 84 & 72.1 & 11.9 \tabularnewline
25 & 156 & 119.588235294118 & 36.4117647058823 \tabularnewline
26 & 120 & 119.588235294118 & 0.411764705882348 \tabularnewline
27 & 114 & 92.016393442623 & 21.983606557377 \tabularnewline
28 & 94 & 92.016393442623 & 1.98360655737704 \tabularnewline
29 & 120 & 119.588235294118 & 0.411764705882348 \tabularnewline
30 & 81 & 92.016393442623 & -11.016393442623 \tabularnewline
31 & 110 & 119.588235294118 & -9.58823529411765 \tabularnewline
32 & 133 & 119.588235294118 & 13.4117647058823 \tabularnewline
33 & 122 & 119.588235294118 & 2.41176470588235 \tabularnewline
34 & 158 & 158.888888888889 & -0.888888888888886 \tabularnewline
35 & 109 & 92.016393442623 & 16.983606557377 \tabularnewline
36 & 124 & 119.588235294118 & 4.41176470588235 \tabularnewline
37 & 39 & 40.4285714285714 & -1.42857142857143 \tabularnewline
38 & 92 & 92.016393442623 & -0.0163934426229559 \tabularnewline
39 & 126 & 119.588235294118 & 6.41176470588235 \tabularnewline
40 & 0 & 4.41176470588235 & -4.41176470588235 \tabularnewline
41 & 70 & 92.016393442623 & -22.016393442623 \tabularnewline
42 & 37 & 40.4285714285714 & -3.42857142857143 \tabularnewline
43 & 38 & 40.4285714285714 & -2.42857142857143 \tabularnewline
44 & 120 & 119.588235294118 & 0.411764705882348 \tabularnewline
45 & 93 & 92.016393442623 & 0.983606557377044 \tabularnewline
46 & 95 & 119.588235294118 & -24.5882352941177 \tabularnewline
47 & 77 & 72.1 & 4.90000000000001 \tabularnewline
48 & 90 & 92.016393442623 & -2.01639344262296 \tabularnewline
49 & 80 & 92.016393442623 & -12.016393442623 \tabularnewline
50 & 31 & 40.4285714285714 & -9.42857142857143 \tabularnewline
51 & 110 & 119.588235294118 & -9.58823529411765 \tabularnewline
52 & 66 & 72.1 & -6.1 \tabularnewline
53 & 138 & 119.588235294118 & 18.4117647058823 \tabularnewline
54 & 133 & 119.588235294118 & 13.4117647058823 \tabularnewline
55 & 113 & 92.016393442623 & 20.983606557377 \tabularnewline
56 & 100 & 92.016393442623 & 7.98360655737704 \tabularnewline
57 & 7 & 4.41176470588235 & 2.58823529411765 \tabularnewline
58 & 140 & 119.588235294118 & 20.4117647058823 \tabularnewline
59 & 61 & 53.4385964912281 & 7.56140350877193 \tabularnewline
60 & 41 & 40.4285714285714 & 0.57142857142857 \tabularnewline
61 & 96 & 92.016393442623 & 3.98360655737704 \tabularnewline
62 & 164 & 158.888888888889 & 5.11111111111111 \tabularnewline
63 & 78 & 72.1 & 5.9 \tabularnewline
64 & 49 & 53.4385964912281 & -4.43859649122807 \tabularnewline
65 & 102 & 92.016393442623 & 9.98360655737704 \tabularnewline
66 & 124 & 119.588235294118 & 4.41176470588235 \tabularnewline
67 & 99 & 92.016393442623 & 6.98360655737704 \tabularnewline
68 & 129 & 119.588235294118 & 9.41176470588235 \tabularnewline
69 & 62 & 72.1 & -10.1 \tabularnewline
70 & 73 & 119.588235294118 & -46.5882352941177 \tabularnewline
71 & 114 & 92.016393442623 & 21.983606557377 \tabularnewline
72 & 99 & 92.016393442623 & 6.98360655737704 \tabularnewline
73 & 70 & 92.016393442623 & -22.016393442623 \tabularnewline
74 & 104 & 92.016393442623 & 11.983606557377 \tabularnewline
75 & 116 & 119.588235294118 & -3.58823529411765 \tabularnewline
76 & 91 & 92.016393442623 & -1.01639344262296 \tabularnewline
77 & 74 & 72.1 & 1.90000000000001 \tabularnewline
78 & 138 & 119.588235294118 & 18.4117647058823 \tabularnewline
79 & 67 & 72.1 & -5.09999999999999 \tabularnewline
80 & 151 & 119.588235294118 & 31.4117647058823 \tabularnewline
81 & 72 & 92.016393442623 & -20.016393442623 \tabularnewline
82 & 120 & 119.588235294118 & 0.411764705882348 \tabularnewline
83 & 115 & 119.588235294118 & -4.58823529411765 \tabularnewline
84 & 105 & 92.016393442623 & 12.983606557377 \tabularnewline
85 & 104 & 119.588235294118 & -15.5882352941177 \tabularnewline
86 & 108 & 92.016393442623 & 15.983606557377 \tabularnewline
87 & 98 & 92.016393442623 & 5.98360655737704 \tabularnewline
88 & 69 & 72.1 & -3.09999999999999 \tabularnewline
89 & 111 & 119.588235294118 & -8.58823529411765 \tabularnewline
90 & 99 & 92.016393442623 & 6.98360655737704 \tabularnewline
91 & 71 & 72.1 & -1.09999999999999 \tabularnewline
92 & 27 & 27 & 0 \tabularnewline
93 & 69 & 72.1 & -3.09999999999999 \tabularnewline
94 & 107 & 92.016393442623 & 14.983606557377 \tabularnewline
95 & 73 & 53.4385964912281 & 19.5614035087719 \tabularnewline
96 & 107 & 92.016393442623 & 14.983606557377 \tabularnewline
97 & 93 & 119.588235294118 & -26.5882352941177 \tabularnewline
98 & 129 & 119.588235294118 & 9.41176470588235 \tabularnewline
99 & 69 & 92.016393442623 & -23.016393442623 \tabularnewline
100 & 118 & 119.588235294118 & -1.58823529411765 \tabularnewline
101 & 73 & 72.1 & 0.900000000000006 \tabularnewline
102 & 119 & 119.588235294118 & -0.588235294117652 \tabularnewline
103 & 104 & 92.016393442623 & 11.983606557377 \tabularnewline
104 & 107 & 92.016393442623 & 14.983606557377 \tabularnewline
105 & 99 & 92.016393442623 & 6.98360655737704 \tabularnewline
106 & 90 & 92.016393442623 & -2.01639344262296 \tabularnewline
107 & 197 & 158.888888888889 & 38.1111111111111 \tabularnewline
108 & 36 & 53.4385964912281 & -17.4385964912281 \tabularnewline
109 & 85 & 72.1 & 12.9 \tabularnewline
110 & 139 & 119.588235294118 & 19.4117647058823 \tabularnewline
111 & 106 & 119.588235294118 & -13.5882352941177 \tabularnewline
112 & 50 & 92.016393442623 & -42.016393442623 \tabularnewline
113 & 64 & 38.8181818181818 & 25.1818181818182 \tabularnewline
114 & 31 & 53.4385964912281 & -22.4385964912281 \tabularnewline
115 & 63 & 92.016393442623 & -29.016393442623 \tabularnewline
116 & 92 & 92.016393442623 & -0.0163934426229559 \tabularnewline
117 & 106 & 119.588235294118 & -13.5882352941177 \tabularnewline
118 & 63 & 53.4385964912281 & 9.56140350877193 \tabularnewline
119 & 69 & 72.1 & -3.09999999999999 \tabularnewline
120 & 41 & 40.4285714285714 & 0.57142857142857 \tabularnewline
121 & 56 & 53.4385964912281 & 2.56140350877193 \tabularnewline
122 & 25 & 27 & -2 \tabularnewline
123 & 65 & 53.4385964912281 & 11.5614035087719 \tabularnewline
124 & 93 & 92.016393442623 & 0.983606557377044 \tabularnewline
125 & 114 & 92.016393442623 & 21.983606557377 \tabularnewline
126 & 38 & 27 & 11 \tabularnewline
127 & 44 & 40.4285714285714 & 3.57142857142857 \tabularnewline
128 & 87 & 72.1 & 14.9 \tabularnewline
129 & 110 & 119.588235294118 & -9.58823529411765 \tabularnewline
130 & 0 & 4.41176470588235 & -4.41176470588235 \tabularnewline
131 & 27 & 27 & 0 \tabularnewline
132 & 83 & 92.016393442623 & -9.01639344262296 \tabularnewline
