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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

Sat, 08 Dec 2012 11:48:25 -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/2012/Dec/08/t1354985343ay8mxkt0gr8ltvd.htm/, Retrieved Sat, 27 Apr 2024 00:57:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197683, Retrieved Sat, 27 Apr 2024 00:57:05 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

107

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)] [Hall_of_fame2] [2012-12-08 16:43:19] [3dc52aaca1c2323e282536a0c7c26bc2]
-           [Recursive Partitioning (Regression Trees)] [Hall_of_fame3] [2012-12-08 16:48:25] [2f047a68beb18e789d06219c4ebd4599] [Current]
-             [Recursive Partitioning (Regression Trees)] [Hall_of_fame2] [2012-12-08 16:54:06] [3dc52aaca1c2323e282536a0c7c26bc2] 
-               [Recursive Partitioning (Regression Trees)] [Hall_of_fame2] [2012-12-08 17:00:03] [3dc52aaca1c2323e282536a0c7c26bc2] 
-    D            [Recursive Partitioning (Regression Trees)] [Hall_of_fame3] [2012-12-08 17:07:09] [3dc52aaca1c2323e282536a0c7c26bc2] 

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Dataseries X:

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Histogram

Boxplots

1418	210907	56	396	81	3	79	30	115	94	112285	24188	146283	144	145
869	120982	56	297	55	4	58	28	109	103	84786	18273	98364	103	101
1530	176508	54	559	50	12	60	38	146	93	83123	14130	86146	98	98
2172	179321	89	967	125	2	108	30	116	103	101193	32287	96933	135	132
901	123185	40	270	40	1	49	22	68	51	38361	8654	79234	61	60
463	52746	25	143	37	3	0	26	101	70	68504	9245	42551	39	38
3201	385534	92	1562	63	0	121	25	96	91	119182	33251	195663	150	144
371	33170	18	109	44	0	1	18	67	22	22807	1271	6853	5	5
1192	101645	63	371	88	0	20	11	44	38	17140	5279	21529	28	28
1583	149061	44	656	66	5	43	26	100	93	116174	27101	95757	84	84
1439	165446	33	511	57	0	69	25	93	60	57635	16373	85584	80	79
1764	237213	84	655	74	0	78	38	140	123	66198	19716	143983	130	127
1495	173326	88	465	49	7	86	44	166	148	71701	17753	75851	82	78
1373	133131	55	525	52	7	44	30	99	90	57793	9028	59238	60	60
2187	258873	60	885	88	3	104	40	139	124	80444	18653	93163	131	131
1491	180083	66	497	36	9	63	34	130	70	53855	8828	96037	84	84
4041	324799	154	1436	108	0	158	47	181	168	97668	29498	151511	140	133
1706	230964	53	612	43	4	102	30	116	115	133824	27563	136368	151	150
2152	236785	119	865	75	3	77	31	116	71	101481	18293	112642	91	91
1036	135473	41	385	32	0	82	23	88	66	99645	22530	94728	138	132
1882	202925	61	567	44	7	115	36	139	134	114789	15977	105499	150	136
1929	215147	58	639	85	0	101	36	135	117	99052	35082	121527	124	124
2242	344297	75	963	86	1	80	30	108	108	67654	16116	127766	119	118
1220	153935	33	398	56	5	50	25	89	84	65553	15849	98958	73	70
1289	132943	40	410	50	7	83	39	156	156	97500	16026	77900	110	107
2515	174724	92	966	135	0	123	34	129	120	69112	26569	85646	123	119
2147	174415	100	801	63	0	73	31	118	114	82753	24785	98579	90	89
2352	225548	112	892	81	5	81	31	118	94	85323	17569	130767	116	112
1638	223632	73	513	52	0	105	33	125	120	72654	23825	131741	113	108
1222	124817	40	469	44	0	47	25	95	81	30727	7869	53907	56	52
1812	221698	45	683	113	0	105	33	126	110	77873	14975	178812	115	112
1677	210767	60	643	39	3	94	35	135	133	117478	37791	146761	119	116
1579	170266	62	535	73	4	44	42	154	122	74007	9605	82036	129	123
1731	260561	75	625	48	1	114	43	165	158	90183	27295	163253	127	125
807	84853	31	264	33	4	38	30	113	109	61542	2746	27032	27	27
2452	294424	77	992	59	2	107	33	127	124	101494	34461	171975	175	162
829	101011	34	238	41	0	30	13	52	39	27570	8098	65990	35	32
1940	215641	46	818	69	0	71	32	121	92	55813	4787	86572	64	64
2662	325107	99	937	64	0	84	36	136	126	79215	24919	159676	96	92
186	7176	17	70	1	0	0	0	0	0	1423	603	1929	0	0
1499	167542	66	507	59	2	59	28	108	70	55461	16329	85371	84	83
865	106408	30	260	32	1	33	14	46	37	31081	12558	58391	41	41
1793	96560	76	503	129	0	42	17	54	38	22996	7784	31580	47	47
2527	265769	146	927	37	2	96	32	124	120	83122	28522	136815	126	120
2747	269651	67	1269	31	10	106	30	115	93	70106	22265	120642	105	105
1324	149112	56	537	65	6	56	35	128	95	60578	14459	69107	80	79
2702	175824	107	910	107	0	57	20	80	77	39992	14526	50495	70	65
1383	152871	58	532	74	5	59	28	97	90	79892	22240	108016	73	70
1179	111665	34	345	54	4	39	28	104	80	49810	11802	46341	57	55
2099	116408	61	918	76	1	34	39	59	31	71570	7623	78348	40	39
4308	362301	119	1635	715	2	76	34	125	110	100708	11912	79336	68	67
918	78800	42	330	57	2	20	26	82	66	33032	7935	56968	21	21
1831	183167	66	557	66	0	91	39	149	138	82875	18220	93176	127	127
3373	277965	89	1178	106	8	115	39	149	133	139077	19199	161632	154	152
1713	150629	44	740	54	3	85	33	122	113	71595	19918	87850	116	113
1438	168809	66	452	32	0	76	28	118	100	72260	21884	127969	102	99
496	24188	24	218	20	0	8	4	12	7	5950	2694	15049	7	7
2253	329267	259	764	71	8	79	39	144	140	115762	15808	155135	148	141
744	65029	17	255	21	5	21	18	67	61	32551	3597	25109	21	21
1161	101097	64	454	70	3	30	14	52	41	31701	5296	45824	35	35
2352	218946	41	866	112	1	76	29	108	96	80670	25239	102996	112	109
2144	244052	68	574	66	5	101	44	166	164	143558	29801	160604	137	133
4691	341570	168	1276	190	1	94	21	80	78	117105	18450	158051	135	123
1112	103597	43	379	66	1	27	16	60	49	23789	7132	44547	26	26
2694	233328	132	825	165	5	92	28	107	102	120733	34861	162647	230	230
1973	256462	105	798	56	0	123	35	127	124	105195	35940	174141	181	166
1769	206161	71	663	61	12	75	28	107	99	73107	16688	60622	71	68
3148	311473	112	1069	53	8	128	38	146	129	132068	24683	179566	147	147
2474	235800	94	921	127	8	105	23	84	62	149193	46230	184301	190	179
2084	177939	82	858	63	8	55	36	141	73	46821	10387	75661	64	61
1954	207176	70	711	38	8	56	32	123	114	87011	21436	96144	105	101
1226	196553	57	503	50	2	41	29	111	99	95260	30546	129847	107	108
1389	174184	53	382	52	0	72	25	98	70	55183	19746	117286	94	90
1496	143246	103	464	42	5	67	27	105	104	106671	15977	71180	116	114
2269	187559	121	717	76	8	75	36	135	116	73511	22583	109377	106	103
1833	187681	62	690	67	2	114	28	107	91	92945	17274	85298	143	142
1268	119016	52	462	50	5	118	23	85	74	78664	16469	73631	81	79
1943	182192	52	657	53	12	77	40	155	138	70054	14251	86767	89	88
893	73566	32	385	39	6	22	23	88	67	22618	3007	23824	26	25
1762	194979	62	577	50	7	66	40	155	151	74011	16851	93487	84	83
1403	167488	45	619	77	2	69	28	104	72	83737	21113	82981	113	113
1425	143756	46	479	57	0	105	34	132	120	69094	17401	73815	120	118
1857	275541	63	817	73	4	116	33	127	115	93133	23958	94552	110	110
1840	243199	75	752	34	3	88	28	108	105	95536	23567	132190	134	129
1502	182999	88	430	39	6	73	34	129	104	225920	13065	128754	54	51
1441	135649	46	451	46	2	99	30	116	108	62133	15358	66363	96	93
1420	152299	53	537	63	0	62	33	122	98	61370	14587	67808	78	76
1416	120221	37	519	35	1	53	22	85	69	43836	12770	61724	51	49
2970	346485	90	1000	106	0	118	38	147	111	106117	24021	131722	121	118
1317	145790	63	637	43	5	30	26	99	99	38692	9648	68580	38	38
