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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_regression_trees1.wasp

Title produced by software

Recursive Partitioning (Regression Trees)

Date of computation

Wed, 14 Dec 2011 15:44:33 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/14/t1323895493bzbtkjc08q7d9nl.htm/, Retrieved Wed, 01 May 2024 22:51:31 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155245, Retrieved Wed, 01 May 2024 22:51:31 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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 20:06:20] [b98453cac15ba1066b407e146608df68]
- R PD    [Recursive Partitioning (Regression Trees)] [] [2011-12-14 20:44:33] [86c924663d3d275e16f9cde57b3a6185] [Current]

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Dataseries X:

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Histogram

Boxplots

1418	210907	396	79	30	112285	144	145
869	120982	297	58	28	84786	103	101
1530	176508	559	60	38	83123	98	98
2172	179321	967	108	30	101193	135	132
901	123185	270	49	22	38361	61	60
463	52746	143	0	26	68504	39	38
3201	385534	1562	121	25	119182	150	144
371	33170	109	1	18	22807	5	5
1192	101645	371	20	11	17140	28	28
1583	149061	656	43	26	116174	84	84
1439	165446	511	69	25	57635	80	79
1764	237213	655	78	38	66198	130	127
1495	173326	465	86	44	71701	82	78
1373	133131	525	44	30	57793	60	60
2187	258873	885	104	40	80444	131	131
1491	180083	497	63	34	53855	84	84
4041	324799	1436	158	47	97668	140	133
1706	230964	612	102	30	133824	151	150
2152	236785	865	77	31	101481	91	91
1036	135473	385	82	23	99645	138	132
1882	202925	567	115	36	114789	150	136
1929	215147	639	101	36	99052	124	124
2242	344297	963	80	30	67654	119	118
1220	153935	398	50	25	65553	73	70
1289	132943	410	83	39	97500	110	107
2515	174724	966	123	34	69112	123	119
2147	174415	801	73	31	82753	90	89
2352	225548	892	81	31	85323	116	112
1638	223632	513	105	33	72654	113	108
1222	124817	469	47	25	30727	56	52
1812	221698	683	105	33	77873	115	112
1677	210767	643	94	35	117478	119	116
1579	170266	535	44	42	74007	129	123
1731	260561	625	114	43	90183	127	125
807	84853	264	38	30	61542	27	27
2452	294424	992	107	33	101494	175	162
829	101011	238	30	13	27570	35	32
1940	215641	818	71	32	55813	64	64
2662	325107	937	84	36	79215	96	92
186	7176	70	0	0	1423	0	0
1499	167542	507	59	28	55461	84	83
865	106408	260	33	14	31081	41	41
1793	96560	503	42	17	22996	47	47
2527	265769	927	96	32	83122	126	120
2747	269651	1269	106	30	70106	105	105
1324	149112	537	56	35	60578	80	79
2702	175824	910	57	20	39992	70	65
1383	152871	532	59	28	79892	73	70
1179	111665	345	39	28	49810	57	55
2099	116408	918	34	39	71570	40	39
4308	362301	1635	76	34	100708	68	67
918	78800	330	20	26	33032	21	21
1831	183167	557	91	39	82875	127	127
3373	277965	1178	115	39	139077	154	152
1713	150629	740	85	33	71595	116	113
1438	168809	452	76	28	72260	102	99
496	24188	218	8	4	5950	7	7
2253	329267	764	79	39	115762	148	141
744	65029	255	21	18	32551	21	21
1161	101097	454	30	14	31701	35	35
2352	218946	866	76	29	80670	112	109
2144	244052	574	101	44	143558	137	133
4691	341570	1276	94	21	117105	135	123
1112	103597	379	27	16	23789	26	26
2694	233328	825	92	28	120733	230	230
1973	256462	798	123	35	105195	181	166
1769	206161	663	75	28	73107	71	68
3148	311473	1069	128	38	132068	147	147
2474	235800	921	105	23	149193	190	179
2084	177939	858	55	36	46821	64	61
1954	207176	711	56	32	87011	105	101
1226	196553	503	41	29	95260	107	108
1389	174184	382	72	25	55183	94	90
1496	143246	464	67	27	106671	116	114
2269	187559	717	75	36	73511	106	103
1833	187681	690	114	28	92945	143	142
1268	119016	462	118	23	78664	81	79
1943	182192	657	77	40	70054	89	88
893	73566	385	22	23	22618	26	25
1762	194979	577	66	40	74011	84	83
1403	167488	619	69	28	83737	113	113
1425	143756	479	105	34	69094	120	118
1857	275541	817	116	33	93133	110	110
1840	243199	752	88	28	95536	134	129
1502	182999	430	73	34	225920	54	51
1441	135649	451	99	30	62133	96	93
1420	152299	537	62	33	61370	78	76
1416	120221	519	53	22	43836	51	49
2970	346485	1000	118	38	106117	121	118
1317	145790	637	30	26	38692	38	38
1644	193339	465	100	35	84651	145	141
870	80953	437	49	8	56622	59	58
1654	122774	711	24	24	15986	27	27
1054	130585	299	67	29	95364	91	91
937	112611	248	46	20	26706	48	48
3004	286468	1162	57	29	89691	68	63
2008	241066	714	75	45	67267	58	56
2547	148446	905	135	37	126846	150	144
1885	204713	649	68	33	41140	74	73
1626	182079	512	124	33	102860	181	168
1468	140344	472	33	25	51715	65	64
2445	220516	905	98	32	55801	97	97
1964	243060	786	58	29	111813	121	117
1381	162765	489	68	28	120293	99	100
1369	182613	479	81	28	138599	152	149
1659	232138	617	131	31	161647	188	187
2888	265318	925	110	52	115929	138	127
1290	85574	351	37	21	24266	40	37
2845	310839	1144	130	24	162901	254	245
1982	225060	669	93	41	109825	87	87
1904	232317	707	118	33	129838	178	177
1391	144966	458	39	32	37510	51	49
602	43287	214	13	19	43750	49	49
1743	155754	599	74	20	40652	73	73
1559	164709	572	81	31	87771	176	177
2014	201940	897	109	31	85872	94	94
2143	235454	819	151	32	89275	120	117
2146	220801	720	51	18	44418	66	60
874	99466	273	28	23	192565	56	55
1590	92661	508	40	17	35232	39	39
1590	133328	506	56	20	40909	66	64
1210	61361	451	27	12	13294	27	26
2072	125930	699	37	17	32387	65	64
1281	100750	407	83	30	140867	58	58
1401	224549	465	54	31	120662	98	95
834	82316	245	27	10	21233	25	25
1105	102010	370	28	13	44332	26	26
1272	101523	316	59	22	61056	77	76
1944	243511	603	133	42	101338	130	129
391	22938	154	12	1	1168	11	11
761	41566	229	0	9	13497	2	2
1605	152474	577	106	32	65567	101	101
530	61857	192	23	11	25162	31	28
1988	99923	617	44	25	32334	36	36
1386	132487	411	71	36	40735	120	89
2395	317394	975	116	31	91413	195	193
387	21054	146	4	0	855	4	4
1742	209641	705	62	24	97068	89	84
620	22648	184	12	13	44339	24	23
449	31414	200	18	8	14116	39	39
800	46698	274	14	13	10288	14	14
1684	131698	502	60	19	65622	78	78
1050	91735	382	7	18	16563	15	14
2699	244749	964	98	33	76643	106	101
1606	184510	537	64	40	110681	83	82
1502	79863	438	29	22	29011	24	24
1204	128423	369	32	38	92696	37	36
1138	97839	417	25	24	94785	77	75
568	38214	276	16	8	8773	16	16
1459	151101	514	48	35	83209	56	55
2158	272458	822	100	43	93815	132	131
1111	172494	389	46	43	86687	144	131
1421	108043	466	45	14	34553	40	39
2833	328107	1255	129	41	105547	153	144
1955	250579	694	130	38	103487	143	139
2922	351067	1024	136	45	213688	220	211
1002	158015	400	59	31	71220	79	78
1060	98866	397	25	13	23517	50	50
956	85439	350	32	28	56926	39	39
2186	229242	719	63	31	91721	95	90
3604	351619	1277	95	40	115168	169	166
1035	84207	356	14	30	111194	12	12
1417	120445	457	36	16	51009	63	57
3261	324598	1402	113	37	135777	134	133
1587	131069	600	47	30	51513	69	69
1424	204271	480	92	35	74163	119	119
1701	165543	595	70	32	51633	119	119
1249	141722	436	19	27	75345	75	65
946	116048	230	50	20	33416	63	61
1926	250047	651	41	18	83305	55	49
3352	299775	1367	91	31	98952	103	101
1641	195838	564	111	31	102372	197	196
2035	173260	716	41	21	37238	16	15
2312	254488	747	120	39	103772	140	136
1369	104389	467	135	41	123969	89	89
1577	136084	671	27	13	27142	40	40
2201	199476	861	87	32	135400	125	123
961	92499	319	25	18	21399	21	21
1900	224330	612	131	39	130115	167	163
1254	135781	433	45	14	24874	32	29
1335	74408	434	29	7	34988	36	35
1597	81240	503	58	17	45549	13	13
207	14688	85	4	0	6023	5	5
1645	181633	564	47	30	64466	96	96
2429	271856	824	109	37	54990	151	151
151	7199	74	7	0	1644	6	6
474	46660	259	12	5	6179	13	13
141	17547	69	0	1	3926	3	3
1639	133368	535	37	16	32755	57	56
872	95227	239	37	32	34777	23	23
1318	152601	438	46	24	73224	61	57
1018	98146	459	15	17	27114	21	14
1383	79619	426	42	11	20760	43	43
1314	59194	288	7	24	37636	20	20
1335	139942	498	54	22	65461	82	72
1403	118612	454	54	12	30080	90	87
910	72880	376	14	19	24094	25	21
616	65475	225	16	13	69008	60	56
1407	99643	555	33	17	54968	61	59
771	71965	252	32	15	46090	85	82
766	77272	208	21	16	27507	43	43
473	49289	130	15	24	10672	25	25
1376	135131	481	38	15	34029	41	38
1232	108446	389	22	17	46300	26	25
1521	89746	565	28	18	24760	38	38
572	44296	173	10	20	18779	12	12
1059	77648	278	31	16	21280	29	29
1544	181528	609	32	16	40662	49	47
1230	134019	422	32	18	28987	46	45
1206	124064	445	43	22	22827	41	40
1205	92630	387	27	8	18513	31	30
1255	121848	339	37	17	30594	41	41
613	52915	181	20	18	24006	26	25
721	81872	245	32	16	27913	23	23
1109	58981	384	0	23	42744	14	14
740	53515	212	5	22	12934	16	16
1126	60812	399	26	13	22574	25	26
728	56375	229	10	13	41385	21	21
689	65490	224	27	16	18653	32	27
592	80949	203	11	16	18472	9	9
995	76302	333	29	20	30976	35	33
1613	104011	384	25	22	63339	42	42
2048	98104	636	55	17	25568	68	68
705	67989	185	23	18	33747	32	32
301	30989	93	5	17	4154	6	6
1803	135458	581	43	12	19474	68	67
799	73504	248	23	7	35130	33	33
861	63123	304	34	17	39067	84	77
1186	61254	344	36	14	13310	46	46
1451	74914	407	35	23	65892	30	30
628	31774	170	0	17	4143	0	0
1161	81437	312	37	14	28579	36	36
1463	87186	507	28	15	51776	47	46
742	50090	224	16	17	21152	20	18
979	65745	340	26	21	38084	50	48
675	56653	168	38	18	27717	30	29
1241	158399	443	23	18	32928	30	28
676	46455	204	22	17	11342	34	34
1049	73624	367	30	17	19499	33	33
620	38395	210	16	16	16380	34	34
1081	91899	335	18	15	36874	37	33
1688	139526	364	28	21	48259	83	80
736	52164	178	32	16	16734	32	32
617	51567	206	21	14	28207	30	30
812	70551	279	23	15	30143	43	41
1051	84856	387	29	17	41369	41	41
1656	102538	490	50	15	45833	51	51
705	86678	238	12	15	29156	19	18
945	85709	343	21	10	35944	37	34
554	34662	232	18	6	36278	33	31
1597	150580	530	27	22	45588	41	39
982	99611	291	41	21	45097	54	54
222	19349	67	13	1	3895	14	14
1212	99373	397	12	18	28394	25	24
1143	86230	467	21	17	18632	25	24
435	30837	178	8	4	2325	8	8
532	31706	175	26	10	25139	26	26
882	89806	299	27	16	27975	20	19
608	62088	154	13	16	14483	11	11
459	40151	106	16	9	13127	14	14
578	27634	189	2	16	5839	3	1
826	76990	194	42	17	24069	40	39
509	37460	135	5	7	3738	5	5
717	54157	201	37	15	18625	38	37
637	49862	207	17	14	36341	32	32
857	84337	280	38	14	24548	41	38
830	64175	260	37	18	21792	46	47
652	59382	227	29	12	26263	47	47
707	119308	239	32	16	23686	37	37
954	76702	333	35	21	49303	51	51
1461	103425	428	17	19	25659	49	45
672	70344	230	20	16	28904	21	21
778	43410	292	7	1	2781	1	1
1141	104838	350	46	16	29236	44	42
680	62215	186	24	10	19546	26	26
1090	69304	326	40	19	22818	21	21
616	53117	155	3	12	32689	4	4
285	19764	75	10	2	5752	10	10
1145	86680	361	37	14	22197	43	43
733	84105	261	17	17	20055	34	34
888	77945	299	28	19	25272	32	31
849	89113	300	19	14	82206	20	19
1182	91005	450	29	11	32073	34	34
528	40248	183	8	4	5444	6	6
642	64187	238	10	16	20154	12	11
947	50857	165	15	20	36944	24	24
819	56613	234	15	12	8019	16	16
757	62792	176	28	15	30884	72	72
894	72535	329	17	16	19540	27	21