133 & 30 & 27 & 3 \tabularnewline
134 & 80 & 92.016393442623 & -12.016393442623 \tabularnewline
135 & 98 & 119.588235294118 & -21.5882352941177 \tabularnewline
136 & 82 & 92.016393442623 & -10.016393442623 \tabularnewline
137 & 0 & 4.41176470588235 & -4.41176470588235 \tabularnewline
138 & 60 & 72.1 & -12.1 \tabularnewline
139 & 28 & 27 & 1 \tabularnewline
140 & 9 & 4.41176470588235 & 4.58823529411765 \tabularnewline
141 & 33 & 40.4285714285714 & -7.42857142857143 \tabularnewline
142 & 59 & 53.4385964912281 & 5.56140350877193 \tabularnewline
143 & 49 & 53.4385964912281 & -4.43859649122807 \tabularnewline
144 & 115 & 119.588235294118 & -4.58823529411765 \tabularnewline
145 & 140 & 119.588235294118 & 20.4117647058823 \tabularnewline
146 & 49 & 53.4385964912281 & -4.43859649122807 \tabularnewline
147 & 120 & 119.588235294118 & 0.411764705882348 \tabularnewline
148 & 66 & 72.1 & -6.1 \tabularnewline
149 & 21 & 27 & -6 \tabularnewline
150 & 124 & 119.588235294118 & 4.41176470588235 \tabularnewline
151 & 152 & 158.888888888889 & -6.88888888888889 \tabularnewline
152 & 139 & 158.888888888889 & -19.8888888888889 \tabularnewline
153 & 38 & 40.4285714285714 & -2.42857142857143 \tabularnewline
154 & 144 & 158.888888888889 & -14.8888888888889 \tabularnewline
155 & 120 & 119.588235294118 & 0.411764705882348 \tabularnewline
156 & 160 & 158.888888888889 & 1.11111111111111 \tabularnewline
157 & 114 & 92.016393442623 & 21.983606557377 \tabularnewline
158 & 39 & 40.4285714285714 & -1.42857142857143 \tabularnewline
159 & 78 & 92.016393442623 & -14.016393442623 \tabularnewline
160 & 119 & 92.016393442623 & 26.983606557377 \tabularnewline
161 & 141 & 119.588235294118 & 21.4117647058823 \tabularnewline
162 & 101 & 92.016393442623 & 8.98360655737704 \tabularnewline
163 & 56 & 40.4285714285714 & 15.5714285714286 \tabularnewline
164 & 133 & 119.588235294118 & 13.4117647058823 \tabularnewline
165 & 83 & 92.016393442623 & -9.01639344262296 \tabularnewline
166 & 116 & 119.588235294118 & -3.58823529411765 \tabularnewline
167 & 90 & 92.016393442623 & -2.01639344262296 \tabularnewline
168 & 36 & 92.016393442623 & -56.016393442623 \tabularnewline
169 & 50 & 53.4385964912281 & -3.43859649122807 \tabularnewline
170 & 61 & 53.4385964912281 & 7.56140350877193 \tabularnewline
171 & 97 & 92.016393442623 & 4.98360655737704 \tabularnewline
172 & 98 & 92.016393442623 & 5.98360655737704 \tabularnewline
173 & 78 & 72.1 & 5.9 \tabularnewline
174 & 117 & 119.588235294118 & -2.58823529411765 \tabularnewline
175 & 148 & 119.588235294118 & 28.4117647058823 \tabularnewline
176 & 41 & 40.4285714285714 & 0.57142857142857 \tabularnewline
177 & 105 & 92.016393442623 & 12.983606557377 \tabularnewline
178 & 55 & 53.4385964912281 & 1.56140350877193 \tabularnewline
179 & 132 & 119.588235294118 & 12.4117647058823 \tabularnewline
180 & 44 & 40.4285714285714 & 3.57142857142857 \tabularnewline
181 & 21 & 27 & -6 \tabularnewline
182 & 50 & 53.4385964912281 & -3.43859649122807 \tabularnewline
183 & 0 & 4.41176470588235 & -4.41176470588235 \tabularnewline
184 & 73 & 92.016393442623 & -19.016393442623 \tabularnewline
185 & 86 & 119.588235294118 & -33.5882352941177 \tabularnewline
186 & 0 & 4.41176470588235 & -4.41176470588235 \tabularnewline
187 & 13 & 4.41176470588235 & 8.58823529411765 \tabularnewline
188 & 4 & 4.41176470588235 & -0.411764705882353 \tabularnewline
189 & 57 & 53.4385964912281 & 3.56140350877193 \tabularnewline
190 & 48 & 92.016393442623 & -44.016393442623 \tabularnewline
191 & 46 & 72.1 & -26.1 \tabularnewline
192 & 48 & 53.4385964912281 & -5.43859649122807 \tabularnewline
193 & 32 & 27 & 5 \tabularnewline
194 & 68 & 72.1 & -4.09999999999999 \tabularnewline
195 & 87 & 72.1 & 14.9 \tabularnewline
196 & 43 & 40.4285714285714 & 2.57142857142857 \tabularnewline
197 & 67 & 53.4385964912281 & 13.5614035087719 \tabularnewline
198 & 46 & 40.4285714285714 & 5.57142857142857 \tabularnewline
199 & 46 & 53.4385964912281 & -7.43859649122807 \tabularnewline
200 & 56 & 40.4285714285714 & 15.5714285714286 \tabularnewline
201 & 48 & 53.4385964912281 & -5.43859649122807 \tabularnewline
202 & 44 & 38.8181818181818 & 5.18181818181818 \tabularnewline
203 & 60 & 53.4385964912281 & 6.56140350877193 \tabularnewline
204 & 65 & 53.4385964912281 & 11.5614035087719 \tabularnewline
205 & 55 & 53.4385964912281 & 1.56140350877193 \tabularnewline
206 & 38 & 38.8181818181818 & -0.81818181818182 \tabularnewline
207 & 52 & 53.4385964912281 & -1.43859649122807 \tabularnewline
208 & 60 & 53.4385964912281 & 6.56140350877193 \tabularnewline
209 & 54 & 53.4385964912281 & 0.561403508771932 \tabularnewline
210 & 86 & 72.1 & 13.9 \tabularnewline
211 & 24 & 27 & -3 \tabularnewline
212 & 52 & 53.4385964912281 & -1.43859649122807 \tabularnewline
213 & 49 & 53.4385964912281 & -4.43859649122807 \tabularnewline
214 & 61 & 53.4385964912281 & 7.56140350877193 \tabularnewline
215 & 61 & 72.1 & -11.1 \tabularnewline
216 & 81 & 72.1 & 8.9 \tabularnewline
217 & 43 & 40.4285714285714 & 2.57142857142857 \tabularnewline
218 & 40 & 40.4285714285714 & -0.428571428571431 \tabularnewline
219 & 40 & 53.4385964912281 & -13.4385964912281 \tabularnewline
220 & 56 & 53.4385964912281 & 2.56140350877193 \tabularnewline
221 & 68 & 53.4385964912281 & 14.5614035087719 \tabularnewline
222 & 79 & 72.1 & 6.9 \tabularnewline
223 & 47 & 53.4385964912281 & -6.43859649122807 \tabularnewline
224 & 57 & 53.4385964912281 & 3.56140350877193 \tabularnewline
225 & 41 & 38.8181818181818 & 2.18181818181818 \tabularnewline
226 & 29 & 40.4285714285714 & -11.4285714285714 \tabularnewline
227 & 3 & 4.41176470588235 & -1.41176470588235 \tabularnewline
228 & 60 & 53.4385964912281 & 6.56140350877193 \tabularnewline
229 & 30 & 27 & 3 \tabularnewline
230 & 79 & 72.1 & 6.9 \tabularnewline
231 & 47 & 38.8181818181818 & 8.18181818181818 \tabularnewline
232 & 40 & 40.4285714285714 & -0.428571428571431 \tabularnewline
233 & 48 & 40.4285714285714 & 7.57142857142857 \tabularnewline
234 & 36 & 38.8181818181818 & -2.81818181818182 \tabularnewline
235 & 42 & 53.4385964912281 & -11.4385964912281 \tabularnewline
236 & 49 & 53.4385964912281 & -4.43859649122807 \tabularnewline
237 & 57 & 53.4385964912281 & 3.56140350877193 \tabularnewline
238 & 12 & 38.8181818181818 & -26.8181818181818 \tabularnewline
239 & 40 & 53.4385964912281 & -13.4385964912281 \tabularnewline
240 & 43 & 38.8181818181818 & 4.18181818181818 \tabularnewline
241 & 33 & 40.4285714285714 & -7.42857142857143 \tabularnewline