1644	193339	78	465	47	2	100	35	87	71	84651	20537	106175	145	141
870	80953	25	437	31	0	49	8	28	27	56622	7905	55792	59	58
1654	122774	45	711	162	0	24	24	90	69	15986	4527	25157	27	27
1054	130585	46	299	57	5	67	29	109	107	95364	30495	76669	91	91
937	112611	41	248	36	0	46	20	78	73	26706	7117	57283	48	48
3004	286468	144	1162	263	1	57	29	111	107	89691	17719	105805	68	63
2008	241066	82	714	78	0	75	45	158	93	67267	27056	129484	58	56
2547	148446	91	905	63	1	135	37	141	129	126846	33473	72413	150	144
1885	204713	71	649	54	1	68	33	122	69	41140	9758	87831	74	73
1626	182079	63	512	63	2	124	33	124	118	102860	21115	96971	181	168
1468	140344	53	472	77	6	33	25	93	73	51715	7236	71299	65	64
2445	220516	62	905	79	1	98	32	124	119	55801	13790	77494	97	97
1964	243060	63	786	110	4	58	29	112	104	111813	32902	120336	121	117
1381	162765	32	489	56	2	68	28	108	107	120293	25131	93913	99	100
1369	182613	39	479	56	3	81	28	99	99	138599	30910	136048	152	149
1659	232138	62	617	43	0	131	31	117	90	161647	35947	181248	188	187
2888	265318	117	925	111	10	110	52	199	197	115929	29848	146123	138	127
1290	85574	34	351	71	0	37	21	78	36	24266	6943	32036	40	37
2845	310839	92	1144	62	9	130	24	91	85	162901	42705	186646	254	245
1982	225060	93	669	56	7	93	41	158	139	109825	31808	102255	87	87
1904	232317	54	707	74	0	118	33	126	106	129838	26675	168237	178	177
1391	144966	144	458	60	0	39	32	122	50	37510	8435	64219	51	49
602	43287	14	214	43	4	13	19	71	64	43750	7409	19630	49	49
1743	155754	61	599	68	4	74	20	75	31	40652	14993	76825	73	73
1559	164709	109	572	53	0	81	31	115	63	87771	36867	115338	176	177
2014	201940	38	897	87	0	109	31	119	92	85872	33835	109427	94	94
2143	235454	73	819	46	0	151	32	124	106	89275	24164	118168	120	117
2146	220801	75	720	105	1	51	18	72	63	44418	12607	84845	66	60
874	99466	50	273	32	0	28	23	91	69	192565	22609	153197	56	55
1590	92661	61	508	133	1	40	17	45	41	35232	5892	29877	39	39
1590	133328	55	506	79	0	56	20	78	56	40909	17014	63506	66	64
1210	61361	77	451	51	0	27	12	39	25	13294	5394	22445	27	26
2072	125930	75	699	207	4	37	17	68	65	32387	9178	47695	65	64
1281	100750	72	407	67	0	83	30	119	93	140867	6440	68370	58	58
1401	224549	50	465	47	4	54	31	117	114	120662	21916	146304	98	95
834	82316	32	245	34	4	27	10	39	38	21233	4011	38233	25	25
1105	102010	53	370	66	3	28	13	50	44	44332	5818	42071	26	26
1272	101523	42	316	76	0	59	22	88	87	61056	18647	50517	77	76
1944	243511	71	603	65	0	133	42	155	110	101338	20556	103950	130	129
391	22938	10	154	9	0	12	1	0	0	1168	238	5841	11	11
761	41566	35	229	42	5	0	9	36	27	13497	70	2341	2	2
1605	152474	65	577	45	0	106	32	123	83	65567	22392	84396	101	101
530	61857	25	192	25	4	23	11	32	30	25162	3913	24610	31	28
1988	99923	66	617	115	0	44	25	99	80	32334	12237	35753	36	36
1386	132487	41	411	97	0	71	36	136	98	40735	8388	55515	120	89
2395	317394	86	975	53	1	116	31	117	82	91413	22120	209056	195	193
387	21054	16	146	2	0	4	0	0	0	855	338	6622	4	4
1742	209641	42	705	52	5	62	24	88	60	97068	11727	115814	89	84
620	22648	19	184	44	0	12	13	39	28	44339	3704	11609	24	23
449	31414	19	200	22	0	18	8	25	9	14116	3988	13155	39	39
800	46698	45	274	35	0	14	13	52	33	10288	3030	18274	14	14
1684	131698	65	502	74	0	60	19	75	59	65622	13520	72875	78	78
1050	91735	35	382	103	0	7	18	71	49	16563	1421	10112	15	14
2699	244749	95	964	144	2	98	33	124	115	76643	20923	142775	106	101
1606	184510	49	537	60	7	64	40	151	140	110681	20237	68847	83	82
1502	79863	37	438	134	1	29	22	71	49	29011	3219	17659	24	24
1204	128423	64	369	89	8	32	38	145	120	92696	3769	20112	37	36
1138	97839	38	417	42	2	25	24	87	66	94785	12252	61023	77	75
568	38214	34	276	52	0	16	8	27	21	8773	1888	13983	16	16
1459	151101	32	514	98	2	48	35	131	124	83209	14497	65176	56	55
2158	272458	65	822	99	0	100	43	162	152	93815	28864	132432	132	131
1111	172494	52	389	52	0	46	43	165	139	86687	21721	112494	144	131
1421	108043	62	466	29	1	45	14	54	38	34553	4821	45109	40	39
2833	328107	65	1255	125	3	129	41	159	144	105547	33644	170875	153	144
1955	250579	83	694	106	0	130	38	147	120	103487	15923	180759	143	139
2922	351067	95	1024	95	3	136	45	170	160	213688	42935	214921	220	211
1002	158015	29	400	40	0	59	31	119	114	71220	18864	100226	79	78
1060	98866	18	397	140	0	25	13	49	39	23517	4977	32043	50	50
956	85439	33	350	43	0	32	28	104	78	56926	7785	54454	39	39
2186	229242	247	719	128	4	63	31	120	119	91721	17939	78876	95	90
3604	351619	139	1277	142	4	95	40	150	141	115168	23436	170745	169	166
1035	84207	29	356	73	11	14	30	112	101	111194	325	6940	12	12
1417	120445	118	457	72	0	36	16	59	56	51009	13539	49025	63	57
3261	324598	110	1402	128	0	113	37	136	133	135777	34538	122037	134	133
1587	131069	67	600	61	4	47	30	107	83	51513	12198	53782	69	69
1424	204271	42	480	73	0	92	35	130	116	74163	26924	127748	119	119
1701	165543	65	595	148	1	70	32	115	90	51633	12716	86839	119	119
1249	141722	94	436	64	0	19	27	107	36	75345	8172	44830	75	65
946	116048	64	230	45	0	50	20	75	50	33416	10855	77395	63	61
1926	250047	81	651	58	0	41	18	71	61	83305	11932	89324	55	49
3352	299775	95	1367	97	9	91	31	120	97	98952	14300	103300	103	101
1641	195838	67	564	50	1	111	31	116	98	102372	25515	112283	197	196
2035	173260	63	716	37	3	41	21	79	78	37238	2805	10901	16	15
2312	254488	83	747	50	10	120	39	150	117	103772	29402	120691	140	136
1369	104389	45	467	105	5	135	41	156	148	123969	16440	58106	89	89
1577	136084	30	671	69	0	27	13	51	41	27142	11221	57140	40	40
2201	199476	70	861	46	2	87	32	118	105	135400	28732	122422	125	123
961	92499	32	319	57	0	25	18	71	55	21399	5250	25899	21	21
1900	224330	83	612	52	1	131	39	144	132	130115	28608	139296	167	163
1254	135781	31	433	98	2	45	14	47	44	24874	8092	52678	32	29
1335	74408	67	434	61	4	29	7	28	21	34988	4473	23853	36	35
1597	81240	66	503	89	0	58	17	68	50	45549	1572	17306	13	13
207	14688	10	85	0	0	4	0	0	0	6023	2065	7953	5	5
1645	181633	70	564	48	2	47	30	110	73	64466	14817	89455	96	96
2429	271856	103	824	91	1	109	37	147	86	54990	16714	147866	151	151
151	7199	5	74	0	0	7	0	0	0	1644	556	4245	6	6
474	46660	20	259	7	0	12	5	15	13	6179	2089	21509	13	13
141	17547	5	69	3	0	0	1	4	4	3926	2658	7670	3	3
1639	133368	36	535	54	1	37	16	64	57	32755	10695	66675	57	56
872	95227	34	239	70	0	37	32	111	48	34777	1669	14336	23	23
1318	152601	48	438	36	2	46	24	85	46	73224	16267	53608	61	57
1018	98146	40	459	37	0	15	17	68	48	27114	7768	30059	21	14
1383	79619	43	426	123	3	42	11	40	32	20760	7252	29668	43	43
1314	59194	31	288	247	6	7	24	80	68	37636	6387	22097	20	20
1335	139942	42	498	46	0	54	22	88	87	65461	18715	96841	82	72
1403	118612	46	454	72	2	54	12	48	43	30080	7936	41907	90	87
910	72880	33	376	41	0	14	19	76	67	24094	8643	27080	25	21
616	65475	18	225	24	2	16	13	51	46	69008	7294	35885	60	56
1407	99643	55	555	45	1	33	17	67	46	54968	4570	41247	61	59
771	71965	35	252	33	1	32	15	59	56	46090	7185	28313	85	82
766	77272	59	208	27	2	21	16	61	48	27507	10058	36845	43	43
473	49289	19	130	36	1	15	24	76	44	10672	2342	16548	25	25
1376	135131	66	481	87	0	38	15	60	60	34029	8509	36134	41	38