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 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 & 6 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155245&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]6 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=155245&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155245&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Goodness of Fit
Correlation	0.8513
R-squared	0.7247
RMSE	5.5493

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.8513 \tabularnewline
R-squared & 0.7247 \tabularnewline
RMSE & 5.5493 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155245&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.8513[/C][/ROW]
[ROW][C]R-squared[/C][C]0.7247[/C][/ROW]
[ROW][C]RMSE[/C][C]5.5493[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155245&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155245&T=1

As an alternative you can also use a QR Code:

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

Goodness of Fit
Correlation	0.8513
R-squared	0.7247
RMSE	5.5493

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	30	34.3625	-4.3625
2	28	28.8857142857143	-0.885714285714286
3	38	28.8857142857143	9.11428571428571
4	30	34.3625	-4.3625
5	22	19.9310344827586	2.06896551724138
6	26	27.68	-1.68
7	25	34.3625	-9.3625
8	18	15.8811881188119	2.11881188118812
9	11	15.8811881188119	-4.88118811881188
10	26	27.68	-1.68
11	25	28.8857142857143	-3.88571428571429
12	38	34.3625	3.6375
13	44	34.3625	9.6375
14	30	27.68	2.32
15	40	34.3625	5.6375
16	34	28.8857142857143	5.11428571428571
17	47	34.3625	12.6375
18	30	34.3625	-4.3625
19	31	34.3625	-3.3625
20	23	34.3625	-11.3625
21	36	34.3625	1.6375
22	36	34.3625	1.6375
23	30	34.3625	-4.3625
24	25	27.68	-2.68
25	39	34.3625	4.6375
26	34	34.3625	-0.362499999999997
27	31	28.8857142857143	2.11428571428571
28	31	34.3625	-3.3625
29	33	34.3625	-1.3625
30	25	19.9310344827586	5.06896551724138
31	33	34.3625	-1.3625
32	35	34.3625	0.637500000000003
33	42	27.68	14.32
34	43	34.3625	8.6375
35	30	27.68	2.32
36	33	34.3625	-1.3625
37	13	15.8811881188119	-2.88118811881188
38	32	28.8857142857143	3.11428571428571
39	36	34.3625	1.6375
40	0	5.26315789473684	-5.26315789473684
41	28	28.8857142857143	-0.885714285714286
42	14	15.8811881188119	-1.88118811881188
43	17	15.8811881188119	1.11881188118812
44	32	34.3625	-2.3625
45	30	34.3625	-4.3625
46	35	28.8857142857143	6.11428571428571
47	20	28.8857142857143	-8.88571428571429
48	28	28.8857142857143	-0.885714285714286
49	28	19.9310344827586	8.06896551724138
50	39	27.68	11.32
51	34	34.3625	-0.362499999999997
52	26	15.8811881188119	10.1188118811881
53	39	34.3625	4.6375
54	39	34.3625	4.6375
55	33	34.3625	-1.3625
56	28	34.3625	-6.3625
57	4	5.26315789473684	-1.26315789473684
58	39	34.3625	4.6375
59	18	15.8811881188119	2.11881188118812
60	14	15.8811881188119	-1.88118811881188
61	29	34.3625	-5.3625
62	44	34.3625	9.6375
63	21	34.3625	-13.3625
64	16	15.8811881188119	0.118811881188119
65	28	34.3625	-6.3625
66	35	34.3625	0.637500000000003
67	28	34.3625	-6.3625
68	38	34.3625	3.6375
69	23	34.3625	-11.3625
70	36	28.8857142857143	7.11428571428571
71	32	28.8857142857143	3.11428571428571
72	29	27.68	1.32
73	25	28.8857142857143	-3.88571428571429
74	27	28.8857142857143	-1.88571428571429
75	36	34.3625	1.6375
76	28	34.3625	-6.3625
77	23	34.3625	-11.3625
78	40	34.3625	5.6375
79	23	15.8811881188119	7.11881188118812
80	40	28.8857142857143	11.1142857142857
81	28	28.8857142857143	-0.885714285714286
82	34	34.3625	-0.362499999999997
83	33	34.3625	-1.3625
84	28	34.3625	-6.3625
85	34	28.8857142857143	5.11428571428571
86	30	34.3625	-4.3625
87	33	28.8857142857143	4.11428571428571
88	22	19.9310344827586	2.06896551724138
89	38	34.3625	3.6375
90	26	19.9310344827586	6.06896551724138
91	35	34.3625	0.637500000000003
92	8	15.8811881188119	-7.88118811881188
93	24	19.9310344827586	4.06896551724138
94	29	28.8857142857143	0.114285714285714
95	20	19.9310344827586	0.0689655172413808
96	29	28.8857142857143	0.114285714285714
97	45	34.3625	10.6375
98	37	34.3625	2.6375
99	33	28.8857142857143	4.11428571428571
100	33	34.3625	-1.3625
101	25	19.9310344827586	5.06896551724138
102	32	34.3625	-2.3625
103	29	28.8857142857143	0.114285714285714
104	28	28.8857142857143	-0.885714285714286
105	28	34.3625	-6.3625
106	31	34.3625	-3.3625
107	52	34.3625	17.6375
108	21	15.8811881188119	5.11881188118812
109	24	34.3625	-10.3625
110	41	34.3625	6.6375
111	33	34.3625	-1.3625
112	32	19.9310344827586	12.0689655172414
113	19	15.8811881188119	3.11881188118812
114	20	28.8857142857143	-8.88571428571429
115	31	34.3625	-3.3625
116	31	34.3625	-3.3625
117	32	34.3625	-2.3625
118	18	19.9310344827586	-1.93103448275862
119	23	27.68	-4.68
120	17	15.8811881188119	1.11881188118812
121	20	28.8857142857143	-8.88571428571429
122	12	15.8811881188119	-3.88118811881188
123	17	19.9310344827586	-2.93103448275862
124	30	34.3625	-4.3625
125	31	27.68	3.32
126	10	15.8811881188119	-5.88118811881188
127	13	15.8811881188119	-2.88118811881188
128	22	28.8857142857143	-6.88571428571429
129	42	34.3625	7.6375
130	1	5.26315789473684	-4.26315789473684
131	9	15.8811881188119	-6.88118811881188
132	32	34.3625	-2.3625
133	11	15.8811881188119	-4.88118811881188
134	25	15.8811881188119	9.11881188118812
135	36	28.8857142857143	7.11428571428571
136	31	34.3625	-3.3625
137	0	5.26315789473684	-5.26315789473684
138	24	28.8857142857143	-4.88571428571429
139	13	15.8811881188119	-2.88118811881188
140	8	15.8811881188119	-7.88118811881188
141	13	15.8811881188119	-2.88118811881188
142	19	28.8857142857143	-9.88571428571429
143	18	15.8811881188119	2.11881188118812
144	33	34.3625	-1.3625
145	40	28.8857142857143	11.1142857142857
146	22	15.8811881188119	6.11881188118812
147	38	27.68	10.32
148	24	27.68	-3.68
149	8	5.26315789473684	2.73684210526316
150	35	27.68	7.32
151	43	34.3625	8.6375
152	43	27.68	15.32
153	14	15.8811881188119	-1.88118811881188
154	41	34.3625	6.6375
155	38	34.3625	3.6375
156	45	34.3625	10.6375
157	31	28.8857142857143	2.11428571428571
158	13	15.8811881188119	-2.88118811881188
159	28	27.68	0.32
160	31	28.8857142857143	2.11428571428571
161	40	34.3625	5.6375
162	30	27.68	2.32
163	16	19.9310344827586	-3.93103448275862
164	37	34.3625	2.6375
165	30	19.9310344827586	10.0689655172414
166	35	34.3625	0.637500000000003
167	32	28.8857142857143	3.11428571428571
168	27	27.68	-0.68
169	20	19.9310344827586	0.0689655172413808
170	18	27.68	-9.68
171	31	34.3625	-3.3625
172	31	34.3625	-3.3625
173	21	19.9310344827586	1.06896551724138
174	39	34.3625	4.6375
175	41	34.3625	6.6375
176	13	19.9310344827586	-6.93103448275862
177	32	34.3625	-2.3625
178	18	15.8811881188119	2.11881188118812
179	39	34.3625	4.6375
180	14	19.9310344827586	-5.93103448275862
181	7	15.8811881188119	-8.88118811881188
182	17	28.8857142857143	-11.8857142857143
183	0	5.26315789473684	-5.26315789473684
184	30	27.68	2.32
185	37	34.3625	2.6375
186	0	5.26315789473684	-5.26315789473684
187	5	5.26315789473684	-0.263157894736842
188	1	5.26315789473684	-4.26315789473684
189	16	19.9310344827586	-3.93103448275862
190	32	15.8811881188119	16.1188118811881
191	24	27.68	-3.68
192	17	15.8811881188119	1.11881188118812
193	11	15.8811881188119	-4.88118811881188
194	24	15.8811881188119	8.11881188118812
195	22	27.68	-5.68
196	12	19.9310344827586	-7.93103448275862
197	19	15.8811881188119	3.11881188118812
198	13	27.68	-14.68
199	17	15.8811881188119	1.11881188118812
200	15	15.8811881188119	-0.881188118811881
201	16	15.8811881188119	0.118811881188119
202	24	15.8811881188119	8.11881188118812
203	15	19.9310344827586	-4.93103448275862
204	17	15.8811881188119	1.11881188118812
205	18	15.8811881188119	2.11881188118812
206	20	15.8811881188119	4.11881188118812
207	16	15.8811881188119	0.118811881188119
208	16	19.9310344827586	-3.93103448275862
209	18	19.9310344827586	-1.93103448275862
210	22	19.9310344827586	2.06896551724138
211	8	15.8811881188119	-7.88118811881188
212	17	19.9310344827586	-2.93103448275862
213	18	15.8811881188119	2.11881188118812
214	16	15.8811881188119	0.118811881188119
215	23	15.8811881188119	7.11881188118812
216	22	15.8811881188119	6.11881188118812
217	13	15.8811881188119	-2.88118811881188
218	13	15.8811881188119	-2.88118811881188
219	16	15.8811881188119	0.118811881188119
220	16	15.8811881188119	0.118811881188119
221	20	15.8811881188119	4.11881188118812
222	22	27.68	-5.68
223	17	28.8857142857143	-11.8857142857143
224	18	15.8811881188119	2.11881188118812
225	17	5.26315789473684	11.7368421052632
226	12	19.9310344827586	-7.93103448275862
227	7	15.8811881188119	-8.88118811881188
228	17	15.8811881188119	1.11881188118812
229	14	15.8811881188119	-1.88118811881188
230	23	27.68	-4.68
231	17	5.26315789473684	11.7368421052632
232	14	15.8811881188119	-1.88118811881188
233	15	15.8811881188119	-0.881188118811881
234	17	15.8811881188119	1.11881188118812
235	21	15.8811881188119	5.11881188118812
236	18	15.8811881188119	2.11881188118812
237	18	19.9310344827586	-1.93103448275862
238	17	15.8811881188119	1.11881188118812
239	17	15.8811881188119	1.11881188118812
240	16	15.8811881188119	0.118811881188119
241	15	15.8811881188119	-0.881188118811881
242	21	19.9310344827586	1.06896551724138
243	16	15.8811881188119	0.118811881188119
244	14	15.8811881188119	-1.88118811881188
245	15	15.8811881188119	-0.881188118811881
246	17	15.8811881188119	1.11881188118812
247	15	15.8811881188119	-0.881188118811881
248	15	15.8811881188119	-0.881188118811881
249	10	15.8811881188119	-5.88118811881188
250	6	15.8811881188119	-9.88118811881188
251	22	19.9310344827586	2.06896551724138
252	21	15.8811881188119	5.11881188118812
253	1	5.26315789473684	-4.26315789473684
254	18	15.8811881188119	2.11881188118812
255	17	15.8811881188119	1.11881188118812
256	4	5.26315789473684	-1.26315789473684
257	10	15.8811881188119	-5.88118811881188
258	16	15.8811881188119	0.118811881188119
259	16	15.8811881188119	0.118811881188119
260	9	15.8811881188119	-6.88118811881188
261	16	5.26315789473684	10.7368421052632
262	17	15.8811881188119	1.11881188118812
263	7	5.26315789473684	1.73684210526316
264	15	15.8811881188119	-0.881188118811881
265	14	15.8811881188119	-1.88118811881188
266	14	15.8811881188119	-1.88118811881188
267	18	15.8811881188119	2.11881188118812
268	12	15.8811881188119	-3.88118811881188
269	16	19.9310344827586	-3.93103448275862
270	21	15.8811881188119	5.11881188118812
271	19	15.8811881188119	3.11881188118812
272	16	15.8811881188119	0.118811881188119
273	1	5.26315789473684	-4.26315789473684
274	16	15.8811881188119	0.118811881188119
275	10	15.8811881188119	-5.88118811881188
276	19	15.8811881188119	3.11881188118812
277	12	15.8811881188119	-3.88118811881188
278	2	5.26315789473684	-3.26315789473684
279	14	15.8811881188119	-1.88118811881188
280	17	15.8811881188119	1.11881188118812
281	19	15.8811881188119	3.11881188118812
282	14	27.68	-13.68
283	11	15.8811881188119	-4.88118811881188
284	4	5.26315789473684	-1.26315789473684
285	16	15.8811881188119	0.118811881188119
286	20	15.8811881188119	4.11881188118812
287	12	5.26315789473684	6.73684210526316
288	15	15.8811881188119	-0.881188118811881
289	16	15.8811881188119	0.118811881188119