242 & 77 & 72.1 & 4.90000000000001 \tabularnewline
243 & 43 & 38.8181818181818 & 4.18181818181818 \tabularnewline
244 & 45 & 40.4285714285714 & 4.57142857142857 \tabularnewline
245 & 47 & 40.4285714285714 & 6.57142857142857 \tabularnewline
246 & 43 & 53.4385964912281 & -10.4385964912281 \tabularnewline
247 & 45 & 40.4285714285714 & 4.57142857142857 \tabularnewline
248 & 50 & 40.4285714285714 & 9.57142857142857 \tabularnewline
249 & 35 & 27 & 8 \tabularnewline
250 & 7 & 4.41176470588235 & 2.58823529411765 \tabularnewline
251 & 71 & 72.1 & -1.09999999999999 \tabularnewline
252 & 67 & 72.1 & -5.09999999999999 \tabularnewline
253 & 0 & 4.41176470588235 & -4.41176470588235 \tabularnewline
254 & 62 & 53.4385964912281 & 8.56140350877193 \tabularnewline
255 & 54 & 53.4385964912281 & 0.561403508771932 \tabularnewline
256 & 4 & 4.41176470588235 & -0.411764705882353 \tabularnewline
257 & 25 & 27 & -2 \tabularnewline
258 & 40 & 53.4385964912281 & -13.4385964912281 \tabularnewline
259 & 38 & 40.4285714285714 & -2.42857142857143 \tabularnewline
260 & 19 & 27 & -8 \tabularnewline
261 & 17 & 40.4285714285714 & -23.4285714285714 \tabularnewline
262 & 67 & 53.4385964912281 & 13.5614035087719 \tabularnewline
263 & 14 & 4.41176470588235 & 9.58823529411765 \tabularnewline
264 & 30 & 40.4285714285714 & -10.4285714285714 \tabularnewline
265 & 54 & 40.4285714285714 & 13.5714285714286 \tabularnewline
266 & 35 & 40.4285714285714 & -5.42857142857143 \tabularnewline
267 & 59 & 53.4385964912281 & 5.56140350877193 \tabularnewline
268 & 24 & 27 & -3 \tabularnewline
269 & 58 & 53.4385964912281 & 4.56140350877193 \tabularnewline
270 & 42 & 53.4385964912281 & -11.4385964912281 \tabularnewline
271 & 46 & 53.4385964912281 & -7.43859649122807 \tabularnewline
272 & 61 & 53.4385964912281 & 7.56140350877193 \tabularnewline
273 & 3 & 4.41176470588235 & -1.41176470588235 \tabularnewline
274 & 52 & 53.4385964912281 & -1.43859649122807 \tabularnewline
275 & 25 & 27 & -2 \tabularnewline
276 & 40 & 53.4385964912281 & -13.4385964912281 \tabularnewline
277 & 32 & 40.4285714285714 & -8.42857142857143 \tabularnewline
278 & 4 & 4.41176470588235 & -0.411764705882353 \tabularnewline
279 & 49 & 40.4285714285714 & 8.57142857142857 \tabularnewline
280 & 63 & 53.4385964912281 & 9.56140350877193 \tabularnewline
281 & 67 & 53.4385964912281 & 13.5614035087719 \tabularnewline
282 & 32 & 27 & 5 \tabularnewline
283 & 23 & 27 & -4 \tabularnewline
284 & 7 & 4.41176470588235 & 2.58823529411765 \tabularnewline
285 & 54 & 53.4385964912281 & 0.561403508771932 \tabularnewline
286 & 37 & 38.8181818181818 & -1.81818181818182 \tabularnewline
287 & 35 & 40.4285714285714 & -5.42857142857143 \tabularnewline
288 & 51 & 53.4385964912281 & -2.43859649122807 \tabularnewline
289 & 39 & 53.4385964912281 & -14.4385964912281 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155022&T=2

[TABLE]
[ROW][C]Actuals, Predictions, and Residuals[/C][/ROW]
[ROW][C]#[/C][C]Actuals[/C][C]Forecasts[/C][C]Residuals[/C][/ROW]
[ROW][C]1[/C][C]94[/C][C]92.016393442623[/C][C]1.98360655737704[/C][/ROW]
[ROW][C]2[/C][C]103[/C][C]92.016393442623[/C][C]10.983606557377[/C][/ROW]
[ROW][C]3[/C][C]93[/C][C]119.588235294118[/C][C]-26.5882352941177[/C][/ROW]
[ROW][C]4[/C][C]103[/C][C]92.016393442623[/C][C]10.983606557377[/C][/ROW]
[ROW][C]5[/C][C]51[/C][C]53.4385964912281[/C][C]-2.43859649122807[/C][/ROW]
[ROW][C]6[/C][C]70[/C][C]92.016393442623[/C][C]-22.016393442623[/C][/ROW]
[ROW][C]7[/C][C]91[/C][C]92.016393442623[/C][C]-1.01639344262296[/C][/ROW]
[ROW][C]8[/C][C]22[/C][C]38.8181818181818[/C][C]-16.8181818181818[/C][/ROW]
[ROW][C]9[/C][C]38[/C][C]40.4285714285714[/C][C]-2.42857142857143[/C][/ROW]
[ROW][C]10[/C][C]93[/C][C]92.016393442623[/C][C]0.983606557377044[/C][/ROW]
[ROW][C]11[/C][C]60[/C][C]72.1[/C][C]-12.1[/C][/ROW]
[ROW][C]12[/C][C]123[/C][C]119.588235294118[/C][C]3.41176470588235[/C][/ROW]
[ROW][C]13[/C][C]148[/C][C]158.888888888889[/C][C]-10.8888888888889[/C][/ROW]
[ROW][C]14[/C][C]90[/C][C]92.016393442623[/C][C]-2.01639344262296[/C][/ROW]
[ROW][C]15[/C][C]124[/C][C]119.588235294118[/C][C]4.41176470588235[/C][/ROW]
[ROW][C]16[/C][C]70[/C][C]119.588235294118[/C][C]-49.5882352941177[/C][/ROW]
[ROW][C]17[/C][C]168[/C][C]158.888888888889[/C][C]9.11111111111111[/C][/ROW]
[ROW][C]18[/C][C]115[/C][C]92.016393442623[/C][C]22.983606557377[/C][/ROW]
[ROW][C]19[/C][C]71[/C][C]92.016393442623[/C][C]-21.016393442623[/C][/ROW]
[ROW][C]20[/C][C]66[/C][C]72.1[/C][C]-6.1[/C][/ROW]
[ROW][C]21[/C][C]134[/C][C]119.588235294118[/C][C]14.4117647058823[/C][/ROW]
[ROW][C]22[/C][C]117[/C][C]119.588235294118[/C][C]-2.58823529411765[/C][/ROW]
[ROW][C]23[/C][C]108[/C][C]92.016393442623[/C][C]15.983606557377[/C][/ROW]
[ROW][C]24[/C][C]84[/C][C]72.1[/C][C]11.9[/C][/ROW]
[ROW][C]25[/C][C]156[/C][C]119.588235294118[/C][C]36.4117647058823[/C][/ROW]
[ROW][C]26[/C][C]120[/C][C]119.588235294118[/C][C]0.411764705882348[/C][/ROW]
[ROW][C]27[/C][C]114[/C][C]92.016393442623[/C][C]21.983606557377[/C][/ROW]
[ROW][C]28[/C][C]94[/C][C]92.016393442623[/C][C]1.98360655737704[/C][/ROW]
[ROW][C]29[/C][C]120[/C][C]119.588235294118[/C][C]0.411764705882348[/C][/ROW]
[ROW][C]30[/C][C]81[/C][C]92.016393442623[/C][C]-11.016393442623[/C][/ROW]
[ROW][C]31[/C][C]110[/C][C]119.588235294118[/C][C]-9.58823529411765[/C][/ROW]
[ROW][C]32[/C][C]133[/C][C]119.588235294118[/C][C]13.4117647058823[/C][/ROW]
[ROW][C]33[/C][C]122[/C][C]119.588235294118[/C][C]2.41176470588235[/C][/ROW]
[ROW][C]34[/C][C]158[/C][C]158.888888888889[/C][C]-0.888888888888886[/C][/ROW]
[ROW][C]35[/C][C]109[/C][C]92.016393442623[/C][C]16.983606557377[/C][/ROW]
[ROW][C]36[/C][C]124[/C][C]119.588235294118[/C][C]4.41176470588235[/C][/ROW]
[ROW][C]37[/C][C]39[/C][C]40.4285714285714[/C][C]-1.42857142857143[/C][/ROW]
[ROW][C]38[/C][C]92[/C][C]92.016393442623[/C][C]-0.0163934426229559[/C][/ROW]
[ROW][C]39[/C][C]126[/C][C]119.588235294118[/C][C]6.41176470588235[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]4.41176470588235[/C][C]-4.41176470588235[/C][/ROW]
[ROW][C]41[/C][C]70[/C][C]92.016393442623[/C][C]-22.016393442623[/C][/ROW]
[ROW][C]42[/C][C]37[/C][C]40.4285714285714[/C][C]-3.42857142857143[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]40.4285714285714[/C][C]-2.42857142857143[/C][/ROW]
[ROW][C]44[/C][C]120[/C][C]119.588235294118[/C][C]0.411764705882348[/C][/ROW]
[ROW][C]45[/C][C]93[/C][C]92.016393442623[/C][C]0.983606557377044[/C][/ROW]
[ROW][C]46[/C][C]95[/C][C]119.588235294118[/C][C]-24.5882352941177[/C][/ROW]