1232	108446	60	389	90	1	22	17	68	65	46300	13275	55764	26	25
1521	89746	36	565	114	3	28	18	71	55	24760	6816	28910	38	38
572	44296	25	173	31	0	10	20	76	38	18779	1930	13339	12	12
1059	77648	47	278	45	0	31	16	62	52	21280	8086	25319	29	29
1544	181528	54	609	69	0	32	16	61	60	40662	10737	66956	49	47
1230	134019	53	422	51	0	32	18	67	54	28987	8033	47487	46	45
1206	124064	40	445	34	1	43	22	88	86	22827	7058	52785	41	40
1205	92630	40	387	60	4	27	8	30	24	18513	6782	44683	31	30
1255	121848	39	339	45	0	37	17	64	52	30594	5401	35619	41	41
613	52915	14	181	54	0	20	18	68	49	24006	6521	21920	26	25
721	81872	45	245	25	0	32	16	64	61	27913	10856	45608	23	23
1109	58981	36	384	38	7	0	23	91	61	42744	2154	7721	14	14
740	53515	28	212	52	2	5	22	88	81	12934	6117	20634	16	16
1126	60812	44	399	67	0	26	13	52	43	22574	5238	29788	25	26
728	56375	30	229	74	7	10	13	49	40	41385	4820	31931	21	21
689	65490	22	224	38	3	27	16	62	40	18653	5615	37754	32	27
592	80949	17	203	30	0	11	16	61	56	18472	4272	32505	9	9
995	76302	31	333	26	0	29	20	76	68	30976	8702	40557	35	33
1613	104011	55	384	67	6	25	22	88	79	63339	15340	94238	42	42
2048	98104	54	636	132	2	55	17	66	47	25568	8030	44197	68	68
705	67989	21	185	42	0	23	18	71	57	33747	9526	43228	32	32
301	30989	14	93	35	0	5	17	68	41	4154	1278	4103	6	6
1803	135458	81	581	118	3	43	12	48	29	19474	4236	44144	68	67
799	73504	35	248	68	0	23	7	25	3	35130	3023	32868	33	33
861	63123	43	304	43	1	34	17	68	60	39067	7196	27640	84	77
1186	61254	46	344	76	1	36	14	41	30	13310	3394	14063	46	46
1451	74914	30	407	64	0	35	23	90	79	65892	6371	28990	30	30
628	31774	23	170	48	1	0	17	66	47	4143	1574	4694	0	0
1161	81437	38	312	64	0	37	14	54	40	28579	9620	42648	36	36
1463	87186	54	507	56	0	28	15	59	48	51776	6978	64329	47	46
742	50090	20	224	71	0	16	17	60	36	21152	4911	21928	20	18
979	65745	53	340	75	0	26	21	77	42	38084	8645	25836	50	48
675	56653	45	168	39	0	38	18	68	49	27717	8987	22779	30	29
1241	158399	39	443	42	0	23	18	72	57	32928	5544	40820	30	28
676	46455	20	204	39	0	22	17	67	12	11342	3083	27530	34	34
1049	73624	24	367	93	0	30	17	64	40	19499	6909	32378	33	33
620	38395	31	210	38	0	16	16	63	43	16380	3189	10824	34	34
1081	91899	35	335	60	0	18	15	59	33	36874	6745	39613	37	33
1688	139526	151	364	71	0	28	21	84	77	48259	16724	60865	83	80
736	52164	52	178	52	0	32	16	64	43	16734	4850	19787	32	32
617	51567	30	206	27	2	21	14	56	45	28207	7025	20107	30	30
812	70551	31	279	59	0	23	15	54	47	30143	6047	36605	43	41
1051	84856	29	387	40	1	29	17	67	43	41369	7377	40961	41	41
1656	102538	57	490	79	1	50	15	58	45	45833	9078	48231	51	51
705	86678	40	238	44	0	12	15	59	50	29156	4605	39725	19	18
945	85709	44	343	65	0	21	10	40	35	35944	3238	21455	37	34
554	34662	25	232	10	0	18	6	22	7	36278	8100	23430	33	31
1597	150580	77	530	124	0	27	22	83	71	45588	9653	62991	41	39
982	99611	35	291	81	0	41	21	81	67	45097	8914	49363	54	54
222	19349	11	67	15	0	13	1	2	0	3895	786	9604	14	14
1212	99373	63	397	92	1	12	18	72	62	28394	6700	24552	25	24
1143	86230	44	467	42	0	21	17	61	54	18632	5788	31493	25	24
435	30837	19	178	10	0	8	4	15	4	2325	593	3439	8	8
532	31706	13	175	24	0	26	10	32	25	25139	4506	19555	26	26
882	89806	42	299	64	0	27	16	62	40	27975	6382	21228	20	19
608	62088	38	154	45	1	13	16	58	38	14483	5621	23177	11	11
459	40151	29	106	22	0	16	9	36	19	13127	3997	22094	14	14
578	27634	20	189	56	0	2	16	59	17	5839	520	2342	3	1
826	76990	27	194	94	0	42	17	68	67	24069	8891	38798	40	39
509	37460	20	135	19	0	5	7	21	14	3738	999	3255	5	5
717	54157	19	201	35	0	37	15	55	30	18625	7067	24261	38	37
637	49862	37	207	32	0	17	14	54	54	36341	4639	18511	32	32
857	84337	26	280	35	0	38	14	55	35	24548	5654	40798	41	38
830	64175	42	260	48	0	37	18	72	59	21792	6928	28893	46	47
652	59382	49	227	49	0	29	12	41	24	26263	1514	21425	47	47
707	119308	30	239	48	0	32	16	61	58	23686	9238	50276	37	37
954	76702	49	333	62	0	35	21	67	42	49303	8204	37643	51	51
1461	103425	67	428	96	1	17	19	76	46	25659	5926	30377	49	45
672	70344	28	230	45	0	20	16	64	61	28904	5785	27126	21	21
778	43410	19	292	63	0	7	1	3	3	2781	4	13	1	1
1141	104838	49	350	71	1	46	16	63	52	29236	5930	42097	44	42
680	62215	27	186	26	0	24	10	40	25	19546	3710	24451	26	26
1090	69304	30	326	48	6	40	19	69	40	22818	705	14335	21	21
616	53117	22	155	29	3	3	12	48	32	32689	443	5084	4	4
285	19764	12	75	19	1	10	2	8	4	5752	2416	9927	10	10
1145	86680	31	361	45	2	37	14	52	49	22197	7747	43527	43	43
733	84105	20	261	45	0	17	17	66	63	20055	5432	27184	34	34
888	77945	20	299	67	0	28	19	76	67	25272	4913	21610	32	31
849	89113	39	300	30	0	19	14	43	32	82206	2650	20484	20	19
1182	91005	29	450	36	3	29	11	39	23	32073	2370	20156	34	34
528	40248	16	183	34	1	8	4	14	7	5444	775	6012	6	6
642	64187	27	238	36	0	10	16	61	54	20154	5576	18475	12	11
947	50857	21	165	34	0	15	20	71	37	36944	1352	12645	24	24
819	56613	19	234	37	1	15	12	44	35	8019	3080	11017	16	16
757	62792	35	176	46	0	28	15	60	51	30884	10205	37623	72	72
894	72535	14	329	44	0	17	16	64	39	19540	6095	35873	27	21

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	19 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 & 19 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197683&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]19 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=197683&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197683&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	19 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Goodness of Fit
Correlation	0.9221
R-squared	0.8502
RMSE	14.2574

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.9221 \tabularnewline
R-squared & 0.8502 \tabularnewline
RMSE & 14.2574 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197683&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.9221[/C][/ROW]
[ROW][C]R-squared[/C][C]0.8502[/C][/ROW]
[ROW][C]RMSE[/C][C]14.2574[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197683&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197683&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	0.9221
R-squared	0.8502
RMSE	14.2574

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	79	113.40625	-34.40625
2	58	78.875	-20.875
3	60	78.875	-18.875
4	108	100.333333333333	7.66666666666667
5	49	45.5	3.5
6	0	16.5833333333333	-16.5833333333333
7	121	113.40625	7.59375
8	1	2.36363636363636	-1.36363636363636
9	20	25.7608695652174	-5.76086956521739
10	43	45.5	-2.5
11	69	66.3157894736842	2.68421052631579
12	78	78.875	-0.875
13	86	66.3157894736842	19.6842105263158
14	44	45.5	-1.5
15	104	100.333333333333	3.66666666666667
16	63	66.3157894736842	-3.31578947368421
17	158	113.40625	44.59375
18	102	113.40625	-11.40625
19	77	100.333333333333	-23.3333333333333
20	82	78.875	3.125
21	115	113.40625	1.59375
22	101	78.875	22.125
23	80	100.333333333333	-20.3333333333333
24	50	45.5	4.5
25	83	78.875	4.125
26	123	100.333333333333	22.6666666666667
27	73	78.875	-5.875
28	81	100.333333333333	-19.3333333333333
29	105	78.875	26.125
30	47	45.5	1.5
31	105	78.875	26.125
32	94	78.875	15.125