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 30 & 34.3625 & -4.3625 \tabularnewline
2 & 28 & 28.8857142857143 & -0.885714285714286 \tabularnewline
3 & 38 & 28.8857142857143 & 9.11428571428571 \tabularnewline
4 & 30 & 34.3625 & -4.3625 \tabularnewline
5 & 22 & 19.9310344827586 & 2.06896551724138 \tabularnewline
6 & 26 & 27.68 & -1.68 \tabularnewline
7 & 25 & 34.3625 & -9.3625 \tabularnewline
8 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
9 & 11 & 15.8811881188119 & -4.88118811881188 \tabularnewline
10 & 26 & 27.68 & -1.68 \tabularnewline
11 & 25 & 28.8857142857143 & -3.88571428571429 \tabularnewline
12 & 38 & 34.3625 & 3.6375 \tabularnewline
13 & 44 & 34.3625 & 9.6375 \tabularnewline
14 & 30 & 27.68 & 2.32 \tabularnewline
15 & 40 & 34.3625 & 5.6375 \tabularnewline
16 & 34 & 28.8857142857143 & 5.11428571428571 \tabularnewline
17 & 47 & 34.3625 & 12.6375 \tabularnewline
18 & 30 & 34.3625 & -4.3625 \tabularnewline
19 & 31 & 34.3625 & -3.3625 \tabularnewline
20 & 23 & 34.3625 & -11.3625 \tabularnewline
21 & 36 & 34.3625 & 1.6375 \tabularnewline
22 & 36 & 34.3625 & 1.6375 \tabularnewline
23 & 30 & 34.3625 & -4.3625 \tabularnewline
24 & 25 & 27.68 & -2.68 \tabularnewline
25 & 39 & 34.3625 & 4.6375 \tabularnewline
26 & 34 & 34.3625 & -0.362499999999997 \tabularnewline
27 & 31 & 28.8857142857143 & 2.11428571428571 \tabularnewline
28 & 31 & 34.3625 & -3.3625 \tabularnewline
29 & 33 & 34.3625 & -1.3625 \tabularnewline
30 & 25 & 19.9310344827586 & 5.06896551724138 \tabularnewline
31 & 33 & 34.3625 & -1.3625 \tabularnewline
32 & 35 & 34.3625 & 0.637500000000003 \tabularnewline
33 & 42 & 27.68 & 14.32 \tabularnewline
34 & 43 & 34.3625 & 8.6375 \tabularnewline
35 & 30 & 27.68 & 2.32 \tabularnewline
36 & 33 & 34.3625 & -1.3625 \tabularnewline
37 & 13 & 15.8811881188119 & -2.88118811881188 \tabularnewline
38 & 32 & 28.8857142857143 & 3.11428571428571 \tabularnewline
39 & 36 & 34.3625 & 1.6375 \tabularnewline
40 & 0 & 5.26315789473684 & -5.26315789473684 \tabularnewline
41 & 28 & 28.8857142857143 & -0.885714285714286 \tabularnewline
42 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
43 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
44 & 32 & 34.3625 & -2.3625 \tabularnewline
45 & 30 & 34.3625 & -4.3625 \tabularnewline
46 & 35 & 28.8857142857143 & 6.11428571428571 \tabularnewline
47 & 20 & 28.8857142857143 & -8.88571428571429 \tabularnewline
48 & 28 & 28.8857142857143 & -0.885714285714286 \tabularnewline
49 & 28 & 19.9310344827586 & 8.06896551724138 \tabularnewline
50 & 39 & 27.68 & 11.32 \tabularnewline
51 & 34 & 34.3625 & -0.362499999999997 \tabularnewline
52 & 26 & 15.8811881188119 & 10.1188118811881 \tabularnewline
53 & 39 & 34.3625 & 4.6375 \tabularnewline
54 & 39 & 34.3625 & 4.6375 \tabularnewline
55 & 33 & 34.3625 & -1.3625 \tabularnewline
56 & 28 & 34.3625 & -6.3625 \tabularnewline
57 & 4 & 5.26315789473684 & -1.26315789473684 \tabularnewline
58 & 39 & 34.3625 & 4.6375 \tabularnewline
59 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
60 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
61 & 29 & 34.3625 & -5.3625 \tabularnewline
62 & 44 & 34.3625 & 9.6375 \tabularnewline
63 & 21 & 34.3625 & -13.3625 \tabularnewline
64 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
65 & 28 & 34.3625 & -6.3625 \tabularnewline
66 & 35 & 34.3625 & 0.637500000000003 \tabularnewline
67 & 28 & 34.3625 & -6.3625 \tabularnewline
68 & 38 & 34.3625 & 3.6375 \tabularnewline
69 & 23 & 34.3625 & -11.3625 \tabularnewline
70 & 36 & 28.8857142857143 & 7.11428571428571 \tabularnewline
71 & 32 & 28.8857142857143 & 3.11428571428571 \tabularnewline
72 & 29 & 27.68 & 1.32 \tabularnewline
73 & 25 & 28.8857142857143 & -3.88571428571429 \tabularnewline
74 & 27 & 28.8857142857143 & -1.88571428571429 \tabularnewline
75 & 36 & 34.3625 & 1.6375 \tabularnewline
76 & 28 & 34.3625 & -6.3625 \tabularnewline
77 & 23 & 34.3625 & -11.3625 \tabularnewline
78 & 40 & 34.3625 & 5.6375 \tabularnewline
79 & 23 & 15.8811881188119 & 7.11881188118812 \tabularnewline
80 & 40 & 28.8857142857143 & 11.1142857142857 \tabularnewline
81 & 28 & 28.8857142857143 & -0.885714285714286 \tabularnewline
82 & 34 & 34.3625 & -0.362499999999997 \tabularnewline
83 & 33 & 34.3625 & -1.3625 \tabularnewline
84 & 28 & 34.3625 & -6.3625 \tabularnewline
85 & 34 & 28.8857142857143 & 5.11428571428571 \tabularnewline
86 & 30 & 34.3625 & -4.3625 \tabularnewline
87 & 33 & 28.8857142857143 & 4.11428571428571 \tabularnewline
88 & 22 & 19.9310344827586 & 2.06896551724138 \tabularnewline
89 & 38 & 34.3625 & 3.6375 \tabularnewline
90 & 26 & 19.9310344827586 & 6.06896551724138 \tabularnewline
91 & 35 & 34.3625 & 0.637500000000003 \tabularnewline
92 & 8 & 15.8811881188119 & -7.88118811881188 \tabularnewline
93 & 24 & 19.9310344827586 & 4.06896551724138 \tabularnewline
94 & 29 & 28.8857142857143 & 0.114285714285714 \tabularnewline
95 & 20 & 19.9310344827586 & 0.0689655172413808 \tabularnewline
96 & 29 & 28.8857142857143 & 0.114285714285714 \tabularnewline
97 & 45 & 34.3625 & 10.6375 \tabularnewline
98 & 37 & 34.3625 & 2.6375 \tabularnewline
99 & 33 & 28.8857142857143 & 4.11428571428571 \tabularnewline
100 & 33 & 34.3625 & -1.3625 \tabularnewline
101 & 25 & 19.9310344827586 & 5.06896551724138 \tabularnewline
102 & 32 & 34.3625 & -2.3625 \tabularnewline
103 & 29 & 28.8857142857143 & 0.114285714285714 \tabularnewline
104 & 28 & 28.8857142857143 & -0.885714285714286 \tabularnewline
105 & 28 & 34.3625 & -6.3625 \tabularnewline
106 & 31 & 34.3625 & -3.3625 \tabularnewline
107 & 52 & 34.3625 & 17.6375 \tabularnewline
108 & 21 & 15.8811881188119 & 5.11881188118812 \tabularnewline
109 & 24 & 34.3625 & -10.3625 \tabularnewline
110 & 41 & 34.3625 & 6.6375 \tabularnewline
111 & 33 & 34.3625 & -1.3625 \tabularnewline
112 & 32 & 19.9310344827586 & 12.0689655172414 \tabularnewline
113 & 19 & 15.8811881188119 & 3.11881188118812 \tabularnewline
114 & 20 & 28.8857142857143 & -8.88571428571429 \tabularnewline
115 & 31 & 34.3625 & -3.3625 \tabularnewline
116 & 31 & 34.3625 & -3.3625 \tabularnewline
117 & 32 & 34.3625 & -2.3625 \tabularnewline
118 & 18 & 19.9310344827586 & -1.93103448275862 \tabularnewline
119 & 23 & 27.68 & -4.68 \tabularnewline
120 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
121 & 20 & 28.8857142857143 & -8.88571428571429 \tabularnewline
122 & 12 & 15.8811881188119 & -3.88118811881188 \tabularnewline
123 & 17 & 19.9310344827586 & -2.93103448275862 \tabularnewline
124 & 30 & 34.3625 & -4.3625 \tabularnewline
125 & 31 & 27.68 & 3.32 \tabularnewline
126 & 10 & 15.8811881188119 & -5.88118811881188 \tabularnewline
127 & 13 & 15.8811881188119 & -2.88118811881188 \tabularnewline
128 & 22 & 28.8857142857143 & -6.88571428571429 \tabularnewline
129 & 42 & 34.3625 & 7.6375 \tabularnewline
130 & 1 & 5.26315789473684 & -4.26315789473684 \tabularnewline
131 & 9 & 15.8811881188119 & -6.88118811881188 \tabularnewline
132 & 32 & 34.3625 & -2.3625 \tabularnewline
133 & 11 & 15.8811881188119 & -4.88118811881188 \tabularnewline
134 & 25 & 15.8811881188119 & 9.11881188118812 \tabularnewline
135 & 36 & 28.8857142857143 & 7.11428571428571 \tabularnewline
136 & 31 & 34.3625 & -3.3625 \tabularnewline