[ROW][C]47[/C][C]77[/C][C]72.1[/C][C]4.90000000000001[/C][/ROW]
[ROW][C]48[/C][C]90[/C][C]92.016393442623[/C][C]-2.01639344262296[/C][/ROW]
[ROW][C]49[/C][C]80[/C][C]92.016393442623[/C][C]-12.016393442623[/C][/ROW]
[ROW][C]50[/C][C]31[/C][C]40.4285714285714[/C][C]-9.42857142857143[/C][/ROW]
[ROW][C]51[/C][C]110[/C][C]119.588235294118[/C][C]-9.58823529411765[/C][/ROW]
[ROW][C]52[/C][C]66[/C][C]72.1[/C][C]-6.1[/C][/ROW]
[ROW][C]53[/C][C]138[/C][C]119.588235294118[/C][C]18.4117647058823[/C][/ROW]
[ROW][C]54[/C][C]133[/C][C]119.588235294118[/C][C]13.4117647058823[/C][/ROW]
[ROW][C]55[/C][C]113[/C][C]92.016393442623[/C][C]20.983606557377[/C][/ROW]
[ROW][C]56[/C][C]100[/C][C]92.016393442623[/C][C]7.98360655737704[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]4.41176470588235[/C][C]2.58823529411765[/C][/ROW]
[ROW][C]58[/C][C]140[/C][C]119.588235294118[/C][C]20.4117647058823[/C][/ROW]
[ROW][C]59[/C][C]61[/C][C]53.4385964912281[/C][C]7.56140350877193[/C][/ROW]
[ROW][C]60[/C][C]41[/C][C]40.4285714285714[/C][C]0.57142857142857[/C][/ROW]
[ROW][C]61[/C][C]96[/C][C]92.016393442623[/C][C]3.98360655737704[/C][/ROW]
[ROW][C]62[/C][C]164[/C][C]158.888888888889[/C][C]5.11111111111111[/C][/ROW]
[ROW][C]63[/C][C]78[/C][C]72.1[/C][C]5.9[/C][/ROW]
[ROW][C]64[/C][C]49[/C][C]53.4385964912281[/C][C]-4.43859649122807[/C][/ROW]
[ROW][C]65[/C][C]102[/C][C]92.016393442623[/C][C]9.98360655737704[/C][/ROW]
[ROW][C]66[/C][C]124[/C][C]119.588235294118[/C][C]4.41176470588235[/C][/ROW]
[ROW][C]67[/C][C]99[/C][C]92.016393442623[/C][C]6.98360655737704[/C][/ROW]
[ROW][C]68[/C][C]129[/C][C]119.588235294118[/C][C]9.41176470588235[/C][/ROW]
[ROW][C]69[/C][C]62[/C][C]72.1[/C][C]-10.1[/C][/ROW]
[ROW][C]70[/C][C]73[/C][C]119.588235294118[/C][C]-46.5882352941177[/C][/ROW]
[ROW][C]71[/C][C]114[/C][C]92.016393442623[/C][C]21.983606557377[/C][/ROW]
[ROW][C]72[/C][C]99[/C][C]92.016393442623[/C][C]6.98360655737704[/C][/ROW]
[ROW][C]73[/C][C]70[/C][C]92.016393442623[/C][C]-22.016393442623[/C][/ROW]
[ROW][C]74[/C][C]104[/C][C]92.016393442623[/C][C]11.983606557377[/C][/ROW]
[ROW][C]75[/C][C]116[/C][C]119.588235294118[/C][C]-3.58823529411765[/C][/ROW]
[ROW][C]76[/C][C]91[/C][C]92.016393442623[/C][C]-1.01639344262296[/C][/ROW]
[ROW][C]77[/C][C]74[/C][C]72.1[/C][C]1.90000000000001[/C][/ROW]
[ROW][C]78[/C][C]138[/C][C]119.588235294118[/C][C]18.4117647058823[/C][/ROW]
[ROW][C]79[/C][C]67[/C][C]72.1[/C][C]-5.09999999999999[/C][/ROW]
[ROW][C]80[/C][C]151[/C][C]119.588235294118[/C][C]31.4117647058823[/C][/ROW]
[ROW][C]81[/C][C]72[/C][C]92.016393442623[/C][C]-20.016393442623[/C][/ROW]
[ROW][C]82[/C][C]120[/C][C]119.588235294118[/C][C]0.411764705882348[/C][/ROW]
[ROW][C]83[/C][C]115[/C][C]119.588235294118[/C][C]-4.58823529411765[/C][/ROW]
[ROW][C]84[/C][C]105[/C][C]92.016393442623[/C][C]12.983606557377[/C][/ROW]
[ROW][C]85[/C][C]104[/C][C]119.588235294118[/C][C]-15.5882352941177[/C][/ROW]
[ROW][C]86[/C][C]108[/C][C]92.016393442623[/C][C]15.983606557377[/C][/ROW]
[ROW][C]87[/C][C]98[/C][C]92.016393442623[/C][C]5.98360655737704[/C][/ROW]
[ROW][C]88[/C][C]69[/C][C]72.1[/C][C]-3.09999999999999[/C][/ROW]
[ROW][C]89[/C][C]111[/C][C]119.588235294118[/C][C]-8.58823529411765[/C][/ROW]
[ROW][C]90[/C][C]99[/C][C]92.016393442623[/C][C]6.98360655737704[/C][/ROW]
[ROW][C]91[/C][C]71[/C][C]72.1[/C][C]-1.09999999999999[/C][/ROW]
[ROW][C]92[/C][C]27[/C][C]27[/C][C]0[/C][/ROW]
[ROW][C]93[/C][C]69[/C][C]72.1[/C][C]-3.09999999999999[/C][/ROW]
[ROW][C]94[/C][C]107[/C][C]92.016393442623[/C][C]14.983606557377[/C][/ROW]
[ROW][C]95[/C][C]73[/C][C]53.4385964912281[/C][C]19.5614035087719[/C][/ROW]
[ROW][C]96[/C][C]107[/C][C]92.016393442623[/C][C]14.983606557377[/C][/ROW]
[ROW][C]97[/C][C]93[/C][C]119.588235294118[/C][C]-26.5882352941177[/C][/ROW]
[ROW][C]98[/C][C]129[/C][C]119.588235294118[/C][C]9.41176470588235[/C][/ROW]
[ROW][C]99[/C][C]69[/C][C]92.016393442623[/C][C]-23.016393442623[/C][/ROW]
[ROW][C]100[/C][C]118[/C][C]119.588235294118[/C][C]-1.58823529411765[/C][/ROW]
[ROW][C]101[/C][C]73[/C][C]72.1[/C][C]0.900000000000006[/C][/ROW]
[ROW][C]102[/C][C]119[/C][C]119.588235294118[/C][C]-0.588235294117652[/C][/ROW]
[ROW][C]103[/C][C]104[/C][C]92.016393442623[/C][C]11.983606557377[/C][/ROW]
[ROW][C]104[/C][C]107[/C][C]92.016393442623[/C][C]14.983606557377[/C][/ROW]
[ROW][C]105[/C][C]99[/C][C]92.016393442623[/C][C]6.98360655737704[/C][/ROW]
[ROW][C]106[/C][C]90[/C][C]92.016393442623[/C][C]-2.01639344262296[/C][/ROW]
[ROW][C]107[/C][C]197[/C][C]158.888888888889[/C][C]38.1111111111111[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]53.4385964912281[/C][C]-17.4385964912281[/C][/ROW]
[ROW][C]109[/C][C]85[/C][C]72.1[/C][C]12.9[/C][/ROW]
[ROW][C]110[/C][C]139[/C][C]119.588235294118[/C][C]19.4117647058823[/C][/ROW]
[ROW][C]111[/C][C]106[/C][C]119.588235294118[/C][C]-13.5882352941177[/C][/ROW]
[ROW][C]112[/C][C]50[/C][C]92.016393442623[/C][C]-42.016393442623[/C][/ROW]
[ROW][C]113[/C][C]64[/C][C]38.8181818181818[/C][C]25.1818181818182[/C][/ROW]
[ROW][C]114[/C][C]31[/C][C]53.4385964912281[/C][C]-22.4385964912281[/C][/ROW]
[ROW][C]115[/C][C]63[/C][C]92.016393442623[/C][C]-29.016393442623[/C][/ROW]
[ROW][C]116[/C][C]92[/C][C]92.016393442623[/C][C]-0.0163934426229559[/C][/ROW]
[ROW][C]117[/C][C]106[/C][C]119.588235294118[/C][C]-13.5882352941177[/C][/ROW]
[ROW][C]118[/C][C]63[/C][C]53.4385964912281[/C][C]9.56140350877193[/C][/ROW]
[ROW][C]119[/C][C]69[/C][C]72.1[/C][C]-3.09999999999999[/C][/ROW]
[ROW][C]120[/C][C]41[/C][C]40.4285714285714[/C][C]0.57142857142857[/C][/ROW]
[ROW][C]121[/C][C]56[/C][C]53.4385964912281[/C][C]2.56140350877193[/C][/ROW]
[ROW][C]122[/C][C]25[/C][C]27[/C][C]-2[/C][/ROW]
[ROW][C]123[/C][C]65[/C][C]53.4385964912281[/C][C]11.5614035087719[/C][/ROW]
[ROW][C]124[/C][C]93[/C][C]92.016393442623[/C][C]0.983606557377044[/C][/ROW]
[ROW][C]125[/C][C]114[/C][C]92.016393442623[/C][C]21.983606557377[/C][/ROW]
[ROW][C]126[/C][C]38[/C][C]27[/C][C]11[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]40.4285714285714[/C][C]3.57142857142857[/C][/ROW]
[ROW][C]128[/C][C]87[/C][C]72.1[/C][C]14.9[/C][/ROW]
[ROW][C]129[/C][C]110[/C][C]119.588235294118[/C][C]-9.58823529411765[/C][/ROW]
[ROW][C]130[/C][C]0[/C][C]4.41176470588235[/C][C]-4.41176470588235[/C][/ROW]
[ROW][C]131[/C][C]27[/C][C]27[/C][C]0[/C][/ROW]
[ROW][C]132[/C][C]83[/C][C]92.016393442623[/C][C]-9.01639344262296[/C][/ROW]
[ROW][C]133[/C][C]30[/C][C]27[/C][C]3[/C][/ROW]
[ROW][C]134[/C][C]80[/C][C]92.016393442623[/C][C]-12.016393442623[/C][/ROW]