33	44	78.875	-34.875
34	114	78.875	35.125
35	38	25.7608695652174	12.2391304347826
36	107	113.40625	-6.40625
37	30	25.7608695652174	4.23913043478261
38	71	66.3157894736842	4.68421052631579
39	84	100.333333333333	-16.3333333333333
40	0	2.36363636363636	-2.36363636363636
41	59	66.3157894736842	-7.31578947368421
42	33	34.609756097561	-1.60975609756098
43	42	34.609756097561	7.39024390243902
44	96	100.333333333333	-4.33333333333333
45	106	100.333333333333	5.66666666666667
46	56	45.5	10.5
47	57	66.3157894736842	-9.31578947368421
48	59	45.5	13.5
49	39	45.5	-6.5
50	34	34.609756097561	-0.609756097560975
51	76	66.3157894736842	9.68421052631579
52	20	25.7608695652174	-5.76086956521739
53	91	78.875	12.125
54	115	113.40625	1.59375
55	85	78.875	6.125
56	76	78.875	-2.875
57	8	10.1363636363636	-2.13636363636364
58	79	113.40625	-34.40625
59	21	25.7608695652174	-4.76086956521739
60	30	25.7608695652174	4.23913043478261
61	76	100.333333333333	-24.3333333333333
62	101	113.40625	-12.40625
63	94	100.333333333333	-6.33333333333333
64	27	25.7608695652174	1.23913043478261
65	92	113.40625	-21.40625
66	123	113.40625	9.59375
67	75	66.3157894736842	8.68421052631579
68	128	113.40625	14.59375
69	105	113.40625	-8.40625
70	55	66.3157894736842	-11.3157894736842
71	56	78.875	-22.875
72	41	78.875	-37.875
73	72	78.875	-6.875
74	67	78.875	-11.875
75	75	78.875	-3.875
76	114	113.40625	0.59375
77	118	45.5	72.5
78	77	78.875	-1.875
79	22	25.7608695652174	-3.76086956521739
80	66	66.3157894736842	-0.315789473684205
81	69	78.875	-9.875
82	105	78.875	26.125
83	116	100.333333333333	15.6666666666667
84	88	78.875	9.125
85	73	66.3157894736842	6.68421052631579
86	99	78.875	20.125
87	62	45.5	16.5
88	53	34.609756097561	18.390243902439
89	118	100.333333333333	17.6666666666667
90	30	34.609756097561	-4.60975609756098
91	100	113.40625	-13.40625
92	49	45.5	3.5
93	24	25.7608695652174	-1.76086956521739
94	67	78.875	-11.875
95	46	34.609756097561	11.390243902439
96	57	66.3157894736842	-9.31578947368421
97	75	66.3157894736842	8.68421052631579
98	135	113.40625	21.59375
99	68	66.3157894736842	1.68421052631579
100	124	113.40625	10.59375
101	33	45.5	-12.5
102	98	100.333333333333	-2.33333333333333
103	58	78.875	-20.875
104	68	78.875	-10.875
105	81	113.40625	-32.40625
106	131	113.40625	17.59375
107	110	100.333333333333	9.66666666666667
108	37	34.609756097561	2.39024390243902
109	130	113.40625	16.59375
110	93	78.875	14.125
111	118	113.40625	4.59375
112	39	34.609756097561	4.39024390243902
113	13	16.5833333333333	-3.58333333333333
114	74	66.3157894736842	7.68421052631579
115	81	113.40625	-32.40625
116	109	100.333333333333	8.66666666666667
117	151	100.333333333333	50.6666666666667
118	51	66.3157894736842	-15.3157894736842
119	28	45.5	-17.5
120	40	34.609756097561	5.39024390243902
121	56	45.5	10.5
122	27	25.7608695652174	1.23913043478261
123	37	45.5	-8.5
124	83	45.5	37.5
125	54	78.875	-24.875
126	27	25.7608695652174	1.23913043478261
127	28	25.7608695652174	2.23913043478261
128	59	45.5	13.5
129	133	78.875	54.125
130	12	10.1363636363636	1.86363636363636
131	0	2.36363636363636	-2.36363636363636
132	106	78.875	27.125
133	23	16.5833333333333	6.41666666666667
134	44	34.609756097561	9.39024390243902
135	71	78.875	-7.875
136	116	113.40625	2.59375
137	4	2.36363636363636	1.63636363636364
138	62	66.3157894736842	-4.31578947368421
139	12	16.5833333333333	-4.58333333333333
140	18	16.5833333333333	1.41666666666667
141	14	26.5714285714286	-12.5714285714286
142	60	45.5	14.5
143	7	10.1363636363636	-3.13636363636364
144	98	100.333333333333	-2.33333333333333
145	64	66.3157894736842	-2.31578947368421
146	29	25.7608695652174	3.23913043478261
147	32	34.609756097561	-2.60975609756098
148	25	45.5	-20.5
149	16	10.1363636363636	5.86363636363636
150	48	45.5	2.5
151	100	100.333333333333	-0.333333333333329
152	46	78.875	-32.875
153	45	34.609756097561	10.390243902439
154	129	113.40625	15.59375
155	130	113.40625	16.59375
156	136	113.40625	22.59375
157	59	66.3157894736842	-7.31578947368421
158	25	34.609756097561	-9.60975609756098
159	32	34.609756097561	-2.60975609756098
160	63	78.875	-15.875
161	95	113.40625	-18.40625
162	14	10.1363636363636	3.86363636363636
163	36	45.5	-9.5
164	113	113.40625	-0.40625
165	47	45.5	1.5
166	92	78.875	13.125
167	70	78.875	-8.875
168	19	45.5	-26.5
169	50	45.5	4.5
170	41	34.609756097561	6.39024390243902
171	91	100.333333333333	-9.33333333333333
172	111	113.40625	-2.40625
173	41	26.5714285714286	14.4285714285714
174	120	113.40625	6.59375
175	135	78.875	56.125
176	27	34.609756097561	-7.60975609756098
177	87	100.333333333333	-13.3333333333333
178	25	25.7608695652174	-0.760869565217391
179	131	113.40625	17.59375
180	45	25.7608695652174	19.2391304347826
181	29	25.7608695652174	3.23913043478261
182	58	26.5714285714286	31.4285714285714
183	4	2.36363636363636	1.63636363636364
184	47	78.875	-31.875
185	109	113.40625	-4.40625
186	7	10.1363636363636	-3.13636363636364
187	12	10.1363636363636	1.86363636363636
188	0	2.36363636363636	-2.36363636363636
189	37	45.5	-8.5
190	37	25.7608695652174	11.2391304347826
191	46	45.5	0.5
192	15	26.5714285714286	-11.5714285714286
193	42	34.609756097561	7.39024390243902
194	7	10.1363636363636	-3.13636363636364
195	54	45.5	8.5
196	54	78.875	-24.875
197	14	25.7608695652174	-11.7608695652174
198	16	45.5	-29.5
199	33	45.5	-12.5
200	32	45.5	-13.5
201	21	34.609756097561	-13.609756097561
202	15	16.5833333333333	-1.58333333333333
203	38	34.609756097561	3.39024390243902
204	22	25.7608695652174	-3.76086956521739
205	28	34.609756097561	-6.60975609756098
206	10	10.1363636363636	-0.136363636363637
207	31	25.7608695652174	5.23913043478261
208	32	34.609756097561	-2.60975609756098
209	32	34.609756097561	-2.60975609756098
210	43	34.609756097561	8.39024390243902
211	27	25.7608695652174	1.23913043478261
212	37	34.609756097561	2.39024390243902
213	20	16.5833333333333	3.41666666666667
214	32	25.7608695652174	6.23913043478261
215	0	10.1363636363636	-10.1363636363636
216	5	10.1363636363636	-5.13636363636364
217	26	25.7608695652174	0.239130434782609
218	10	25.7608695652174	-15.7608695652174
219	27	25.7608695652174	1.23913043478261
220	11	10.1363636363636	0.863636363636363
221	29	25.7608695652174	3.23913043478261
222	25	34.609756097561	-9.60975609756098
223	55	45.5	9.5
224	23	25.7608695652174	-2.76086956521739
225	5	10.1363636363636	-5.13636363636364
226	43	45.5	-2.5
227	23	25.7608695652174	-2.76086956521739
228	34	45.5	-11.5
229	36	34.609756097561	1.39024390243902
230	35	25.7608695652174	9.23913043478261
231	0	2.36363636363636	-2.36363636363636
232	37	34.609756097561	2.39024390243902
233	28	34.609756097561	-6.60975609756098
234	16	10.1363636363636	5.86363636363636
235	26	34.609756097561	-8.60975609756098
236	38	25.7608695652174	12.2391304347826
237	23	25.7608695652174	-2.76086956521739
238	22	25.7608695652174	-3.76086956521739
239	30	25.7608695652174	4.23913043478261
240	16	16.5833333333333	-0.583333333333332
241	18	25.7608695652174	-7.76086956521739