137 & 0 & 5.26315789473684 & -5.26315789473684 \tabularnewline
138 & 24 & 28.8857142857143 & -4.88571428571429 \tabularnewline
139 & 13 & 15.8811881188119 & -2.88118811881188 \tabularnewline
140 & 8 & 15.8811881188119 & -7.88118811881188 \tabularnewline
141 & 13 & 15.8811881188119 & -2.88118811881188 \tabularnewline
142 & 19 & 28.8857142857143 & -9.88571428571429 \tabularnewline
143 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
144 & 33 & 34.3625 & -1.3625 \tabularnewline
145 & 40 & 28.8857142857143 & 11.1142857142857 \tabularnewline
146 & 22 & 15.8811881188119 & 6.11881188118812 \tabularnewline
147 & 38 & 27.68 & 10.32 \tabularnewline
148 & 24 & 27.68 & -3.68 \tabularnewline
149 & 8 & 5.26315789473684 & 2.73684210526316 \tabularnewline
150 & 35 & 27.68 & 7.32 \tabularnewline
151 & 43 & 34.3625 & 8.6375 \tabularnewline
152 & 43 & 27.68 & 15.32 \tabularnewline
153 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
154 & 41 & 34.3625 & 6.6375 \tabularnewline
155 & 38 & 34.3625 & 3.6375 \tabularnewline
156 & 45 & 34.3625 & 10.6375 \tabularnewline
157 & 31 & 28.8857142857143 & 2.11428571428571 \tabularnewline
158 & 13 & 15.8811881188119 & -2.88118811881188 \tabularnewline
159 & 28 & 27.68 & 0.32 \tabularnewline
160 & 31 & 28.8857142857143 & 2.11428571428571 \tabularnewline
161 & 40 & 34.3625 & 5.6375 \tabularnewline
162 & 30 & 27.68 & 2.32 \tabularnewline
163 & 16 & 19.9310344827586 & -3.93103448275862 \tabularnewline
164 & 37 & 34.3625 & 2.6375 \tabularnewline
165 & 30 & 19.9310344827586 & 10.0689655172414 \tabularnewline
166 & 35 & 34.3625 & 0.637500000000003 \tabularnewline
167 & 32 & 28.8857142857143 & 3.11428571428571 \tabularnewline
168 & 27 & 27.68 & -0.68 \tabularnewline
169 & 20 & 19.9310344827586 & 0.0689655172413808 \tabularnewline
170 & 18 & 27.68 & -9.68 \tabularnewline
171 & 31 & 34.3625 & -3.3625 \tabularnewline
172 & 31 & 34.3625 & -3.3625 \tabularnewline
173 & 21 & 19.9310344827586 & 1.06896551724138 \tabularnewline
174 & 39 & 34.3625 & 4.6375 \tabularnewline
175 & 41 & 34.3625 & 6.6375 \tabularnewline
176 & 13 & 19.9310344827586 & -6.93103448275862 \tabularnewline
177 & 32 & 34.3625 & -2.3625 \tabularnewline
178 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
179 & 39 & 34.3625 & 4.6375 \tabularnewline
180 & 14 & 19.9310344827586 & -5.93103448275862 \tabularnewline
181 & 7 & 15.8811881188119 & -8.88118811881188 \tabularnewline
182 & 17 & 28.8857142857143 & -11.8857142857143 \tabularnewline
183 & 0 & 5.26315789473684 & -5.26315789473684 \tabularnewline
184 & 30 & 27.68 & 2.32 \tabularnewline
185 & 37 & 34.3625 & 2.6375 \tabularnewline
186 & 0 & 5.26315789473684 & -5.26315789473684 \tabularnewline
187 & 5 & 5.26315789473684 & -0.263157894736842 \tabularnewline
188 & 1 & 5.26315789473684 & -4.26315789473684 \tabularnewline
189 & 16 & 19.9310344827586 & -3.93103448275862 \tabularnewline
190 & 32 & 15.8811881188119 & 16.1188118811881 \tabularnewline
191 & 24 & 27.68 & -3.68 \tabularnewline
192 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
193 & 11 & 15.8811881188119 & -4.88118811881188 \tabularnewline
194 & 24 & 15.8811881188119 & 8.11881188118812 \tabularnewline
195 & 22 & 27.68 & -5.68 \tabularnewline
196 & 12 & 19.9310344827586 & -7.93103448275862 \tabularnewline
197 & 19 & 15.8811881188119 & 3.11881188118812 \tabularnewline
198 & 13 & 27.68 & -14.68 \tabularnewline
199 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
200 & 15 & 15.8811881188119 & -0.881188118811881 \tabularnewline
201 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
202 & 24 & 15.8811881188119 & 8.11881188118812 \tabularnewline
203 & 15 & 19.9310344827586 & -4.93103448275862 \tabularnewline
204 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
205 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
206 & 20 & 15.8811881188119 & 4.11881188118812 \tabularnewline
207 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
208 & 16 & 19.9310344827586 & -3.93103448275862 \tabularnewline
209 & 18 & 19.9310344827586 & -1.93103448275862 \tabularnewline
210 & 22 & 19.9310344827586 & 2.06896551724138 \tabularnewline
211 & 8 & 15.8811881188119 & -7.88118811881188 \tabularnewline
212 & 17 & 19.9310344827586 & -2.93103448275862 \tabularnewline
213 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
214 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
215 & 23 & 15.8811881188119 & 7.11881188118812 \tabularnewline
216 & 22 & 15.8811881188119 & 6.11881188118812 \tabularnewline
217 & 13 & 15.8811881188119 & -2.88118811881188 \tabularnewline
218 & 13 & 15.8811881188119 & -2.88118811881188 \tabularnewline
219 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
220 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
221 & 20 & 15.8811881188119 & 4.11881188118812 \tabularnewline
222 & 22 & 27.68 & -5.68 \tabularnewline
223 & 17 & 28.8857142857143 & -11.8857142857143 \tabularnewline
224 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
225 & 17 & 5.26315789473684 & 11.7368421052632 \tabularnewline
226 & 12 & 19.9310344827586 & -7.93103448275862 \tabularnewline
227 & 7 & 15.8811881188119 & -8.88118811881188 \tabularnewline
228 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
229 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
230 & 23 & 27.68 & -4.68 \tabularnewline
231 & 17 & 5.26315789473684 & 11.7368421052632 \tabularnewline
232 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
233 & 15 & 15.8811881188119 & -0.881188118811881 \tabularnewline
234 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
235 & 21 & 15.8811881188119 & 5.11881188118812 \tabularnewline
236 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
237 & 18 & 19.9310344827586 & -1.93103448275862 \tabularnewline
238 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
239 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
240 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
241 & 15 & 15.8811881188119 & -0.881188118811881 \tabularnewline
242 & 21 & 19.9310344827586 & 1.06896551724138 \tabularnewline
243 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
244 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
245 & 15 & 15.8811881188119 & -0.881188118811881 \tabularnewline
246 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
247 & 15 & 15.8811881188119 & -0.881188118811881 \tabularnewline
248 & 15 & 15.8811881188119 & -0.881188118811881 \tabularnewline
249 & 10 & 15.8811881188119 & -5.88118811881188 \tabularnewline
250 & 6 & 15.8811881188119 & -9.88118811881188 \tabularnewline
251 & 22 & 19.9310344827586 & 2.06896551724138 \tabularnewline
252 & 21 & 15.8811881188119 & 5.11881188118812 \tabularnewline
253 & 1 & 5.26315789473684 & -4.26315789473684 \tabularnewline
254 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
255 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
256 & 4 & 5.26315789473684 & -1.26315789473684 \tabularnewline
257 & 10 & 15.8811881188119 & -5.88118811881188 \tabularnewline
258 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
259 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
260 & 9 & 15.8811881188119 & -6.88118811881188 \tabularnewline
261 & 16 & 5.26315789473684 & 10.7368421052632 \tabularnewline
262 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