[ROW][C]135[/C][C]98[/C][C]119.588235294118[/C][C]-21.5882352941177[/C][/ROW]
[ROW][C]136[/C][C]82[/C][C]92.016393442623[/C][C]-10.016393442623[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]4.41176470588235[/C][C]-4.41176470588235[/C][/ROW]
[ROW][C]138[/C][C]60[/C][C]72.1[/C][C]-12.1[/C][/ROW]
[ROW][C]139[/C][C]28[/C][C]27[/C][C]1[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]4.41176470588235[/C][C]4.58823529411765[/C][/ROW]
[ROW][C]141[/C][C]33[/C][C]40.4285714285714[/C][C]-7.42857142857143[/C][/ROW]
[ROW][C]142[/C][C]59[/C][C]53.4385964912281[/C][C]5.56140350877193[/C][/ROW]
[ROW][C]143[/C][C]49[/C][C]53.4385964912281[/C][C]-4.43859649122807[/C][/ROW]
[ROW][C]144[/C][C]115[/C][C]119.588235294118[/C][C]-4.58823529411765[/C][/ROW]
[ROW][C]145[/C][C]140[/C][C]119.588235294118[/C][C]20.4117647058823[/C][/ROW]
[ROW][C]146[/C][C]49[/C][C]53.4385964912281[/C][C]-4.43859649122807[/C][/ROW]
[ROW][C]147[/C][C]120[/C][C]119.588235294118[/C][C]0.411764705882348[/C][/ROW]
[ROW][C]148[/C][C]66[/C][C]72.1[/C][C]-6.1[/C][/ROW]
[ROW][C]149[/C][C]21[/C][C]27[/C][C]-6[/C][/ROW]
[ROW][C]150[/C][C]124[/C][C]119.588235294118[/C][C]4.41176470588235[/C][/ROW]
[ROW][C]151[/C][C]152[/C][C]158.888888888889[/C][C]-6.88888888888889[/C][/ROW]
[ROW][C]152[/C][C]139[/C][C]158.888888888889[/C][C]-19.8888888888889[/C][/ROW]
[ROW][C]153[/C][C]38[/C][C]40.4285714285714[/C][C]-2.42857142857143[/C][/ROW]
[ROW][C]154[/C][C]144[/C][C]158.888888888889[/C][C]-14.8888888888889[/C][/ROW]
[ROW][C]155[/C][C]120[/C][C]119.588235294118[/C][C]0.411764705882348[/C][/ROW]
[ROW][C]156[/C][C]160[/C][C]158.888888888889[/C][C]1.11111111111111[/C][/ROW]
[ROW][C]157[/C][C]114[/C][C]92.016393442623[/C][C]21.983606557377[/C][/ROW]
[ROW][C]158[/C][C]39[/C][C]40.4285714285714[/C][C]-1.42857142857143[/C][/ROW]
[ROW][C]159[/C][C]78[/C][C]92.016393442623[/C][C]-14.016393442623[/C][/ROW]
[ROW][C]160[/C][C]119[/C][C]92.016393442623[/C][C]26.983606557377[/C][/ROW]
[ROW][C]161[/C][C]141[/C][C]119.588235294118[/C][C]21.4117647058823[/C][/ROW]
[ROW][C]162[/C][C]101[/C][C]92.016393442623[/C][C]8.98360655737704[/C][/ROW]
[ROW][C]163[/C][C]56[/C][C]40.4285714285714[/C][C]15.5714285714286[/C][/ROW]
[ROW][C]164[/C][C]133[/C][C]119.588235294118[/C][C]13.4117647058823[/C][/ROW]
[ROW][C]165[/C][C]83[/C][C]92.016393442623[/C][C]-9.01639344262296[/C][/ROW]
[ROW][C]166[/C][C]116[/C][C]119.588235294118[/C][C]-3.58823529411765[/C][/ROW]
[ROW][C]167[/C][C]90[/C][C]92.016393442623[/C][C]-2.01639344262296[/C][/ROW]
[ROW][C]168[/C][C]36[/C][C]92.016393442623[/C][C]-56.016393442623[/C][/ROW]
[ROW][C]169[/C][C]50[/C][C]53.4385964912281[/C][C]-3.43859649122807[/C][/ROW]
[ROW][C]170[/C][C]61[/C][C]53.4385964912281[/C][C]7.56140350877193[/C][/ROW]
[ROW][C]171[/C][C]97[/C][C]92.016393442623[/C][C]4.98360655737704[/C][/ROW]
[ROW][C]172[/C][C]98[/C][C]92.016393442623[/C][C]5.98360655737704[/C][/ROW]
[ROW][C]173[/C][C]78[/C][C]72.1[/C][C]5.9[/C][/ROW]
[ROW][C]174[/C][C]117[/C][C]119.588235294118[/C][C]-2.58823529411765[/C][/ROW]
[ROW][C]175[/C][C]148[/C][C]119.588235294118[/C][C]28.4117647058823[/C][/ROW]
[ROW][C]176[/C][C]41[/C][C]40.4285714285714[/C][C]0.57142857142857[/C][/ROW]
[ROW][C]177[/C][C]105[/C][C]92.016393442623[/C][C]12.983606557377[/C][/ROW]
[ROW][C]178[/C][C]55[/C][C]53.4385964912281[/C][C]1.56140350877193[/C][/ROW]
[ROW][C]179[/C][C]132[/C][C]119.588235294118[/C][C]12.4117647058823[/C][/ROW]
[ROW][C]180[/C][C]44[/C][C]40.4285714285714[/C][C]3.57142857142857[/C][/ROW]
[ROW][C]181[/C][C]21[/C][C]27[/C][C]-6[/C][/ROW]
[ROW][C]182[/C][C]50[/C][C]53.4385964912281[/C][C]-3.43859649122807[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]4.41176470588235[/C][C]-4.41176470588235[/C][/ROW]
[ROW][C]184[/C][C]73[/C][C]92.016393442623[/C][C]-19.016393442623[/C][/ROW]
[ROW][C]185[/C][C]86[/C][C]119.588235294118[/C][C]-33.5882352941177[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]4.41176470588235[/C][C]-4.41176470588235[/C][/ROW]
[ROW][C]187[/C][C]13[/C][C]4.41176470588235[/C][C]8.58823529411765[/C][/ROW]
[ROW][C]188[/C][C]4[/C][C]4.41176470588235[/C][C]-0.411764705882353[/C][/ROW]
[ROW][C]189[/C][C]57[/C][C]53.4385964912281[/C][C]3.56140350877193[/C][/ROW]
[ROW][C]190[/C][C]48[/C][C]92.016393442623[/C][C]-44.016393442623[/C][/ROW]
[ROW][C]191[/C][C]46[/C][C]72.1[/C][C]-26.1[/C][/ROW]
[ROW][C]192[/C][C]48[/C][C]53.4385964912281[/C][C]-5.43859649122807[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]27[/C][C]5[/C][/ROW]
[ROW][C]194[/C][C]68[/C][C]72.1[/C][C]-4.09999999999999[/C][/ROW]
[ROW][C]195[/C][C]87[/C][C]72.1[/C][C]14.9[/C][/ROW]
[ROW][C]196[/C][C]43[/C][C]40.4285714285714[/C][C]2.57142857142857[/C][/ROW]
[ROW][C]197[/C][C]67[/C][C]53.4385964912281[/C][C]13.5614035087719[/C][/ROW]
[ROW][C]198[/C][C]46[/C][C]40.4285714285714[/C][C]5.57142857142857[/C][/ROW]
[ROW][C]199[/C][C]46[/C][C]53.4385964912281[/C][C]-7.43859649122807[/C][/ROW]
[ROW][C]200[/C][C]56[/C][C]40.4285714285714[/C][C]15.5714285714286[/C][/ROW]
[ROW][C]201[/C][C]48[/C][C]53.4385964912281[/C][C]-5.43859649122807[/C][/ROW]
[ROW][C]202[/C][C]44[/C][C]38.8181818181818[/C][C]5.18181818181818[/C][/ROW]
[ROW][C]203[/C][C]60[/C][C]53.4385964912281[/C][C]6.56140350877193[/C][/ROW]
[ROW][C]204[/C][C]65[/C][C]53.4385964912281[/C][C]11.5614035087719[/C][/ROW]
[ROW][C]205[/C][C]55[/C][C]53.4385964912281[/C][C]1.56140350877193[/C][/ROW]
[ROW][C]206[/C][C]38[/C][C]38.8181818181818[/C][C]-0.81818181818182[/C][/ROW]
[ROW][C]207[/C][C]52[/C][C]53.4385964912281[/C][C]-1.43859649122807[/C][/ROW]
[ROW][C]208[/C][C]60[/C][C]53.4385964912281[/C][C]6.56140350877193[/C][/ROW]
[ROW][C]209[/C][C]54[/C][C]53.4385964912281[/C][C]0.561403508771932[/C][/ROW]
[ROW][C]210[/C][C]86[/C][C]72.1[/C][C]13.9[/C][/ROW]
[ROW][C]211[/C][C]24[/C][C]27[/C][C]-3[/C][/ROW]
[ROW][C]212[/C][C]52[/C][C]53.4385964912281[/C][C]-1.43859649122807[/C][/ROW]
[ROW][C]213[/C][C]49[/C][C]53.4385964912281[/C][C]-4.43859649122807[/C][/ROW]
[ROW][C]214[/C][C]61[/C][C]53.4385964912281[/C][C]7.56140350877193[/C][/ROW]
[ROW][C]215[/C][C]61[/C][C]72.1[/C][C]-11.1[/C][/ROW]
[ROW][C]216[/C][C]81[/C][C]72.1[/C][C]8.9[/C][/ROW]
[ROW][C]217[/C][C]43[/C][C]40.4285714285714[/C][C]2.57142857142857[/C][/ROW]
[ROW][C]218[/C][C]40[/C][C]40.4285714285714[/C][C]-0.428571428571431[/C][/ROW]
[ROW][C]219[/C][C]40[/C][C]53.4385964912281[/C][C]-13.4385964912281[/C][/ROW]
[ROW][C]220[/C][C]56[/C][C]53.4385964912281[/C][C]2.56140350877193[/C][/ROW]
[ROW][C]221[/C][C]68[/C][C]53.4385964912281[/C][C]14.5614035087719[/C][/ROW]