242	28	45.5	-17.5
243	32	25.7608695652174	6.23913043478261
244	21	16.5833333333333	4.41666666666667
245	23	34.609756097561	-11.609756097561
246	29	34.609756097561	-5.60975609756098
247	50	45.5	4.5
248	12	26.5714285714286	-14.5714285714286
249	21	25.7608695652174	-4.76086956521739
250	18	16.5833333333333	1.41666666666667
251	27	34.609756097561	-7.60975609756098
252	41	45.5	-4.5
253	13	10.1363636363636	2.86363636363636
254	12	25.7608695652174	-13.7608695652174
255	21	25.7608695652174	-4.76086956521739
256	8	10.1363636363636	-2.13636363636364
257	26	16.5833333333333	9.41666666666667
258	27	26.5714285714286	0.428571428571427
259	13	10.1363636363636	2.86363636363636
260	16	10.1363636363636	5.86363636363636
261	2	2.36363636363636	-0.363636363636364
262	42	34.609756097561	7.39024390243902
263	5	2.36363636363636	2.63636363636364
264	37	34.609756097561	2.39024390243902
265	17	16.5833333333333	0.416666666666668
266	38	34.609756097561	3.39024390243902
267	37	34.609756097561	2.39024390243902
268	29	34.609756097561	-5.60975609756098
269	32	34.609756097561	-2.60975609756098
270	35	45.5	-10.5
271	17	34.609756097561	-17.609756097561
272	20	25.7608695652174	-5.76086956521739
273	7	2.36363636363636	4.63636363636364
274	46	34.609756097561	11.390243902439
275	24	25.7608695652174	-1.76086956521739
276	40	25.7608695652174	14.2391304347826
277	3	2.36363636363636	0.636363636363636
278	10	10.1363636363636	-0.136363636363637
279	37	34.609756097561	2.39024390243902
280	17	25.7608695652174	-8.76086956521739
281	28	25.7608695652174	2.23913043478261
282	19	26.5714285714286	-7.57142857142857
283	29	25.7608695652174	3.23913043478261
284	8	10.1363636363636	-2.13636363636364
285	10	10.1363636363636	-0.136363636363637
286	15	25.7608695652174	-10.7608695652174
287	15	10.1363636363636	4.86363636363636
288	28	45.5	-17.5
289	17	25.7608695652174	-8.76086956521739

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 79 & 113.40625 & -34.40625 \tabularnewline
2 & 58 & 78.875 & -20.875 \tabularnewline
3 & 60 & 78.875 & -18.875 \tabularnewline
4 & 108 & 100.333333333333 & 7.66666666666667 \tabularnewline
5 & 49 & 45.5 & 3.5 \tabularnewline
6 & 0 & 16.5833333333333 & -16.5833333333333 \tabularnewline
7 & 121 & 113.40625 & 7.59375 \tabularnewline
8 & 1 & 2.36363636363636 & -1.36363636363636 \tabularnewline
9 & 20 & 25.7608695652174 & -5.76086956521739 \tabularnewline
10 & 43 & 45.5 & -2.5 \tabularnewline
11 & 69 & 66.3157894736842 & 2.68421052631579 \tabularnewline
12 & 78 & 78.875 & -0.875 \tabularnewline
13 & 86 & 66.3157894736842 & 19.6842105263158 \tabularnewline
14 & 44 & 45.5 & -1.5 \tabularnewline
15 & 104 & 100.333333333333 & 3.66666666666667 \tabularnewline
16 & 63 & 66.3157894736842 & -3.31578947368421 \tabularnewline
17 & 158 & 113.40625 & 44.59375 \tabularnewline
18 & 102 & 113.40625 & -11.40625 \tabularnewline
19 & 77 & 100.333333333333 & -23.3333333333333 \tabularnewline
20 & 82 & 78.875 & 3.125 \tabularnewline
21 & 115 & 113.40625 & 1.59375 \tabularnewline
22 & 101 & 78.875 & 22.125 \tabularnewline
23 & 80 & 100.333333333333 & -20.3333333333333 \tabularnewline
24 & 50 & 45.5 & 4.5 \tabularnewline
25 & 83 & 78.875 & 4.125 \tabularnewline
26 & 123 & 100.333333333333 & 22.6666666666667 \tabularnewline
27 & 73 & 78.875 & -5.875 \tabularnewline
28 & 81 & 100.333333333333 & -19.3333333333333 \tabularnewline
29 & 105 & 78.875 & 26.125 \tabularnewline
30 & 47 & 45.5 & 1.5 \tabularnewline
31 & 105 & 78.875 & 26.125 \tabularnewline
32 & 94 & 78.875 & 15.125 \tabularnewline
33 & 44 & 78.875 & -34.875 \tabularnewline
34 & 114 & 78.875 & 35.125 \tabularnewline
35 & 38 & 25.7608695652174 & 12.2391304347826 \tabularnewline
36 & 107 & 113.40625 & -6.40625 \tabularnewline
37 & 30 & 25.7608695652174 & 4.23913043478261 \tabularnewline
38 & 71 & 66.3157894736842 & 4.68421052631579 \tabularnewline
39 & 84 & 100.333333333333 & -16.3333333333333 \tabularnewline
40 & 0 & 2.36363636363636 & -2.36363636363636 \tabularnewline
41 & 59 & 66.3157894736842 & -7.31578947368421 \tabularnewline
42 & 33 & 34.609756097561 & -1.60975609756098 \tabularnewline
43 & 42 & 34.609756097561 & 7.39024390243902 \tabularnewline
44 & 96 & 100.333333333333 & -4.33333333333333 \tabularnewline
45 & 106 & 100.333333333333 & 5.66666666666667 \tabularnewline
46 & 56 & 45.5 & 10.5 \tabularnewline
47 & 57 & 66.3157894736842 & -9.31578947368421 \tabularnewline
48 & 59 & 45.5 & 13.5 \tabularnewline
49 & 39 & 45.5 & -6.5 \tabularnewline
50 & 34 & 34.609756097561 & -0.609756097560975 \tabularnewline
51 & 76 & 66.3157894736842 & 9.68421052631579 \tabularnewline
52 & 20 & 25.7608695652174 & -5.76086956521739 \tabularnewline
53 & 91 & 78.875 & 12.125 \tabularnewline
54 & 115 & 113.40625 & 1.59375 \tabularnewline
55 & 85 & 78.875 & 6.125 \tabularnewline
56 & 76 & 78.875 & -2.875 \tabularnewline
57 & 8 & 10.1363636363636 & -2.13636363636364 \tabularnewline
58 & 79 & 113.40625 & -34.40625 \tabularnewline
59 & 21 & 25.7608695652174 & -4.76086956521739 \tabularnewline
60 & 30 & 25.7608695652174 & 4.23913043478261 \tabularnewline
61 & 76 & 100.333333333333 & -24.3333333333333 \tabularnewline
62 & 101 & 113.40625 & -12.40625 \tabularnewline
63 & 94 & 100.333333333333 & -6.33333333333333 \tabularnewline
64 & 27 & 25.7608695652174 & 1.23913043478261 \tabularnewline
65 & 92 & 113.40625 & -21.40625 \tabularnewline
66 & 123 & 113.40625 & 9.59375 \tabularnewline
67 & 75 & 66.3157894736842 & 8.68421052631579 \tabularnewline
68 & 128 & 113.40625 & 14.59375 \tabularnewline
69 & 105 & 113.40625 & -8.40625 \tabularnewline
70 & 55 & 66.3157894736842 & -11.3157894736842 \tabularnewline
71 & 56 & 78.875 & -22.875 \tabularnewline
72 & 41 & 78.875 & -37.875 \tabularnewline
73 & 72 & 78.875 & -6.875 \tabularnewline
74 & 67 & 78.875 & -11.875 \tabularnewline
75 & 75 & 78.875 & -3.875 \tabularnewline
76 & 114 & 113.40625 & 0.59375 \tabularnewline
77 & 118 & 45.5 & 72.5 \tabularnewline
78 & 77 & 78.875 & -1.875 \tabularnewline
79 & 22 & 25.7608695652174 & -3.76086956521739 \tabularnewline
80 & 66 & 66.3157894736842 & -0.315789473684205 \tabularnewline
81 & 69 & 78.875 & -9.875 \tabularnewline
82 & 105 & 78.875 & 26.125 \tabularnewline
83 & 116 & 100.333333333333 & 15.6666666666667 \tabularnewline
84 & 88 & 78.875 & 9.125 \tabularnewline
85 & 73 & 66.3157894736842 & 6.68421052631579 \tabularnewline
86 & 99 & 78.875 & 20.125 \tabularnewline
87 & 62 & 45.5 & 16.5 \tabularnewline
88 & 53 & 34.609756097561 & 18.390243902439 \tabularnewline
89 & 118 & 100.333333333333 & 17.6666666666667 \tabularnewline
90 & 30 & 34.609756097561 & -4.60975609756098 \tabularnewline
91 & 100 & 113.40625 & -13.40625 \tabularnewline
92 & 49 & 45.5 & 3.5 \tabularnewline
93 & 24 & 25.7608695652174 & -1.76086956521739 \tabularnewline
94 & 67 & 78.875 & -11.875 \tabularnewline
95 & 46 & 34.609756097561 & 11.390243902439 \tabularnewline
96 & 57 & 66.3157894736842 & -9.31578947368421 \tabularnewline