263 & 7 & 5.26315789473684 & 1.73684210526316 \tabularnewline
264 & 15 & 15.8811881188119 & -0.881188118811881 \tabularnewline
265 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
266 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
267 & 18 & 15.8811881188119 & 2.11881188118812 \tabularnewline
268 & 12 & 15.8811881188119 & -3.88118811881188 \tabularnewline
269 & 16 & 19.9310344827586 & -3.93103448275862 \tabularnewline
270 & 21 & 15.8811881188119 & 5.11881188118812 \tabularnewline
271 & 19 & 15.8811881188119 & 3.11881188118812 \tabularnewline
272 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
273 & 1 & 5.26315789473684 & -4.26315789473684 \tabularnewline
274 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
275 & 10 & 15.8811881188119 & -5.88118811881188 \tabularnewline
276 & 19 & 15.8811881188119 & 3.11881188118812 \tabularnewline
277 & 12 & 15.8811881188119 & -3.88118811881188 \tabularnewline
278 & 2 & 5.26315789473684 & -3.26315789473684 \tabularnewline
279 & 14 & 15.8811881188119 & -1.88118811881188 \tabularnewline
280 & 17 & 15.8811881188119 & 1.11881188118812 \tabularnewline
281 & 19 & 15.8811881188119 & 3.11881188118812 \tabularnewline
282 & 14 & 27.68 & -13.68 \tabularnewline
283 & 11 & 15.8811881188119 & -4.88118811881188 \tabularnewline
284 & 4 & 5.26315789473684 & -1.26315789473684 \tabularnewline
285 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
286 & 20 & 15.8811881188119 & 4.11881188118812 \tabularnewline
287 & 12 & 5.26315789473684 & 6.73684210526316 \tabularnewline
288 & 15 & 15.8811881188119 & -0.881188118811881 \tabularnewline
289 & 16 & 15.8811881188119 & 0.118811881188119 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155245&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]30[/C][C]34.3625[/C][C]-4.3625[/C][/ROW]
[ROW][C]2[/C][C]28[/C][C]28.8857142857143[/C][C]-0.885714285714286[/C][/ROW]
[ROW][C]3[/C][C]38[/C][C]28.8857142857143[/C][C]9.11428571428571[/C][/ROW]
[ROW][C]4[/C][C]30[/C][C]34.3625[/C][C]-4.3625[/C][/ROW]
[ROW][C]5[/C][C]22[/C][C]19.9310344827586[/C][C]2.06896551724138[/C][/ROW]
[ROW][C]6[/C][C]26[/C][C]27.68[/C][C]-1.68[/C][/ROW]
[ROW][C]7[/C][C]25[/C][C]34.3625[/C][C]-9.3625[/C][/ROW]
[ROW][C]8[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]9[/C][C]11[/C][C]15.8811881188119[/C][C]-4.88118811881188[/C][/ROW]
[ROW][C]10[/C][C]26[/C][C]27.68[/C][C]-1.68[/C][/ROW]
[ROW][C]11[/C][C]25[/C][C]28.8857142857143[/C][C]-3.88571428571429[/C][/ROW]
[ROW][C]12[/C][C]38[/C][C]34.3625[/C][C]3.6375[/C][/ROW]
[ROW][C]13[/C][C]44[/C][C]34.3625[/C][C]9.6375[/C][/ROW]
[ROW][C]14[/C][C]30[/C][C]27.68[/C][C]2.32[/C][/ROW]
[ROW][C]15[/C][C]40[/C][C]34.3625[/C][C]5.6375[/C][/ROW]
[ROW][C]16[/C][C]34[/C][C]28.8857142857143[/C][C]5.11428571428571[/C][/ROW]
[ROW][C]17[/C][C]47[/C][C]34.3625[/C][C]12.6375[/C][/ROW]
[ROW][C]18[/C][C]30[/C][C]34.3625[/C][C]-4.3625[/C][/ROW]
[ROW][C]19[/C][C]31[/C][C]34.3625[/C][C]-3.3625[/C][/ROW]
[ROW][C]20[/C][C]23[/C][C]34.3625[/C][C]-11.3625[/C][/ROW]
[ROW][C]21[/C][C]36[/C][C]34.3625[/C][C]1.6375[/C][/ROW]
[ROW][C]22[/C][C]36[/C][C]34.3625[/C][C]1.6375[/C][/ROW]
[ROW][C]23[/C][C]30[/C][C]34.3625[/C][C]-4.3625[/C][/ROW]
[ROW][C]24[/C][C]25[/C][C]27.68[/C][C]-2.68[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.3625[/C][C]4.6375[/C][/ROW]
[ROW][C]26[/C][C]34[/C][C]34.3625[/C][C]-0.362499999999997[/C][/ROW]
[ROW][C]27[/C][C]31[/C][C]28.8857142857143[/C][C]2.11428571428571[/C][/ROW]
[ROW][C]28[/C][C]31[/C][C]34.3625[/C][C]-3.3625[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.3625[/C][C]-1.3625[/C][/ROW]
[ROW][C]30[/C][C]25[/C][C]19.9310344827586[/C][C]5.06896551724138[/C][/ROW]
[ROW][C]31[/C][C]33[/C][C]34.3625[/C][C]-1.3625[/C][/ROW]
[ROW][C]32[/C][C]35[/C][C]34.3625[/C][C]0.637500000000003[/C][/ROW]
[ROW][C]33[/C][C]42[/C][C]27.68[/C][C]14.32[/C][/ROW]
[ROW][C]34[/C][C]43[/C][C]34.3625[/C][C]8.6375[/C][/ROW]
[ROW][C]35[/C][C]30[/C][C]27.68[/C][C]2.32[/C][/ROW]
[ROW][C]36[/C][C]33[/C][C]34.3625[/C][C]-1.3625[/C][/ROW]
[ROW][C]37[/C][C]13[/C][C]15.8811881188119[/C][C]-2.88118811881188[/C][/ROW]
[ROW][C]38[/C][C]32[/C][C]28.8857142857143[/C][C]3.11428571428571[/C][/ROW]
[ROW][C]39[/C][C]36[/C][C]34.3625[/C][C]1.6375[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]5.26315789473684[/C][C]-5.26315789473684[/C][/ROW]
[ROW][C]41[/C][C]28[/C][C]28.8857142857143[/C][C]-0.885714285714286[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]43[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]44[/C][C]32[/C][C]34.3625[/C][C]-2.3625[/C][/ROW]
[ROW][C]45[/C][C]30[/C][C]34.3625[/C][C]-4.3625[/C][/ROW]
[ROW][C]46[/C][C]35[/C][C]28.8857142857143[/C][C]6.11428571428571[/C][/ROW]
[ROW][C]47[/C][C]20[/C][C]28.8857142857143[/C][C]-8.88571428571429[/C][/ROW]
[ROW][C]48[/C][C]28[/C][C]28.8857142857143[/C][C]-0.885714285714286[/C][/ROW]
[ROW][C]49[/C][C]28[/C][C]19.9310344827586[/C][C]8.06896551724138[/C][/ROW]
[ROW][C]50[/C][C]39[/C][C]27.68[/C][C]11.32[/C][/ROW]
[ROW][C]51[/C][C]34[/C][C]34.3625[/C][C]-0.362499999999997[/C][/ROW]
[ROW][C]52[/C][C]26[/C][C]15.8811881188119[/C][C]10.1188118811881[/C][/ROW]
[ROW][C]53[/C][C]39[/C][C]34.3625[/C][C]4.6375[/C][/ROW]
[ROW][C]54[/C][C]39[/C][C]34.3625[/C][C]4.6375[/C][/ROW]
[ROW][C]55[/C][C]33[/C][C]34.3625[/C][C]-1.3625[/C][/ROW]
[ROW][C]56[/C][C]28[/C][C]34.3625[/C][C]-6.3625[/C][/ROW]
[ROW][C]57[/C][C]4[/C][C]5.26315789473684[/C][C]-1.26315789473684[/C][/ROW]
[ROW][C]58[/C][C]39[/C][C]34.3625[/C][C]4.6375[/C][/ROW]
[ROW][C]59[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]60[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]61[/C][C]29[/C][C]34.3625[/C][C]-5.3625[/C][/ROW]
[ROW][C]62[/C][C]44[/C][C]34.3625[/C][C]9.6375[/C][/ROW]
[ROW][C]63[/C][C]21[/C][C]34.3625[/C][C]-13.3625[/C][/ROW]
[ROW][C]64[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]65[/C][C]28[/C][C]34.3625[/C][C]-6.3625[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]34.3625[/C][C]0.637500000000003[/C][/ROW]
[ROW][C]67[/C][C]28[/C][C]34.3625[/C][C]-6.3625[/C][/ROW]
[ROW][C]68[/C][C]38[/C][C]34.3625[/C][C]3.6375[/C][/ROW]
[ROW][C]69[/C][C]23[/C][C]34.3625[/C][C]-11.3625[/C][/ROW]
[ROW][C]70[/C][C]36[/C][C]28.8857142857143[/C][C]7.11428571428571[/C][/ROW]
[ROW][C]71[/C][C]32[/C][C]28.8857142857143[/C][C]3.11428571428571[/C][/ROW]
[ROW][C]72[/C][C]29[/C][C]27.68[/C][C]1.32[/C][/ROW]
[ROW][C]73[/C][C]25[/C][C]28.8857142857143[/C][C]-3.88571428571429[/C][/ROW]
[ROW][C]74[/C][C]27[/C][C]28.8857142857143[/C][C]-1.88571428571429[/C][/ROW]
[ROW][C]75[/C][C]36[/C][C]34.3625[/C][C]1.6375[/C][/ROW]
[ROW][C]76[/C][C]28[/C][C]34.3625[/C][C]-6.3625[/C][/ROW]
[ROW][C]77[/C][C]23[/C][C]34.3625[/C][C]-11.3625[/C][/ROW]
[ROW][C]78[/C][C]40[/C][C]34.3625[/C][C]5.6375[/C][/ROW]
[ROW][C]79[/C][C]23[/C][C]15.8811881188119[/C][C]7.11881188118812[/C][/ROW]
[ROW][C]80[/C][C]40[/C][C]28.8857142857143[/C][C]11.1142857142857[/C][/ROW]
[ROW][C]81[/C][C]28[/C][C]28.8857142857143[/C][C]-0.885714285714286[/C][/ROW]
[ROW][C]82[/C][C]34[/C][C]34.3625[/C][C]-0.362499999999997[/C][/ROW]
[ROW][C]83[/C][C]33[/C][C]34.3625[/C][C]-1.3625[/C][/ROW]
[ROW][C]84[/C][C]28[/C][C]34.3625[/C][C]-6.3625[/C][/ROW]
[ROW][C]85[/C][C]34[/C][C]28.8857142857143[/C][C]5.11428571428571[/C][/ROW]