[ROW][C]222[/C][C]79[/C][C]72.1[/C][C]6.9[/C][/ROW]
[ROW][C]223[/C][C]47[/C][C]53.4385964912281[/C][C]-6.43859649122807[/C][/ROW]
[ROW][C]224[/C][C]57[/C][C]53.4385964912281[/C][C]3.56140350877193[/C][/ROW]
[ROW][C]225[/C][C]41[/C][C]38.8181818181818[/C][C]2.18181818181818[/C][/ROW]
[ROW][C]226[/C][C]29[/C][C]40.4285714285714[/C][C]-11.4285714285714[/C][/ROW]
[ROW][C]227[/C][C]3[/C][C]4.41176470588235[/C][C]-1.41176470588235[/C][/ROW]
[ROW][C]228[/C][C]60[/C][C]53.4385964912281[/C][C]6.56140350877193[/C][/ROW]
[ROW][C]229[/C][C]30[/C][C]27[/C][C]3[/C][/ROW]
[ROW][C]230[/C][C]79[/C][C]72.1[/C][C]6.9[/C][/ROW]
[ROW][C]231[/C][C]47[/C][C]38.8181818181818[/C][C]8.18181818181818[/C][/ROW]
[ROW][C]232[/C][C]40[/C][C]40.4285714285714[/C][C]-0.428571428571431[/C][/ROW]
[ROW][C]233[/C][C]48[/C][C]40.4285714285714[/C][C]7.57142857142857[/C][/ROW]
[ROW][C]234[/C][C]36[/C][C]38.8181818181818[/C][C]-2.81818181818182[/C][/ROW]
[ROW][C]235[/C][C]42[/C][C]53.4385964912281[/C][C]-11.4385964912281[/C][/ROW]
[ROW][C]236[/C][C]49[/C][C]53.4385964912281[/C][C]-4.43859649122807[/C][/ROW]
[ROW][C]237[/C][C]57[/C][C]53.4385964912281[/C][C]3.56140350877193[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]38.8181818181818[/C][C]-26.8181818181818[/C][/ROW]
[ROW][C]239[/C][C]40[/C][C]53.4385964912281[/C][C]-13.4385964912281[/C][/ROW]
[ROW][C]240[/C][C]43[/C][C]38.8181818181818[/C][C]4.18181818181818[/C][/ROW]
[ROW][C]241[/C][C]33[/C][C]40.4285714285714[/C][C]-7.42857142857143[/C][/ROW]
[ROW][C]242[/C][C]77[/C][C]72.1[/C][C]4.90000000000001[/C][/ROW]
[ROW][C]243[/C][C]43[/C][C]38.8181818181818[/C][C]4.18181818181818[/C][/ROW]
[ROW][C]244[/C][C]45[/C][C]40.4285714285714[/C][C]4.57142857142857[/C][/ROW]
[ROW][C]245[/C][C]47[/C][C]40.4285714285714[/C][C]6.57142857142857[/C][/ROW]
[ROW][C]246[/C][C]43[/C][C]53.4385964912281[/C][C]-10.4385964912281[/C][/ROW]
[ROW][C]247[/C][C]45[/C][C]40.4285714285714[/C][C]4.57142857142857[/C][/ROW]
[ROW][C]248[/C][C]50[/C][C]40.4285714285714[/C][C]9.57142857142857[/C][/ROW]
[ROW][C]249[/C][C]35[/C][C]27[/C][C]8[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]4.41176470588235[/C][C]2.58823529411765[/C][/ROW]
[ROW][C]251[/C][C]71[/C][C]72.1[/C][C]-1.09999999999999[/C][/ROW]
[ROW][C]252[/C][C]67[/C][C]72.1[/C][C]-5.09999999999999[/C][/ROW]
[ROW][C]253[/C][C]0[/C][C]4.41176470588235[/C][C]-4.41176470588235[/C][/ROW]
[ROW][C]254[/C][C]62[/C][C]53.4385964912281[/C][C]8.56140350877193[/C][/ROW]
[ROW][C]255[/C][C]54[/C][C]53.4385964912281[/C][C]0.561403508771932[/C][/ROW]
[ROW][C]256[/C][C]4[/C][C]4.41176470588235[/C][C]-0.411764705882353[/C][/ROW]
[ROW][C]257[/C][C]25[/C][C]27[/C][C]-2[/C][/ROW]
[ROW][C]258[/C][C]40[/C][C]53.4385964912281[/C][C]-13.4385964912281[/C][/ROW]
[ROW][C]259[/C][C]38[/C][C]40.4285714285714[/C][C]-2.42857142857143[/C][/ROW]
[ROW][C]260[/C][C]19[/C][C]27[/C][C]-8[/C][/ROW]
[ROW][C]261[/C][C]17[/C][C]40.4285714285714[/C][C]-23.4285714285714[/C][/ROW]
[ROW][C]262[/C][C]67[/C][C]53.4385964912281[/C][C]13.5614035087719[/C][/ROW]
[ROW][C]263[/C][C]14[/C][C]4.41176470588235[/C][C]9.58823529411765[/C][/ROW]
[ROW][C]264[/C][C]30[/C][C]40.4285714285714[/C][C]-10.4285714285714[/C][/ROW]
[ROW][C]265[/C][C]54[/C][C]40.4285714285714[/C][C]13.5714285714286[/C][/ROW]
[ROW][C]266[/C][C]35[/C][C]40.4285714285714[/C][C]-5.42857142857143[/C][/ROW]
[ROW][C]267[/C][C]59[/C][C]53.4385964912281[/C][C]5.56140350877193[/C][/ROW]
[ROW][C]268[/C][C]24[/C][C]27[/C][C]-3[/C][/ROW]
[ROW][C]269[/C][C]58[/C][C]53.4385964912281[/C][C]4.56140350877193[/C][/ROW]
[ROW][C]270[/C][C]42[/C][C]53.4385964912281[/C][C]-11.4385964912281[/C][/ROW]
[ROW][C]271[/C][C]46[/C][C]53.4385964912281[/C][C]-7.43859649122807[/C][/ROW]
[ROW][C]272[/C][C]61[/C][C]53.4385964912281[/C][C]7.56140350877193[/C][/ROW]
[ROW][C]273[/C][C]3[/C][C]4.41176470588235[/C][C]-1.41176470588235[/C][/ROW]
[ROW][C]274[/C][C]52[/C][C]53.4385964912281[/C][C]-1.43859649122807[/C][/ROW]
[ROW][C]275[/C][C]25[/C][C]27[/C][C]-2[/C][/ROW]
[ROW][C]276[/C][C]40[/C][C]53.4385964912281[/C][C]-13.4385964912281[/C][/ROW]
[ROW][C]277[/C][C]32[/C][C]40.4285714285714[/C][C]-8.42857142857143[/C][/ROW]
[ROW][C]278[/C][C]4[/C][C]4.41176470588235[/C][C]-0.411764705882353[/C][/ROW]
[ROW][C]279[/C][C]49[/C][C]40.4285714285714[/C][C]8.57142857142857[/C][/ROW]
[ROW][C]280[/C][C]63[/C][C]53.4385964912281[/C][C]9.56140350877193[/C][/ROW]
[ROW][C]281[/C][C]67[/C][C]53.4385964912281[/C][C]13.5614035087719[/C][/ROW]
[ROW][C]282[/C][C]32[/C][C]27[/C][C]5[/C][/ROW]
[ROW][C]283[/C][C]23[/C][C]27[/C][C]-4[/C][/ROW]
[ROW][C]284[/C][C]7[/C][C]4.41176470588235[/C][C]2.58823529411765[/C][/ROW]
[ROW][C]285[/C][C]54[/C][C]53.4385964912281[/C][C]0.561403508771932[/C][/ROW]
[ROW][C]286[/C][C]37[/C][C]38.8181818181818[/C][C]-1.81818181818182[/C][/ROW]
[ROW][C]287[/C][C]35[/C][C]40.4285714285714[/C][C]-5.42857142857143[/C][/ROW]
[ROW][C]288[/C][C]51[/C][C]53.4385964912281[/C][C]-2.43859649122807[/C][/ROW]
[ROW][C]289[/C][C]39[/C][C]53.4385964912281[/C][C]-14.4385964912281[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155022&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155022&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:

Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
19492.0163934426231.98360655737704
210392.01639344262310.983606557377
393119.588235294118-26.5882352941177
410392.01639344262310.983606557377
55153.4385964912281-2.43859649122807
67092.016393442623-22.016393442623
79192.016393442623-1.01639344262296
82238.8181818181818-16.8181818181818
93840.4285714285714-2.42857142857143
109392.0163934426230.983606557377044
116072.1-12.1
12123119.5882352941183.41176470588235
13148158.888888888889-10.8888888888889
149092.016393442623-2.01639344262296
15124119.5882352941184.41176470588235
1670119.588235294118-49.5882352941177
17168158.8888888888899.11111111111111
1811592.01639344262322.983606557377
197192.016393442623-21.016393442623
206672.1-6.1
21134119.58823529411814.4117647058823
22117119.588235294118-2.58823529411765
2310892.01639344262315.983606557377
248472.111.9
25156119.58823529411836.4117647058823
26120119.5882352941180.411764705882348
2711492.01639344262321.983606557377
289492.0163934426231.98360655737704
29120119.5882352941180.411764705882348
308192.016393442623-11.016393442623
31110119.588235294118-9.58823529411765
32133119.58823529411813.4117647058823
33122119.5882352941182.41176470588235
34158158.888888888889-0.888888888888886