97 & 75 & 66.3157894736842 & 8.68421052631579 \tabularnewline
98 & 135 & 113.40625 & 21.59375 \tabularnewline
99 & 68 & 66.3157894736842 & 1.68421052631579 \tabularnewline
100 & 124 & 113.40625 & 10.59375 \tabularnewline
101 & 33 & 45.5 & -12.5 \tabularnewline
102 & 98 & 100.333333333333 & -2.33333333333333 \tabularnewline
103 & 58 & 78.875 & -20.875 \tabularnewline
104 & 68 & 78.875 & -10.875 \tabularnewline
105 & 81 & 113.40625 & -32.40625 \tabularnewline
106 & 131 & 113.40625 & 17.59375 \tabularnewline
107 & 110 & 100.333333333333 & 9.66666666666667 \tabularnewline
108 & 37 & 34.609756097561 & 2.39024390243902 \tabularnewline
109 & 130 & 113.40625 & 16.59375 \tabularnewline
110 & 93 & 78.875 & 14.125 \tabularnewline
111 & 118 & 113.40625 & 4.59375 \tabularnewline
112 & 39 & 34.609756097561 & 4.39024390243902 \tabularnewline
113 & 13 & 16.5833333333333 & -3.58333333333333 \tabularnewline
114 & 74 & 66.3157894736842 & 7.68421052631579 \tabularnewline
115 & 81 & 113.40625 & -32.40625 \tabularnewline
116 & 109 & 100.333333333333 & 8.66666666666667 \tabularnewline
117 & 151 & 100.333333333333 & 50.6666666666667 \tabularnewline
118 & 51 & 66.3157894736842 & -15.3157894736842 \tabularnewline
119 & 28 & 45.5 & -17.5 \tabularnewline
120 & 40 & 34.609756097561 & 5.39024390243902 \tabularnewline
121 & 56 & 45.5 & 10.5 \tabularnewline
122 & 27 & 25.7608695652174 & 1.23913043478261 \tabularnewline
123 & 37 & 45.5 & -8.5 \tabularnewline
124 & 83 & 45.5 & 37.5 \tabularnewline
125 & 54 & 78.875 & -24.875 \tabularnewline
126 & 27 & 25.7608695652174 & 1.23913043478261 \tabularnewline
127 & 28 & 25.7608695652174 & 2.23913043478261 \tabularnewline
128 & 59 & 45.5 & 13.5 \tabularnewline
129 & 133 & 78.875 & 54.125 \tabularnewline
130 & 12 & 10.1363636363636 & 1.86363636363636 \tabularnewline
131 & 0 & 2.36363636363636 & -2.36363636363636 \tabularnewline
132 & 106 & 78.875 & 27.125 \tabularnewline
133 & 23 & 16.5833333333333 & 6.41666666666667 \tabularnewline
134 & 44 & 34.609756097561 & 9.39024390243902 \tabularnewline
135 & 71 & 78.875 & -7.875 \tabularnewline
136 & 116 & 113.40625 & 2.59375 \tabularnewline
137 & 4 & 2.36363636363636 & 1.63636363636364 \tabularnewline
138 & 62 & 66.3157894736842 & -4.31578947368421 \tabularnewline
139 & 12 & 16.5833333333333 & -4.58333333333333 \tabularnewline
140 & 18 & 16.5833333333333 & 1.41666666666667 \tabularnewline
141 & 14 & 26.5714285714286 & -12.5714285714286 \tabularnewline
142 & 60 & 45.5 & 14.5 \tabularnewline
143 & 7 & 10.1363636363636 & -3.13636363636364 \tabularnewline
144 & 98 & 100.333333333333 & -2.33333333333333 \tabularnewline
145 & 64 & 66.3157894736842 & -2.31578947368421 \tabularnewline
146 & 29 & 25.7608695652174 & 3.23913043478261 \tabularnewline
147 & 32 & 34.609756097561 & -2.60975609756098 \tabularnewline
148 & 25 & 45.5 & -20.5 \tabularnewline
149 & 16 & 10.1363636363636 & 5.86363636363636 \tabularnewline
150 & 48 & 45.5 & 2.5 \tabularnewline
151 & 100 & 100.333333333333 & -0.333333333333329 \tabularnewline
152 & 46 & 78.875 & -32.875 \tabularnewline
153 & 45 & 34.609756097561 & 10.390243902439 \tabularnewline
154 & 129 & 113.40625 & 15.59375 \tabularnewline
155 & 130 & 113.40625 & 16.59375 \tabularnewline
156 & 136 & 113.40625 & 22.59375 \tabularnewline
157 & 59 & 66.3157894736842 & -7.31578947368421 \tabularnewline
158 & 25 & 34.609756097561 & -9.60975609756098 \tabularnewline
159 & 32 & 34.609756097561 & -2.60975609756098 \tabularnewline
160 & 63 & 78.875 & -15.875 \tabularnewline
161 & 95 & 113.40625 & -18.40625 \tabularnewline
162 & 14 & 10.1363636363636 & 3.86363636363636 \tabularnewline
163 & 36 & 45.5 & -9.5 \tabularnewline
164 & 113 & 113.40625 & -0.40625 \tabularnewline
165 & 47 & 45.5 & 1.5 \tabularnewline
166 & 92 & 78.875 & 13.125 \tabularnewline
167 & 70 & 78.875 & -8.875 \tabularnewline
168 & 19 & 45.5 & -26.5 \tabularnewline
169 & 50 & 45.5 & 4.5 \tabularnewline
170 & 41 & 34.609756097561 & 6.39024390243902 \tabularnewline
171 & 91 & 100.333333333333 & -9.33333333333333 \tabularnewline
172 & 111 & 113.40625 & -2.40625 \tabularnewline
173 & 41 & 26.5714285714286 & 14.4285714285714 \tabularnewline
174 & 120 & 113.40625 & 6.59375 \tabularnewline
175 & 135 & 78.875 & 56.125 \tabularnewline
176 & 27 & 34.609756097561 & -7.60975609756098 \tabularnewline
177 & 87 & 100.333333333333 & -13.3333333333333 \tabularnewline
178 & 25 & 25.7608695652174 & -0.760869565217391 \tabularnewline
179 & 131 & 113.40625 & 17.59375 \tabularnewline
180 & 45 & 25.7608695652174 & 19.2391304347826 \tabularnewline
181 & 29 & 25.7608695652174 & 3.23913043478261 \tabularnewline
182 & 58 & 26.5714285714286 & 31.4285714285714 \tabularnewline
183 & 4 & 2.36363636363636 & 1.63636363636364 \tabularnewline
184 & 47 & 78.875 & -31.875 \tabularnewline
185 & 109 & 113.40625 & -4.40625 \tabularnewline
186 & 7 & 10.1363636363636 & -3.13636363636364 \tabularnewline
187 & 12 & 10.1363636363636 & 1.86363636363636 \tabularnewline
188 & 0 & 2.36363636363636 & -2.36363636363636 \tabularnewline
189 & 37 & 45.5 & -8.5 \tabularnewline
190 & 37 & 25.7608695652174 & 11.2391304347826 \tabularnewline
191 & 46 & 45.5 & 0.5 \tabularnewline
192 & 15 & 26.5714285714286 & -11.5714285714286 \tabularnewline
193 & 42 & 34.609756097561 & 7.39024390243902 \tabularnewline
194 & 7 & 10.1363636363636 & -3.13636363636364 \tabularnewline
195 & 54 & 45.5 & 8.5 \tabularnewline
196 & 54 & 78.875 & -24.875 \tabularnewline
197 & 14 & 25.7608695652174 & -11.7608695652174 \tabularnewline
198 & 16 & 45.5 & -29.5 \tabularnewline
199 & 33 & 45.5 & -12.5 \tabularnewline
200 & 32 & 45.5 & -13.5 \tabularnewline
201 & 21 & 34.609756097561 & -13.609756097561 \tabularnewline
202 & 15 & 16.5833333333333 & -1.58333333333333 \tabularnewline
203 & 38 & 34.609756097561 & 3.39024390243902 \tabularnewline
204 & 22 & 25.7608695652174 & -3.76086956521739 \tabularnewline
205 & 28 & 34.609756097561 & -6.60975609756098 \tabularnewline
206 & 10 & 10.1363636363636 & -0.136363636363637 \tabularnewline
207 & 31 & 25.7608695652174 & 5.23913043478261 \tabularnewline
208 & 32 & 34.609756097561 & -2.60975609756098 \tabularnewline
209 & 32 & 34.609756097561 & -2.60975609756098 \tabularnewline
210 & 43 & 34.609756097561 & 8.39024390243902 \tabularnewline
211 & 27 & 25.7608695652174 & 1.23913043478261 \tabularnewline
212 & 37 & 34.609756097561 & 2.39024390243902 \tabularnewline
213 & 20 & 16.5833333333333 & 3.41666666666667 \tabularnewline
214 & 32 & 25.7608695652174 & 6.23913043478261 \tabularnewline
215 & 0 & 10.1363636363636 & -10.1363636363636 \tabularnewline
216 & 5 & 10.1363636363636 & -5.13636363636364 \tabularnewline
217 & 26 & 25.7608695652174 & 0.239130434782609 \tabularnewline
218 & 10 & 25.7608695652174 & -15.7608695652174 \tabularnewline
219 & 27 & 25.7608695652174 & 1.23913043478261 \tabularnewline
220 & 11 & 10.1363636363636 & 0.863636363636363 \tabularnewline