[ROW][C]86[/C][C]30[/C][C]34.3625[/C][C]-4.3625[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]28.8857142857143[/C][C]4.11428571428571[/C][/ROW]
[ROW][C]88[/C][C]22[/C][C]19.9310344827586[/C][C]2.06896551724138[/C][/ROW]
[ROW][C]89[/C][C]38[/C][C]34.3625[/C][C]3.6375[/C][/ROW]
[ROW][C]90[/C][C]26[/C][C]19.9310344827586[/C][C]6.06896551724138[/C][/ROW]
[ROW][C]91[/C][C]35[/C][C]34.3625[/C][C]0.637500000000003[/C][/ROW]
[ROW][C]92[/C][C]8[/C][C]15.8811881188119[/C][C]-7.88118811881188[/C][/ROW]
[ROW][C]93[/C][C]24[/C][C]19.9310344827586[/C][C]4.06896551724138[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]28.8857142857143[/C][C]0.114285714285714[/C][/ROW]
[ROW][C]95[/C][C]20[/C][C]19.9310344827586[/C][C]0.0689655172413808[/C][/ROW]
[ROW][C]96[/C][C]29[/C][C]28.8857142857143[/C][C]0.114285714285714[/C][/ROW]
[ROW][C]97[/C][C]45[/C][C]34.3625[/C][C]10.6375[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.3625[/C][C]2.6375[/C][/ROW]
[ROW][C]99[/C][C]33[/C][C]28.8857142857143[/C][C]4.11428571428571[/C][/ROW]
[ROW][C]100[/C][C]33[/C][C]34.3625[/C][C]-1.3625[/C][/ROW]
[ROW][C]101[/C][C]25[/C][C]19.9310344827586[/C][C]5.06896551724138[/C][/ROW]
[ROW][C]102[/C][C]32[/C][C]34.3625[/C][C]-2.3625[/C][/ROW]
[ROW][C]103[/C][C]29[/C][C]28.8857142857143[/C][C]0.114285714285714[/C][/ROW]
[ROW][C]104[/C][C]28[/C][C]28.8857142857143[/C][C]-0.885714285714286[/C][/ROW]
[ROW][C]105[/C][C]28[/C][C]34.3625[/C][C]-6.3625[/C][/ROW]
[ROW][C]106[/C][C]31[/C][C]34.3625[/C][C]-3.3625[/C][/ROW]
[ROW][C]107[/C][C]52[/C][C]34.3625[/C][C]17.6375[/C][/ROW]
[ROW][C]108[/C][C]21[/C][C]15.8811881188119[/C][C]5.11881188118812[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]34.3625[/C][C]-10.3625[/C][/ROW]
[ROW][C]110[/C][C]41[/C][C]34.3625[/C][C]6.6375[/C][/ROW]
[ROW][C]111[/C][C]33[/C][C]34.3625[/C][C]-1.3625[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]19.9310344827586[/C][C]12.0689655172414[/C][/ROW]
[ROW][C]113[/C][C]19[/C][C]15.8811881188119[/C][C]3.11881188118812[/C][/ROW]
[ROW][C]114[/C][C]20[/C][C]28.8857142857143[/C][C]-8.88571428571429[/C][/ROW]
[ROW][C]115[/C][C]31[/C][C]34.3625[/C][C]-3.3625[/C][/ROW]
[ROW][C]116[/C][C]31[/C][C]34.3625[/C][C]-3.3625[/C][/ROW]
[ROW][C]117[/C][C]32[/C][C]34.3625[/C][C]-2.3625[/C][/ROW]
[ROW][C]118[/C][C]18[/C][C]19.9310344827586[/C][C]-1.93103448275862[/C][/ROW]
[ROW][C]119[/C][C]23[/C][C]27.68[/C][C]-4.68[/C][/ROW]
[ROW][C]120[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]121[/C][C]20[/C][C]28.8857142857143[/C][C]-8.88571428571429[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]15.8811881188119[/C][C]-3.88118811881188[/C][/ROW]
[ROW][C]123[/C][C]17[/C][C]19.9310344827586[/C][C]-2.93103448275862[/C][/ROW]
[ROW][C]124[/C][C]30[/C][C]34.3625[/C][C]-4.3625[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]27.68[/C][C]3.32[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]15.8811881188119[/C][C]-5.88118811881188[/C][/ROW]
[ROW][C]127[/C][C]13[/C][C]15.8811881188119[/C][C]-2.88118811881188[/C][/ROW]
[ROW][C]128[/C][C]22[/C][C]28.8857142857143[/C][C]-6.88571428571429[/C][/ROW]
[ROW][C]129[/C][C]42[/C][C]34.3625[/C][C]7.6375[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]5.26315789473684[/C][C]-4.26315789473684[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]15.8811881188119[/C][C]-6.88118811881188[/C][/ROW]
[ROW][C]132[/C][C]32[/C][C]34.3625[/C][C]-2.3625[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]15.8811881188119[/C][C]-4.88118811881188[/C][/ROW]
[ROW][C]134[/C][C]25[/C][C]15.8811881188119[/C][C]9.11881188118812[/C][/ROW]
[ROW][C]135[/C][C]36[/C][C]28.8857142857143[/C][C]7.11428571428571[/C][/ROW]
[ROW][C]136[/C][C]31[/C][C]34.3625[/C][C]-3.3625[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]5.26315789473684[/C][C]-5.26315789473684[/C][/ROW]
[ROW][C]138[/C][C]24[/C][C]28.8857142857143[/C][C]-4.88571428571429[/C][/ROW]
[ROW][C]139[/C][C]13[/C][C]15.8811881188119[/C][C]-2.88118811881188[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]15.8811881188119[/C][C]-7.88118811881188[/C][/ROW]
[ROW][C]141[/C][C]13[/C][C]15.8811881188119[/C][C]-2.88118811881188[/C][/ROW]
[ROW][C]142[/C][C]19[/C][C]28.8857142857143[/C][C]-9.88571428571429[/C][/ROW]
[ROW][C]143[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]144[/C][C]33[/C][C]34.3625[/C][C]-1.3625[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]28.8857142857143[/C][C]11.1142857142857[/C][/ROW]
[ROW][C]146[/C][C]22[/C][C]15.8811881188119[/C][C]6.11881188118812[/C][/ROW]
[ROW][C]147[/C][C]38[/C][C]27.68[/C][C]10.32[/C][/ROW]
[ROW][C]148[/C][C]24[/C][C]27.68[/C][C]-3.68[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]5.26315789473684[/C][C]2.73684210526316[/C][/ROW]
[ROW][C]150[/C][C]35[/C][C]27.68[/C][C]7.32[/C][/ROW]
[ROW][C]151[/C][C]43[/C][C]34.3625[/C][C]8.6375[/C][/ROW]
[ROW][C]152[/C][C]43[/C][C]27.68[/C][C]15.32[/C][/ROW]
[ROW][C]153[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]154[/C][C]41[/C][C]34.3625[/C][C]6.6375[/C][/ROW]
[ROW][C]155[/C][C]38[/C][C]34.3625[/C][C]3.6375[/C][/ROW]
[ROW][C]156[/C][C]45[/C][C]34.3625[/C][C]10.6375[/C][/ROW]
[ROW][C]157[/C][C]31[/C][C]28.8857142857143[/C][C]2.11428571428571[/C][/ROW]
[ROW][C]158[/C][C]13[/C][C]15.8811881188119[/C][C]-2.88118811881188[/C][/ROW]
[ROW][C]159[/C][C]28[/C][C]27.68[/C][C]0.32[/C][/ROW]
[ROW][C]160[/C][C]31[/C][C]28.8857142857143[/C][C]2.11428571428571[/C][/ROW]
[ROW][C]161[/C][C]40[/C][C]34.3625[/C][C]5.6375[/C][/ROW]
[ROW][C]162[/C][C]30[/C][C]27.68[/C][C]2.32[/C][/ROW]
[ROW][C]163[/C][C]16[/C][C]19.9310344827586[/C][C]-3.93103448275862[/C][/ROW]
[ROW][C]164[/C][C]37[/C][C]34.3625[/C][C]2.6375[/C][/ROW]
[ROW][C]165[/C][C]30[/C][C]19.9310344827586[/C][C]10.0689655172414[/C][/ROW]
[ROW][C]166[/C][C]35[/C][C]34.3625[/C][C]0.637500000000003[/C][/ROW]
[ROW][C]167[/C][C]32[/C][C]28.8857142857143[/C][C]3.11428571428571[/C][/ROW]
[ROW][C]168[/C][C]27[/C][C]27.68[/C][C]-0.68[/C][/ROW]
[ROW][C]169[/C][C]20[/C][C]19.9310344827586[/C][C]0.0689655172413808[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]27.68[/C][C]-9.68[/C][/ROW]
[ROW][C]171[/C][C]31[/C][C]34.3625[/C][C]-3.3625[/C][/ROW]
[ROW][C]172[/C][C]31[/C][C]34.3625[/C][C]-3.3625[/C][/ROW]
[ROW][C]173[/C][C]21[/C][C]19.9310344827586[/C][C]1.06896551724138[/C][/ROW]
[ROW][C]174[/C][C]39[/C][C]34.3625[/C][C]4.6375[/C][/ROW]
[ROW][C]175[/C][C]41[/C][C]34.3625[/C][C]6.6375[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]19.9310344827586[/C][C]-6.93103448275862[/C][/ROW]
[ROW][C]177[/C][C]32[/C][C]34.3625[/C][C]-2.3625[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]179[/C][C]39[/C][C]34.3625[/C][C]4.6375[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]19.9310344827586[/C][C]-5.93103448275862[/C][/ROW]
[ROW][C]181[/C][C]7[/C][C]15.8811881188119[/C][C]-8.88118811881188[/C][/ROW]
[ROW][C]182[/C][C]17[/C][C]28.8857142857143[/C][C]-11.8857142857143[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]5.26315789473684[/C][C]-5.26315789473684[/C][/ROW]
[ROW][C]184[/C][C]30[/C][C]27.68[/C][C]2.32[/C][/ROW]
[ROW][C]185[/C][C]37[/C][C]34.3625[/C][C]2.6375[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]5.26315789473684[/C][C]-5.26315789473684[/C][/ROW]