3510992.01639344262316.983606557377
36124119.5882352941184.41176470588235
373940.4285714285714-1.42857142857143
389292.016393442623-0.0163934426229559
39126119.5882352941186.41176470588235
4004.41176470588235-4.41176470588235
417092.016393442623-22.016393442623
423740.4285714285714-3.42857142857143
433840.4285714285714-2.42857142857143
44120119.5882352941180.411764705882348
459392.0163934426230.983606557377044
4695119.588235294118-24.5882352941177
477772.14.90000000000001
489092.016393442623-2.01639344262296
498092.016393442623-12.016393442623
503140.4285714285714-9.42857142857143
51110119.588235294118-9.58823529411765
526672.1-6.1
53138119.58823529411818.4117647058823
54133119.58823529411813.4117647058823
5511392.01639344262320.983606557377
5610092.0163934426237.98360655737704
5774.411764705882352.58823529411765
58140119.58823529411820.4117647058823
596153.43859649122817.56140350877193
604140.42857142857140.57142857142857
619692.0163934426233.98360655737704
62164158.8888888888895.11111111111111
637872.15.9
644953.4385964912281-4.43859649122807
6510292.0163934426239.98360655737704
66124119.5882352941184.41176470588235
679992.0163934426236.98360655737704
68129119.5882352941189.41176470588235
696272.1-10.1
7073119.588235294118-46.5882352941177
7111492.01639344262321.983606557377
729992.0163934426236.98360655737704
737092.016393442623-22.016393442623
7410492.01639344262311.983606557377
75116119.588235294118-3.58823529411765
769192.016393442623-1.01639344262296
777472.11.90000000000001
78138119.58823529411818.4117647058823
796772.1-5.09999999999999
80151119.58823529411831.4117647058823
817292.016393442623-20.016393442623
82120119.5882352941180.411764705882348
83115119.588235294118-4.58823529411765
8410592.01639344262312.983606557377
85104119.588235294118-15.5882352941177
8610892.01639344262315.983606557377
879892.0163934426235.98360655737704
886972.1-3.09999999999999
89111119.588235294118-8.58823529411765
909992.0163934426236.98360655737704
917172.1-1.09999999999999
9227270
936972.1-3.09999999999999
9410792.01639344262314.983606557377
957353.438596491228119.5614035087719
9610792.01639344262314.983606557377
9793119.588235294118-26.5882352941177
98129119.5882352941189.41176470588235
996992.016393442623-23.016393442623
100118119.588235294118-1.58823529411765
1017372.10.900000000000006
102119119.588235294118-0.588235294117652
10310492.01639344262311.983606557377
10410792.01639344262314.983606557377
1059992.0163934426236.98360655737704
1069092.016393442623-2.01639344262296
107197158.88888888888938.1111111111111
1083653.4385964912281-17.4385964912281
1098572.112.9
110139119.58823529411819.4117647058823
111106119.588235294118-13.5882352941177
1125092.016393442623-42.016393442623
1136438.818181818181825.1818181818182
1143153.4385964912281-22.4385964912281
1156392.016393442623-29.016393442623
1169292.016393442623-0.0163934426229559
117106119.588235294118-13.5882352941177
1186353.43859649122819.56140350877193
1196972.1-3.09999999999999
1204140.42857142857140.57142857142857
1215653.43859649122812.56140350877193
1222527-2
1236553.438596491228111.5614035087719
1249392.0163934426230.983606557377044
12511492.01639344262321.983606557377
126382711
1274440.42857142857143.57142857142857
1288772.114.9
129110119.588235294118-9.58823529411765
13004.41176470588235-4.41176470588235
13127270
1328392.016393442623-9.01639344262296
13330273
1348092.016393442623-12.016393442623
13598119.588235294118-21.5882352941177
1368292.016393442623-10.016393442623
13704.41176470588235-4.41176470588235
1386072.1-12.1
13928271
14094.411764705882354.58823529411765
1413340.4285714285714-7.42857142857143
1425953.43859649122815.56140350877193
1434953.4385964912281-4.43859649122807
144115119.588235294118-4.58823529411765
145140119.58823529411820.4117647058823
1464953.4385964912281-4.43859649122807
147120119.5882352941180.411764705882348
1486672.1-6.1
1492127-6
150124119.5882352941184.41176470588235
151152158.888888888889-6.88888888888889
152139158.888888888889-19.8888888888889
1533840.4285714285714-2.42857142857143
154144158.888888888889-14.8888888888889
155120119.5882352941180.411764705882348
156160158.8888888888891.11111111111111
15711492.01639344262321.983606557377
1583940.4285714285714-1.42857142857143
1597892.016393442623-14.016393442623
16011992.01639344262326.983606557377
161141119.58823529411821.4117647058823
16210192.0163934426238.98360655737704
1635640.428571428571415.5714285714286
164133119.58823529411813.4117647058823
1658392.016393442623-9.01639344262296
166116119.588235294118-3.58823529411765
1679092.016393442623-2.01639344262296
1683692.016393442623-56.016393442623
1695053.4385964912281-3.43859649122807
1706153.43859649122817.56140350877193
1719792.0163934426234.98360655737704
1729892.0163934426235.98360655737704
1737872.15.9
174117119.588235294118-2.58823529411765
175148119.58823529411828.4117647058823
1764140.42857142857140.57142857142857
17710592.01639344262312.983606557377
1785553.43859649122811.56140350877193
179132119.58823529411812.4117647058823
1804440.42857142857143.57142857142857
1812127-6
1825053.4385964912281-3.43859649122807
18304.41176470588235-4.41176470588235
1847392.016393442623-19.016393442623
18586119.588235294118-33.5882352941177
18604.41176470588235-4.41176470588235
187134.411764705882358.58823529411765
18844.41176470588235-0.411764705882353
1895753.43859649122813.56140350877193
1904892.016393442623-44.016393442623
1914672.1-26.1
1924853.4385964912281-5.43859649122807
19332275
1946872.1-4.09999999999999
1958772.114.9
1964340.42857142857142.57142857142857
1976753.438596491228113.5614035087719
1984640.42857142857145.57142857142857
1994653.4385964912281-7.43859649122807
2005640.428571428571415.5714285714286
2014853.4385964912281-5.43859649122807
2024438.81818181818185.18181818181818
2036053.43859649122816.56140350877193
2046553.438596491228111.5614035087719
2055553.43859649122811.56140350877193
2063838.8181818181818-0.81818181818182
2075253.4385964912281-1.43859649122807
2086053.43859649122816.56140350877193
2095453.43859649122810.561403508771932
2108672.113.9
2112427-3
2125253.4385964912281-1.43859649122807
2134953.4385964912281-4.43859649122807
2146153.43859649122817.56140350877193
2156172.1-11.1
2168172.18.9
2174340.42857142857142.57142857142857
2184040.4285714285714-0.428571428571431
2194053.4385964912281-13.4385964912281
2205653.43859649122812.56140350877193
2216853.438596491228114.5614035087719
2227972.16.9
2234753.4385964912281-6.43859649122807