221 & 29 & 25.7608695652174 & 3.23913043478261 \tabularnewline
222 & 25 & 34.609756097561 & -9.60975609756098 \tabularnewline
223 & 55 & 45.5 & 9.5 \tabularnewline
224 & 23 & 25.7608695652174 & -2.76086956521739 \tabularnewline
225 & 5 & 10.1363636363636 & -5.13636363636364 \tabularnewline
226 & 43 & 45.5 & -2.5 \tabularnewline
227 & 23 & 25.7608695652174 & -2.76086956521739 \tabularnewline
228 & 34 & 45.5 & -11.5 \tabularnewline
229 & 36 & 34.609756097561 & 1.39024390243902 \tabularnewline
230 & 35 & 25.7608695652174 & 9.23913043478261 \tabularnewline
231 & 0 & 2.36363636363636 & -2.36363636363636 \tabularnewline
232 & 37 & 34.609756097561 & 2.39024390243902 \tabularnewline
233 & 28 & 34.609756097561 & -6.60975609756098 \tabularnewline
234 & 16 & 10.1363636363636 & 5.86363636363636 \tabularnewline
235 & 26 & 34.609756097561 & -8.60975609756098 \tabularnewline
236 & 38 & 25.7608695652174 & 12.2391304347826 \tabularnewline
237 & 23 & 25.7608695652174 & -2.76086956521739 \tabularnewline
238 & 22 & 25.7608695652174 & -3.76086956521739 \tabularnewline
239 & 30 & 25.7608695652174 & 4.23913043478261 \tabularnewline
240 & 16 & 16.5833333333333 & -0.583333333333332 \tabularnewline
241 & 18 & 25.7608695652174 & -7.76086956521739 \tabularnewline
242 & 28 & 45.5 & -17.5 \tabularnewline
243 & 32 & 25.7608695652174 & 6.23913043478261 \tabularnewline
244 & 21 & 16.5833333333333 & 4.41666666666667 \tabularnewline
245 & 23 & 34.609756097561 & -11.609756097561 \tabularnewline
246 & 29 & 34.609756097561 & -5.60975609756098 \tabularnewline
247 & 50 & 45.5 & 4.5 \tabularnewline
248 & 12 & 26.5714285714286 & -14.5714285714286 \tabularnewline
249 & 21 & 25.7608695652174 & -4.76086956521739 \tabularnewline
250 & 18 & 16.5833333333333 & 1.41666666666667 \tabularnewline
251 & 27 & 34.609756097561 & -7.60975609756098 \tabularnewline
252 & 41 & 45.5 & -4.5 \tabularnewline
253 & 13 & 10.1363636363636 & 2.86363636363636 \tabularnewline
254 & 12 & 25.7608695652174 & -13.7608695652174 \tabularnewline
255 & 21 & 25.7608695652174 & -4.76086956521739 \tabularnewline
256 & 8 & 10.1363636363636 & -2.13636363636364 \tabularnewline
257 & 26 & 16.5833333333333 & 9.41666666666667 \tabularnewline
258 & 27 & 26.5714285714286 & 0.428571428571427 \tabularnewline
259 & 13 & 10.1363636363636 & 2.86363636363636 \tabularnewline
260 & 16 & 10.1363636363636 & 5.86363636363636 \tabularnewline
261 & 2 & 2.36363636363636 & -0.363636363636364 \tabularnewline
262 & 42 & 34.609756097561 & 7.39024390243902 \tabularnewline
263 & 5 & 2.36363636363636 & 2.63636363636364 \tabularnewline
264 & 37 & 34.609756097561 & 2.39024390243902 \tabularnewline
265 & 17 & 16.5833333333333 & 0.416666666666668 \tabularnewline
266 & 38 & 34.609756097561 & 3.39024390243902 \tabularnewline
267 & 37 & 34.609756097561 & 2.39024390243902 \tabularnewline
268 & 29 & 34.609756097561 & -5.60975609756098 \tabularnewline
269 & 32 & 34.609756097561 & -2.60975609756098 \tabularnewline
270 & 35 & 45.5 & -10.5 \tabularnewline
271 & 17 & 34.609756097561 & -17.609756097561 \tabularnewline
272 & 20 & 25.7608695652174 & -5.76086956521739 \tabularnewline
273 & 7 & 2.36363636363636 & 4.63636363636364 \tabularnewline
274 & 46 & 34.609756097561 & 11.390243902439 \tabularnewline
275 & 24 & 25.7608695652174 & -1.76086956521739 \tabularnewline
276 & 40 & 25.7608695652174 & 14.2391304347826 \tabularnewline
277 & 3 & 2.36363636363636 & 0.636363636363636 \tabularnewline
278 & 10 & 10.1363636363636 & -0.136363636363637 \tabularnewline
279 & 37 & 34.609756097561 & 2.39024390243902 \tabularnewline
280 & 17 & 25.7608695652174 & -8.76086956521739 \tabularnewline
281 & 28 & 25.7608695652174 & 2.23913043478261 \tabularnewline
282 & 19 & 26.5714285714286 & -7.57142857142857 \tabularnewline
283 & 29 & 25.7608695652174 & 3.23913043478261 \tabularnewline
284 & 8 & 10.1363636363636 & -2.13636363636364 \tabularnewline
285 & 10 & 10.1363636363636 & -0.136363636363637 \tabularnewline
286 & 15 & 25.7608695652174 & -10.7608695652174 \tabularnewline
287 & 15 & 10.1363636363636 & 4.86363636363636 \tabularnewline
288 & 28 & 45.5 & -17.5 \tabularnewline
289 & 17 & 25.7608695652174 & -8.76086956521739 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197683&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]79[/C][C]113.40625[/C][C]-34.40625[/C][/ROW]
[ROW][C]2[/C][C]58[/C][C]78.875[/C][C]-20.875[/C][/ROW]
[ROW][C]3[/C][C]60[/C][C]78.875[/C][C]-18.875[/C][/ROW]
[ROW][C]4[/C][C]108[/C][C]100.333333333333[/C][C]7.66666666666667[/C][/ROW]
[ROW][C]5[/C][C]49[/C][C]45.5[/C][C]3.5[/C][/ROW]
[ROW][C]6[/C][C]0[/C][C]16.5833333333333[/C][C]-16.5833333333333[/C][/ROW]
[ROW][C]7[/C][C]121[/C][C]113.40625[/C][C]7.59375[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]2.36363636363636[/C][C]-1.36363636363636[/C][/ROW]
[ROW][C]9[/C][C]20[/C][C]25.7608695652174[/C][C]-5.76086956521739[/C][/ROW]
[ROW][C]10[/C][C]43[/C][C]45.5[/C][C]-2.5[/C][/ROW]
[ROW][C]11[/C][C]69[/C][C]66.3157894736842[/C][C]2.68421052631579[/C][/ROW]
[ROW][C]12[/C][C]78[/C][C]78.875[/C][C]-0.875[/C][/ROW]
[ROW][C]13[/C][C]86[/C][C]66.3157894736842[/C][C]19.6842105263158[/C][/ROW]
[ROW][C]14[/C][C]44[/C][C]45.5[/C][C]-1.5[/C][/ROW]
[ROW][C]15[/C][C]104[/C][C]100.333333333333[/C][C]3.66666666666667[/C][/ROW]
[ROW][C]16[/C][C]63[/C][C]66.3157894736842[/C][C]-3.31578947368421[/C][/ROW]
[ROW][C]17[/C][C]158[/C][C]113.40625[/C][C]44.59375[/C][/ROW]
[ROW][C]18[/C][C]102[/C][C]113.40625[/C][C]-11.40625[/C][/ROW]
[ROW][C]19[/C][C]77[/C][C]100.333333333333[/C][C]-23.3333333333333[/C][/ROW]
[ROW][C]20[/C][C]82[/C][C]78.875[/C][C]3.125[/C][/ROW]
[ROW][C]21[/C][C]115[/C][C]113.40625[/C][C]1.59375[/C][/ROW]
[ROW][C]22[/C][C]101[/C][C]78.875[/C][C]22.125[/C][/ROW]
[ROW][C]23[/C][C]80[/C][C]100.333333333333[/C][C]-20.3333333333333[/C][/ROW]
[ROW][C]24[/C][C]50[/C][C]45.5[/C][C]4.5[/C][/ROW]
[ROW][C]25[/C][C]83[/C][C]78.875[/C][C]4.125[/C][/ROW]
[ROW][C]26[/C][C]123[/C][C]100.333333333333[/C][C]22.6666666666667[/C][/ROW]
[ROW][C]27[/C][C]73[/C][C]78.875[/C][C]-5.875[/C][/ROW]
[ROW][C]28[/C][C]81[/C][C]100.333333333333[/C][C]-19.3333333333333[/C][/ROW]
[ROW][C]29[/C][C]105[/C][C]78.875[/C][C]26.125[/C][/ROW]
[ROW][C]30[/C][C]47[/C][C]45.5[/C][C]1.5[/C][/ROW]
[ROW][C]31[/C][C]105[/C][C]78.875[/C][C]26.125[/C][/ROW]
[ROW][C]32[/C][C]94[/C][C]78.875[/C][C]15.125[/C][/ROW]
[ROW][C]33[/C][C]44[/C][C]78.875[/C][C]-34.875[/C][/ROW]
[ROW][C]34[/C][C]114[/C][C]78.875[/C][C]35.125[/C][/ROW]
[ROW][C]35[/C][C]38[/C][C]25.7608695652174[/C][C]12.2391304347826[/C][/ROW]
[ROW][C]36[/C][C]107[/C][C]113.40625[/C][C]-6.40625[/C][/ROW]
[ROW][C]37[/C][C]30[/C][C]25.7608695652174[/C][C]4.23913043478261[/C][/ROW]
[ROW][C]38[/C][C]71[/C][C]66.3157894736842[/C][C]4.68421052631579[/C][/ROW]
[ROW][C]39[/C][C]84[/C][C]100.333333333333[/C][C]-16.3333333333333[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]2.36363636363636[/C][C]-2.36363636363636[/C][/ROW]