[ROW][C]187[/C][C]5[/C][C]5.26315789473684[/C][C]-0.263157894736842[/C][/ROW]
[ROW][C]188[/C][C]1[/C][C]5.26315789473684[/C][C]-4.26315789473684[/C][/ROW]
[ROW][C]189[/C][C]16[/C][C]19.9310344827586[/C][C]-3.93103448275862[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]15.8811881188119[/C][C]16.1188118811881[/C][/ROW]
[ROW][C]191[/C][C]24[/C][C]27.68[/C][C]-3.68[/C][/ROW]
[ROW][C]192[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]193[/C][C]11[/C][C]15.8811881188119[/C][C]-4.88118811881188[/C][/ROW]
[ROW][C]194[/C][C]24[/C][C]15.8811881188119[/C][C]8.11881188118812[/C][/ROW]
[ROW][C]195[/C][C]22[/C][C]27.68[/C][C]-5.68[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]19.9310344827586[/C][C]-7.93103448275862[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]15.8811881188119[/C][C]3.11881188118812[/C][/ROW]
[ROW][C]198[/C][C]13[/C][C]27.68[/C][C]-14.68[/C][/ROW]
[ROW][C]199[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]200[/C][C]15[/C][C]15.8811881188119[/C][C]-0.881188118811881[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]15.8811881188119[/C][C]8.11881188118812[/C][/ROW]
[ROW][C]203[/C][C]15[/C][C]19.9310344827586[/C][C]-4.93103448275862[/C][/ROW]
[ROW][C]204[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]205[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]206[/C][C]20[/C][C]15.8811881188119[/C][C]4.11881188118812[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]19.9310344827586[/C][C]-3.93103448275862[/C][/ROW]
[ROW][C]209[/C][C]18[/C][C]19.9310344827586[/C][C]-1.93103448275862[/C][/ROW]
[ROW][C]210[/C][C]22[/C][C]19.9310344827586[/C][C]2.06896551724138[/C][/ROW]
[ROW][C]211[/C][C]8[/C][C]15.8811881188119[/C][C]-7.88118811881188[/C][/ROW]
[ROW][C]212[/C][C]17[/C][C]19.9310344827586[/C][C]-2.93103448275862[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]214[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]215[/C][C]23[/C][C]15.8811881188119[/C][C]7.11881188118812[/C][/ROW]
[ROW][C]216[/C][C]22[/C][C]15.8811881188119[/C][C]6.11881188118812[/C][/ROW]
[ROW][C]217[/C][C]13[/C][C]15.8811881188119[/C][C]-2.88118811881188[/C][/ROW]
[ROW][C]218[/C][C]13[/C][C]15.8811881188119[/C][C]-2.88118811881188[/C][/ROW]
[ROW][C]219[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]220[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]221[/C][C]20[/C][C]15.8811881188119[/C][C]4.11881188118812[/C][/ROW]
[ROW][C]222[/C][C]22[/C][C]27.68[/C][C]-5.68[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]28.8857142857143[/C][C]-11.8857142857143[/C][/ROW]
[ROW][C]224[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]225[/C][C]17[/C][C]5.26315789473684[/C][C]11.7368421052632[/C][/ROW]
[ROW][C]226[/C][C]12[/C][C]19.9310344827586[/C][C]-7.93103448275862[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]15.8811881188119[/C][C]-8.88118811881188[/C][/ROW]
[ROW][C]228[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]229[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]230[/C][C]23[/C][C]27.68[/C][C]-4.68[/C][/ROW]
[ROW][C]231[/C][C]17[/C][C]5.26315789473684[/C][C]11.7368421052632[/C][/ROW]
[ROW][C]232[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]15.8811881188119[/C][C]-0.881188118811881[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]235[/C][C]21[/C][C]15.8811881188119[/C][C]5.11881188118812[/C][/ROW]
[ROW][C]236[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]237[/C][C]18[/C][C]19.9310344827586[/C][C]-1.93103448275862[/C][/ROW]
[ROW][C]238[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]239[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]240[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]241[/C][C]15[/C][C]15.8811881188119[/C][C]-0.881188118811881[/C][/ROW]
[ROW][C]242[/C][C]21[/C][C]19.9310344827586[/C][C]1.06896551724138[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]244[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]15.8811881188119[/C][C]-0.881188118811881[/C][/ROW]
[ROW][C]246[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]15.8811881188119[/C][C]-0.881188118811881[/C][/ROW]
[ROW][C]248[/C][C]15[/C][C]15.8811881188119[/C][C]-0.881188118811881[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]15.8811881188119[/C][C]-5.88118811881188[/C][/ROW]
[ROW][C]250[/C][C]6[/C][C]15.8811881188119[/C][C]-9.88118811881188[/C][/ROW]
[ROW][C]251[/C][C]22[/C][C]19.9310344827586[/C][C]2.06896551724138[/C][/ROW]
[ROW][C]252[/C][C]21[/C][C]15.8811881188119[/C][C]5.11881188118812[/C][/ROW]
[ROW][C]253[/C][C]1[/C][C]5.26315789473684[/C][C]-4.26315789473684[/C][/ROW]
[ROW][C]254[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]256[/C][C]4[/C][C]5.26315789473684[/C][C]-1.26315789473684[/C][/ROW]
[ROW][C]257[/C][C]10[/C][C]15.8811881188119[/C][C]-5.88118811881188[/C][/ROW]
[ROW][C]258[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]259[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]260[/C][C]9[/C][C]15.8811881188119[/C][C]-6.88118811881188[/C][/ROW]
[ROW][C]261[/C][C]16[/C][C]5.26315789473684[/C][C]10.7368421052632[/C][/ROW]
[ROW][C]262[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]5.26315789473684[/C][C]1.73684210526316[/C][/ROW]
[ROW][C]264[/C][C]15[/C][C]15.8811881188119[/C][C]-0.881188118811881[/C][/ROW]
[ROW][C]265[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]266[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]267[/C][C]18[/C][C]15.8811881188119[/C][C]2.11881188118812[/C][/ROW]
[ROW][C]268[/C][C]12[/C][C]15.8811881188119[/C][C]-3.88118811881188[/C][/ROW]
[ROW][C]269[/C][C]16[/C][C]19.9310344827586[/C][C]-3.93103448275862[/C][/ROW]
[ROW][C]270[/C][C]21[/C][C]15.8811881188119[/C][C]5.11881188118812[/C][/ROW]
[ROW][C]271[/C][C]19[/C][C]15.8811881188119[/C][C]3.11881188118812[/C][/ROW]
[ROW][C]272[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]273[/C][C]1[/C][C]5.26315789473684[/C][C]-4.26315789473684[/C][/ROW]
[ROW][C]274[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]275[/C][C]10[/C][C]15.8811881188119[/C][C]-5.88118811881188[/C][/ROW]
[ROW][C]276[/C][C]19[/C][C]15.8811881188119[/C][C]3.11881188118812[/C][/ROW]
[ROW][C]277[/C][C]12[/C][C]15.8811881188119[/C][C]-3.88118811881188[/C][/ROW]
[ROW][C]278[/C][C]2[/C][C]5.26315789473684[/C][C]-3.26315789473684[/C][/ROW]
[ROW][C]279[/C][C]14[/C][C]15.8811881188119[/C][C]-1.88118811881188[/C][/ROW]
[ROW][C]280[/C][C]17[/C][C]15.8811881188119[/C][C]1.11881188118812[/C][/ROW]
[ROW][C]281[/C][C]19[/C][C]15.8811881188119[/C][C]3.11881188118812[/C][/ROW]
[ROW][C]282[/C][C]14[/C][C]27.68[/C][C]-13.68[/C][/ROW]
[ROW][C]283[/C][C]11[/C][C]15.8811881188119[/C][C]-4.88118811881188[/C][/ROW]
[ROW][C]284[/C][C]4[/C][C]5.26315789473684[/C][C]-1.26315789473684[/C][/ROW]
[ROW][C]285[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[ROW][C]286[/C][C]20[/C][C]15.8811881188119[/C][C]4.11881188118812[/C][/ROW]
[ROW][C]287[/C][C]12[/C][C]5.26315789473684[/C][C]6.73684210526316[/C][/ROW]
[ROW][C]288[/C][C]15[/C][C]15.8811881188119[/C][C]-0.881188118811881[/C][/ROW]
[ROW][C]289[/C][C]16[/C][C]15.8811881188119[/C][C]0.118811881188119[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155245&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155245&T=2