2245753.43859649122813.56140350877193
2254138.81818181818182.18181818181818
2262940.4285714285714-11.4285714285714
22734.41176470588235-1.41176470588235
2286053.43859649122816.56140350877193
22930273
2307972.16.9
2314738.81818181818188.18181818181818
2324040.4285714285714-0.428571428571431
2334840.42857142857147.57142857142857
2343638.8181818181818-2.81818181818182
2354253.4385964912281-11.4385964912281
2364953.4385964912281-4.43859649122807
2375753.43859649122813.56140350877193
2381238.8181818181818-26.8181818181818
2394053.4385964912281-13.4385964912281
2404338.81818181818184.18181818181818
2413340.4285714285714-7.42857142857143
2427772.14.90000000000001
2434338.81818181818184.18181818181818
2444540.42857142857144.57142857142857
2454740.42857142857146.57142857142857
2464353.4385964912281-10.4385964912281
2474540.42857142857144.57142857142857
2485040.42857142857149.57142857142857
24935278
25074.411764705882352.58823529411765
2517172.1-1.09999999999999
2526772.1-5.09999999999999
25304.41176470588235-4.41176470588235
2546253.43859649122818.56140350877193
2555453.43859649122810.561403508771932
25644.41176470588235-0.411764705882353
2572527-2
2584053.4385964912281-13.4385964912281
2593840.4285714285714-2.42857142857143
2601927-8
2611740.4285714285714-23.4285714285714
2626753.438596491228113.5614035087719
263144.411764705882359.58823529411765
2643040.4285714285714-10.4285714285714
2655440.428571428571413.5714285714286
2663540.4285714285714-5.42857142857143
2675953.43859649122815.56140350877193
2682427-3
2695853.43859649122814.56140350877193
2704253.4385964912281-11.4385964912281
2714653.4385964912281-7.43859649122807
2726153.43859649122817.56140350877193
27334.41176470588235-1.41176470588235
2745253.4385964912281-1.43859649122807
2752527-2
2764053.4385964912281-13.4385964912281
2773240.4285714285714-8.42857142857143
27844.41176470588235-0.411764705882353
2794940.42857142857148.57142857142857
2806353.43859649122819.56140350877193
2816753.438596491228113.5614035087719
28232275
2832327-4
28474.411764705882352.58823529411765
2855453.43859649122810.561403508771932
2863738.8181818181818-1.81818181818182
2873540.4285714285714-5.42857142857143
2885153.4385964912281-2.43859649122807
2893953.4385964912281-14.4385964912281


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 10 ; par2 = none ; par3 = 3 ; par4 = no ;
Parameters (R input):
par1 = 10 ; par2 = none ; par3 = 3 ; par4 = no ;
R code (references can be found in the software module):
library(party)
library(Hmisc)
par1 <- as.numeric(par1)
par3 <- as.numeric(par3)
x <- data.frame(t(y))
is.data.frame(x)
x <- x[!is.na(x[,par1]),]
k <- length(x[1,])
n <- length(x[,1])
colnames(x)[par1]
x[,par1]
if (par2 == 'kmeans') {
cl <- kmeans(x[,par1], par3)
print(cl)
clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
clm <- clm[sort.list(clm[,1]),]
for (i in 1:par3) {
cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
}
cl$cluster <- as.factor(cl$cluster)
print(cl$cluster)
x[,par1] <- cl$cluster
}
if (par2 == 'quantiles') {
x[,par1] <- cut2(x[,par1],g=par3)
}
if (par2 == 'hclust') {
hc <- hclust(dist(x[,par1])^2, 'cen')
print(hc)
memb <- cutree(hc, k = par3)
dum <- c(mean(x[memb==1,par1]))
for (i in 2:par3) {
dum <- c(dum, mean(x[memb==i,par1]))
}
hcm <- matrix(cbind(dum,1:par3),ncol=2)
hcm <- hcm[sort.list(hcm[,1]),]
for (i in 1:par3) {
memb[memb==hcm[i,2]] <- paste('C',i,sep='')
}
memb <- as.factor(memb)
print(memb)
x[,par1] <- memb
}
if (par2=='equal') {
ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
x[,par1] <- as.factor(ed)
}
table(x[,par1])
colnames(x)
colnames(x)[par1]
x[,par1]
if (par2 == 'none') {
m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
}
load(file='createtable')
if (par2 != 'none') {
m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
if (par4=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Prediction (training)',par3+1,TRUE)
a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Actual',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
a<-table.row.end(a)
for (i in 1:10) {
ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
if (i==1) {
m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
m.ct.i.actu <- x[ind==1,par1]
m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
m.ct.x.actu <- x[ind==2,par1]
} else {
m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
}
}
print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
numer <- numer + m.ct.i.tab[i,i]
}
print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
numer <- numer + m.ct.x.tab[i,i]
}
print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'Overall',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.i.cp,4))
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.x.cp,4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
}
}
m
bitmap(file='test1.png')
plot(m)
dev.off()
bitmap(file='test1a.png')
plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
dev.off()
if (par2 == 'none') {
forec <- predict(m)
result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
colnames(result) <- c('Actuals','Forecasts','Residuals')
print(result)
}
if (par2 != 'none') {
print(cbind(as.factor(x[,par1]),predict(m)))
myt <- table(as.factor(x[,par1]),predict(m))
print(myt)
}
bitmap(file='test2.png')
if(par2=='none') {
op <- par(mfrow=c(2,2))
plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
par(op)
}
if(par2!='none') {
plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
}
dev.off()
if (par2 == 'none') {
detcoef <- cor(result$Forecasts,result$Actuals)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goodness of Fit',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.element(a,round(detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'R-squared',1,TRUE)
a<-table.element(a,round(detcoef*detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'RMSE',1,TRUE)
a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#',header=TRUE)
a<-table.element(a,'Actuals',header=TRUE)
a<-table.element(a,'Forecasts',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(result$Actuals)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,result$Actuals[i])
a<-table.element(a,result$Forecasts[i])
a<-table.element(a,result$Residuals[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if (par2 != 'none') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
for (i in 1:par3) {
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (j in 1:par3) {
a<-table.element(a,myt[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}