As an alternative you can also use a QR Code:

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

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	30	34.3625	-4.3625
2	28	28.8857142857143	-0.885714285714286
3	38	28.8857142857143	9.11428571428571
4	30	34.3625	-4.3625
5	22	19.9310344827586	2.06896551724138
6	26	27.68	-1.68
7	25	34.3625	-9.3625
8	18	15.8811881188119	2.11881188118812
9	11	15.8811881188119	-4.88118811881188
10	26	27.68	-1.68
11	25	28.8857142857143	-3.88571428571429
12	38	34.3625	3.6375
13	44	34.3625	9.6375
14	30	27.68	2.32
15	40	34.3625	5.6375
16	34	28.8857142857143	5.11428571428571
17	47	34.3625	12.6375
18	30	34.3625	-4.3625
19	31	34.3625	-3.3625
20	23	34.3625	-11.3625
21	36	34.3625	1.6375
22	36	34.3625	1.6375
23	30	34.3625	-4.3625
24	25	27.68	-2.68
25	39	34.3625	4.6375
26	34	34.3625	-0.362499999999997
27	31	28.8857142857143	2.11428571428571
28	31	34.3625	-3.3625
29	33	34.3625	-1.3625
30	25	19.9310344827586	5.06896551724138
31	33	34.3625	-1.3625
32	35	34.3625	0.637500000000003
33	42	27.68	14.32
34	43	34.3625	8.6375
35	30	27.68	2.32
36	33	34.3625	-1.3625
37	13	15.8811881188119	-2.88118811881188
38	32	28.8857142857143	3.11428571428571
39	36	34.3625	1.6375
40	0	5.26315789473684	-5.26315789473684
41	28	28.8857142857143	-0.885714285714286
42	14	15.8811881188119	-1.88118811881188
43	17	15.8811881188119	1.11881188118812
44	32	34.3625	-2.3625
45	30	34.3625	-4.3625
46	35	28.8857142857143	6.11428571428571
47	20	28.8857142857143	-8.88571428571429
48	28	28.8857142857143	-0.885714285714286
49	28	19.9310344827586	8.06896551724138
50	39	27.68	11.32
51	34	34.3625	-0.362499999999997
52	26	15.8811881188119	10.1188118811881
53	39	34.3625	4.6375
54	39	34.3625	4.6375
55	33	34.3625	-1.3625
56	28	34.3625	-6.3625
57	4	5.26315789473684	-1.26315789473684
58	39	34.3625	4.6375
59	18	15.8811881188119	2.11881188118812
60	14	15.8811881188119	-1.88118811881188
61	29	34.3625	-5.3625
62	44	34.3625	9.6375
63	21	34.3625	-13.3625
64	16	15.8811881188119	0.118811881188119
65	28	34.3625	-6.3625
66	35	34.3625	0.637500000000003
67	28	34.3625	-6.3625
68	38	34.3625	3.6375
69	23	34.3625	-11.3625
70	36	28.8857142857143	7.11428571428571
71	32	28.8857142857143	3.11428571428571
72	29	27.68	1.32
73	25	28.8857142857143	-3.88571428571429
74	27	28.8857142857143	-1.88571428571429
75	36	34.3625	1.6375
76	28	34.3625	-6.3625
77	23	34.3625	-11.3625
78	40	34.3625	5.6375
79	23	15.8811881188119	7.11881188118812
80	40	28.8857142857143	11.1142857142857
81	28	28.8857142857143	-0.885714285714286
82	34	34.3625	-0.362499999999997
83	33	34.3625	-1.3625
84	28	34.3625	-6.3625
85	34	28.8857142857143	5.11428571428571
86	30	34.3625	-4.3625
87	33	28.8857142857143	4.11428571428571
88	22	19.9310344827586	2.06896551724138
89	38	34.3625	3.6375
90	26	19.9310344827586	6.06896551724138
91	35	34.3625	0.637500000000003
92	8	15.8811881188119	-7.88118811881188
93	24	19.9310344827586	4.06896551724138
94	29	28.8857142857143	0.114285714285714
95	20	19.9310344827586	0.0689655172413808
96	29	28.8857142857143	0.114285714285714
97	45	34.3625	10.6375
98	37	34.3625	2.6375
99	33	28.8857142857143	4.11428571428571
100	33	34.3625	-1.3625
101	25	19.9310344827586	5.06896551724138
102	32	34.3625	-2.3625
103	29	28.8857142857143	0.114285714285714
104	28	28.8857142857143	-0.885714285714286
105	28	34.3625	-6.3625
106	31	34.3625	-3.3625
107	52	34.3625	17.6375
108	21	15.8811881188119	5.11881188118812
109	24	34.3625	-10.3625
110	41	34.3625	6.6375
111	33	34.3625	-1.3625
112	32	19.9310344827586	12.0689655172414
113	19	15.8811881188119	3.11881188118812
114	20	28.8857142857143	-8.88571428571429
115	31	34.3625	-3.3625
116	31	34.3625	-3.3625
117	32	34.3625	-2.3625
118	18	19.9310344827586	-1.93103448275862
119	23	27.68	-4.68
120	17	15.8811881188119	1.11881188118812
121	20	28.8857142857143	-8.88571428571429
122	12	15.8811881188119	-3.88118811881188
123	17	19.9310344827586	-2.93103448275862
124	30	34.3625	-4.3625
125	31	27.68	3.32
126	10	15.8811881188119	-5.88118811881188
127	13	15.8811881188119	-2.88118811881188
128	22	28.8857142857143	-6.88571428571429
129	42	34.3625	7.6375
130	1	5.26315789473684	-4.26315789473684
131	9	15.8811881188119	-6.88118811881188
132	32	34.3625	-2.3625
133	11	15.8811881188119	-4.88118811881188
134	25	15.8811881188119	9.11881188118812
135	36	28.8857142857143	7.11428571428571
136	31	34.3625	-3.3625
137	0	5.26315789473684	-5.26315789473684
138	24	28.8857142857143	-4.88571428571429
139	13	15.8811881188119	-2.88118811881188
140	8	15.8811881188119	-7.88118811881188
141	13	15.8811881188119	-2.88118811881188
142	19	28.8857142857143	-9.88571428571429
143	18	15.8811881188119	2.11881188118812
144	33	34.3625	-1.3625
145	40	28.8857142857143	11.1142857142857
146	22	15.8811881188119	6.11881188118812
147	38	27.68	10.32
148	24	27.68	-3.68
149	8	5.26315789473684	2.73684210526316
150	35	27.68	7.32
151	43	34.3625	8.6375
152	43	27.68	15.32
153	14	15.8811881188119	-1.88118811881188
154	41	34.3625	6.6375
155	38	34.3625	3.6375
156	45	34.3625	10.6375
157	31	28.8857142857143	2.11428571428571
158	13	15.8811881188119	-2.88118811881188
159	28	27.68	0.32
160	31	28.8857142857143	2.11428571428571
161	40	34.3625	5.6375
162	30	27.68	2.32
163	16	19.9310344827586	-3.93103448275862
164	37	34.3625	2.6375
165	30	19.9310344827586	10.0689655172414
166	35	34.3625	0.637500000000003
167	32	28.8857142857143	3.11428571428571
168	27	27.68	-0.68
169	20	19.9310344827586	0.0689655172413808
170	18	27.68	-9.68
171	31	34.3625	-3.3625
172	31	34.3625	-3.3625
173	21	19.9310344827586	1.06896551724138
174	39	34.3625	4.6375
175	41	34.3625	6.6375
176	13	19.9310344827586	-6.93103448275862
177	32	34.3625	-2.3625
178	18	15.8811881188119	2.11881188118812
179	39	34.3625	4.6375
180	14	19.9310344827586	-5.93103448275862
181	7	15.8811881188119	-8.88118811881188
182	17	28.8857142857143	-11.8857142857143
183	0	5.26315789473684	-5.26315789473684
184	30	27.68	2.32
185	37	34.3625	2.6375
186	0	5.26315789473684	-5.26315789473684
187	5	5.26315789473684	-0.263157894736842
188	1	5.26315789473684	-4.26315789473684
189	16	19.9310344827586	-3.93103448275862
190	32	15.8811881188119	16.1188118811881
191	24	27.68	-3.68
192	17	15.8811881188119	1.11881188118812
193	11	15.8811881188119	-4.88118811881188
194	24	15.8811881188119	8.11881188118812
195	22	27.68	-5.68
196	12	19.9310344827586	-7.93103448275862
197	19	15.8811881188119	3.11881188118812
198	13	27.68	-14.68
199	17	15.8811881188119	1.11881188118812
200	15	15.8811881188119	-0.881188118811881
201	16	15.8811881188119	0.118811881188119
202	24	15.8811881188119	8.11881188118812
203	15	19.9310344827586	-4.93103448275862
204	17	15.8811881188119	1.11881188118812
205	18	15.8811881188119	2.11881188118812
206	20	15.8811881188119	4.11881188118812
207	16	15.8811881188119	0.118811881188119
208	16	19.9310344827586	-3.93103448275862
209	18	19.9310344827586	-1.93103448275862
210	22	19.9310344827586	2.06896551724138
211	8	15.8811881188119	-7.88118811881188
212	17	19.9310344827586	-2.93103448275862
213	18	15.8811881188119	2.11881188118812
214	16	15.8811881188119	0.118811881188119
215	23	15.8811881188119	7.11881188118812
216	22	15.8811881188119	6.11881188118812
217	13	15.8811881188119	-2.88118811881188
218	13	15.8811881188119	-2.88118811881188
219	16	15.8811881188119	0.118811881188119
220	16	15.8811881188119	0.118811881188119
221	20	15.8811881188119	4.11881188118812
222	22	27.68	-5.68
223	17	28.8857142857143	-11.8857142857143
224	18	15.8811881188119	2.11881188118812
225	17	5.26315789473684	11.7368421052632
226	12	19.9310344827586	-7.93103448275862
227	7	15.8811881188119	-8.88118811881188
228	17	15.8811881188119	1.11881188118812
229	14	15.8811881188119	-1.88118811881188
230	23	27.68	-4.68
231	17	5.26315789473684	11.7368421052632
232	14	15.8811881188119	-1.88118811881188
233	15	15.8811881188119	-0.881188118811881
234	17	15.8811881188119	1.11881188118812
235	21	15.8811881188119	5.11881188118812
236	18	15.8811881188119	2.11881188118812
237	18	19.9310344827586	-1.93103448275862
238	17	15.8811881188119	1.11881188118812
239	17	15.8811881188119	1.11881188118812
240	16	15.8811881188119	0.118811881188119
241	15	15.8811881188119	-0.881188118811881
242	21	19.9310344827586	1.06896551724138
243	16	15.8811881188119	0.118811881188119
244	14	15.8811881188119	-1.88118811881188
245	15	15.8811881188119	-0.881188118811881
246	17	15.8811881188119	1.11881188118812
247	15	15.8811881188119	-0.881188118811881
248	15	15.8811881188119	-0.881188118811881
249	10	15.8811881188119	-5.88118811881188
250	6	15.8811881188119	-9.88118811881188
251	22	19.9310344827586	2.06896551724138
252	21	15.8811881188119	5.11881188118812
253	1	5.26315789473684	-4.26315789473684
254	18	15.8811881188119	2.11881188118812
255	17	15.8811881188119	1.11881188118812
256	4	5.26315789473684	-1.26315789473684
257	10	15.8811881188119	-5.88118811881188
258	16	15.8811881188119	0.118811881188119
259	16	15.8811881188119	0.118811881188119
260	9	15.8811881188119	-6.88118811881188
261	16	5.26315789473684	10.7368421052632
262	17	15.8811881188119	1.11881188118812
263	7	5.26315789473684	1.73684210526316
264	15	15.8811881188119	-0.881188118811881
265	14	15.8811881188119	-1.88118811881188
266	14	15.8811881188119	-1.88118811881188
267	18	15.8811881188119	2.11881188118812
268	12	15.8811881188119	-3.88118811881188
269	16	19.9310344827586	-3.93103448275862
270	21	15.8811881188119	5.11881188118812
271	19	15.8811881188119	3.11881188118812
272	16	15.8811881188119	0.118811881188119
273	1	5.26315789473684	-4.26315789473684
274	16	15.8811881188119	0.118811881188119
275	10	15.8811881188119	-5.88118811881188
276	19	15.8811881188119	3.11881188118812
277	12	15.8811881188119	-3.88118811881188
278	2	5.26315789473684	-3.26315789473684
279	14	15.8811881188119	-1.88118811881188
280	17	15.8811881188119	1.11881188118812
281	19	15.8811881188119	3.11881188118812
282	14	27.68	-13.68
283	11	15.8811881188119	-4.88118811881188
284	4	5.26315789473684	-1.26315789473684
285	16	15.8811881188119	0.118811881188119
286	20	15.8811881188119	4.11881188118812
287	12	5.26315789473684	6.73684210526316
288	15	15.8811881188119	-0.881188118811881
289	16	15.8811881188119	0.118811881188119

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 7 ; par2 = none ; par3 = 2 ; par4 = no ;

Parameters (R input):

par1 = 5 ; par2 = none ; par3 = 2 ; 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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code