[ROW][C]41[/C][C]59[/C][C]66.3157894736842[/C][C]-7.31578947368421[/C][/ROW]
[ROW][C]42[/C][C]33[/C][C]34.609756097561[/C][C]-1.60975609756098[/C][/ROW]
[ROW][C]43[/C][C]42[/C][C]34.609756097561[/C][C]7.39024390243902[/C][/ROW]
[ROW][C]44[/C][C]96[/C][C]100.333333333333[/C][C]-4.33333333333333[/C][/ROW]
[ROW][C]45[/C][C]106[/C][C]100.333333333333[/C][C]5.66666666666667[/C][/ROW]
[ROW][C]46[/C][C]56[/C][C]45.5[/C][C]10.5[/C][/ROW]
[ROW][C]47[/C][C]57[/C][C]66.3157894736842[/C][C]-9.31578947368421[/C][/ROW]
[ROW][C]48[/C][C]59[/C][C]45.5[/C][C]13.5[/C][/ROW]
[ROW][C]49[/C][C]39[/C][C]45.5[/C][C]-6.5[/C][/ROW]
[ROW][C]50[/C][C]34[/C][C]34.609756097561[/C][C]-0.609756097560975[/C][/ROW]
[ROW][C]51[/C][C]76[/C][C]66.3157894736842[/C][C]9.68421052631579[/C][/ROW]
[ROW][C]52[/C][C]20[/C][C]25.7608695652174[/C][C]-5.76086956521739[/C][/ROW]
[ROW][C]53[/C][C]91[/C][C]78.875[/C][C]12.125[/C][/ROW]
[ROW][C]54[/C][C]115[/C][C]113.40625[/C][C]1.59375[/C][/ROW]
[ROW][C]55[/C][C]85[/C][C]78.875[/C][C]6.125[/C][/ROW]
[ROW][C]56[/C][C]76[/C][C]78.875[/C][C]-2.875[/C][/ROW]
[ROW][C]57[/C][C]8[/C][C]10.1363636363636[/C][C]-2.13636363636364[/C][/ROW]
[ROW][C]58[/C][C]79[/C][C]113.40625[/C][C]-34.40625[/C][/ROW]
[ROW][C]59[/C][C]21[/C][C]25.7608695652174[/C][C]-4.76086956521739[/C][/ROW]
[ROW][C]60[/C][C]30[/C][C]25.7608695652174[/C][C]4.23913043478261[/C][/ROW]
[ROW][C]61[/C][C]76[/C][C]100.333333333333[/C][C]-24.3333333333333[/C][/ROW]
[ROW][C]62[/C][C]101[/C][C]113.40625[/C][C]-12.40625[/C][/ROW]
[ROW][C]63[/C][C]94[/C][C]100.333333333333[/C][C]-6.33333333333333[/C][/ROW]
[ROW][C]64[/C][C]27[/C][C]25.7608695652174[/C][C]1.23913043478261[/C][/ROW]
[ROW][C]65[/C][C]92[/C][C]113.40625[/C][C]-21.40625[/C][/ROW]
[ROW][C]66[/C][C]123[/C][C]113.40625[/C][C]9.59375[/C][/ROW]
[ROW][C]67[/C][C]75[/C][C]66.3157894736842[/C][C]8.68421052631579[/C][/ROW]
[ROW][C]68[/C][C]128[/C][C]113.40625[/C][C]14.59375[/C][/ROW]
[ROW][C]69[/C][C]105[/C][C]113.40625[/C][C]-8.40625[/C][/ROW]
[ROW][C]70[/C][C]55[/C][C]66.3157894736842[/C][C]-11.3157894736842[/C][/ROW]
[ROW][C]71[/C][C]56[/C][C]78.875[/C][C]-22.875[/C][/ROW]
[ROW][C]72[/C][C]41[/C][C]78.875[/C][C]-37.875[/C][/ROW]
[ROW][C]73[/C][C]72[/C][C]78.875[/C][C]-6.875[/C][/ROW]
[ROW][C]74[/C][C]67[/C][C]78.875[/C][C]-11.875[/C][/ROW]
[ROW][C]75[/C][C]75[/C][C]78.875[/C][C]-3.875[/C][/ROW]
[ROW][C]76[/C][C]114[/C][C]113.40625[/C][C]0.59375[/C][/ROW]
[ROW][C]77[/C][C]118[/C][C]45.5[/C][C]72.5[/C][/ROW]
[ROW][C]78[/C][C]77[/C][C]78.875[/C][C]-1.875[/C][/ROW]
[ROW][C]79[/C][C]22[/C][C]25.7608695652174[/C][C]-3.76086956521739[/C][/ROW]
[ROW][C]80[/C][C]66[/C][C]66.3157894736842[/C][C]-0.315789473684205[/C][/ROW]
[ROW][C]81[/C][C]69[/C][C]78.875[/C][C]-9.875[/C][/ROW]
[ROW][C]82[/C][C]105[/C][C]78.875[/C][C]26.125[/C][/ROW]
[ROW][C]83[/C][C]116[/C][C]100.333333333333[/C][C]15.6666666666667[/C][/ROW]
[ROW][C]84[/C][C]88[/C][C]78.875[/C][C]9.125[/C][/ROW]
[ROW][C]85[/C][C]73[/C][C]66.3157894736842[/C][C]6.68421052631579[/C][/ROW]
[ROW][C]86[/C][C]99[/C][C]78.875[/C][C]20.125[/C][/ROW]
[ROW][C]87[/C][C]62[/C][C]45.5[/C][C]16.5[/C][/ROW]
[ROW][C]88[/C][C]53[/C][C]34.609756097561[/C][C]18.390243902439[/C][/ROW]
[ROW][C]89[/C][C]118[/C][C]100.333333333333[/C][C]17.6666666666667[/C][/ROW]
[ROW][C]90[/C][C]30[/C][C]34.609756097561[/C][C]-4.60975609756098[/C][/ROW]
[ROW][C]91[/C][C]100[/C][C]113.40625[/C][C]-13.40625[/C][/ROW]
[ROW][C]92[/C][C]49[/C][C]45.5[/C][C]3.5[/C][/ROW]
[ROW][C]93[/C][C]24[/C][C]25.7608695652174[/C][C]-1.76086956521739[/C][/ROW]
[ROW][C]94[/C][C]67[/C][C]78.875[/C][C]-11.875[/C][/ROW]
[ROW][C]95[/C][C]46[/C][C]34.609756097561[/C][C]11.390243902439[/C][/ROW]
[ROW][C]96[/C][C]57[/C][C]66.3157894736842[/C][C]-9.31578947368421[/C][/ROW]
[ROW][C]97[/C][C]75[/C][C]66.3157894736842[/C][C]8.68421052631579[/C][/ROW]
[ROW][C]98[/C][C]135[/C][C]113.40625[/C][C]21.59375[/C][/ROW]
[ROW][C]99[/C][C]68[/C][C]66.3157894736842[/C][C]1.68421052631579[/C][/ROW]
[ROW][C]100[/C][C]124[/C][C]113.40625[/C][C]10.59375[/C][/ROW]
[ROW][C]101[/C][C]33[/C][C]45.5[/C][C]-12.5[/C][/ROW]
[ROW][C]102[/C][C]98[/C][C]100.333333333333[/C][C]-2.33333333333333[/C][/ROW]
[ROW][C]103[/C][C]58[/C][C]78.875[/C][C]-20.875[/C][/ROW]
[ROW][C]104[/C][C]68[/C][C]78.875[/C][C]-10.875[/C][/ROW]
[ROW][C]105[/C][C]81[/C][C]113.40625[/C][C]-32.40625[/C][/ROW]
[ROW][C]106[/C][C]131[/C][C]113.40625[/C][C]17.59375[/C][/ROW]
[ROW][C]107[/C][C]110[/C][C]100.333333333333[/C][C]9.66666666666667[/C][/ROW]
[ROW][C]108[/C][C]37[/C][C]34.609756097561[/C][C]2.39024390243902[/C][/ROW]
[ROW][C]109[/C][C]130[/C][C]113.40625[/C][C]16.59375[/C][/ROW]
[ROW][C]110[/C][C]93[/C][C]78.875[/C][C]14.125[/C][/ROW]
[ROW][C]111[/C][C]118[/C][C]113.40625[/C][C]4.59375[/C][/ROW]
[ROW][C]112[/C][C]39[/C][C]34.609756097561[/C][C]4.39024390243902[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]16.5833333333333[/C][C]-3.58333333333333[/C][/ROW]
[ROW][C]114[/C][C]74[/C][C]66.3157894736842[/C][C]7.68421052631579[/C][/ROW]
[ROW][C]115[/C][C]81[/C][C]113.40625[/C][C]-32.40625[/C][/ROW]
[ROW][C]116[/C][C]109[/C][C]100.333333333333[/C][C]8.66666666666667[/C][/ROW]
[ROW][C]117[/C][C]151[/C][C]100.333333333333[/C][C]50.6666666666667[/C][/ROW]
[ROW][C]118[/C][C]51[/C][C]66.3157894736842[/C][C]-15.3157894736842[/C][/ROW]
[ROW][C]119[/C][C]28[/C][C]45.5[/C][C]-17.5[/C][/ROW]
[ROW][C]120[/C][C]40[/C][C]34.609756097561[/C][C]5.39024390243902[/C][/ROW]
[ROW][C]121[/C][C]56[/C][C]45.5[/C][C]10.5[/C][/ROW]
[ROW][C]122[/C][C]27[/C][C]25.7608695652174[/C][C]1.23913043478261[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]45.5[/C][C]-8.5[/C][/ROW]
[ROW][C]124[/C][C]83[/C][C]45.5[/C][C]37.5[/C][/ROW]
[ROW][C]125[/C][C]54[/C][C]78.875[/C][C]-24.875[/C][/ROW]
[ROW][C]126[/C][C]27[/C][C]25.7608695652174[/C][C]1.23913043478261[/C][/ROW]
[ROW][C]127[/C][C]28[/C][C]25.7608695652174[/C][C]2.23913043478261[/C][/ROW]
[ROW][C]128[/C][C]59[/C][C]45.5[/C][C]13.5[/C][/ROW]
[ROW][C]129[/C][C]133[/C][C]78.875[/C][C]54.125[/C][/ROW]
[ROW][C]130[/C][C]12[/C][C]10.1363636363636[/C][C]1.86363636363636[/C][/ROW]
[ROW][C]131[/C][C]0[/C][C]2.36363636363636[/C][C]-2.36363636363636[/C][/ROW]
[ROW][C]132[/C][C]106[/C][C]78.875[/C][C]27.125[/C][/ROW]
[ROW][C]133[/C][C]23[/C][C]16.5833333333333[/C][C]6.41666666666667[/C][/ROW]
[ROW][C]134[/C][C]44[/C][C]34.609756097561[/C][C]9.39024390243902[/C][/ROW]
[ROW][C]135[/C][C]71[/C][C]78.875[/C][C]-7.875[/C][/ROW]
[ROW][C]136[/C][C]116[/C][C]113.40625[/C][C]2.59375[/C][/ROW]
[ROW][C]137[/C][C]4[/C][C]2.36363636363636[/C][C]1.63636363636364[/C][/ROW]
[ROW][C]138[/C][C]62[/C][C]66.3157894736842[/C][C]-4.31578947368421[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]16.5833333333333[/C][C]-4.58333333333333[/C][/ROW]
[ROW][C]140[/C][C]18[/C][C]16.5833333333333[/C][C]1.41666666666667[/C][/ROW]
[ROW][C]141[/C][C]14[/C][C]26.5714285714286[/C][C]-12.5714285714286[/C][/ROW]
[ROW][C]142[/C][C]60[/C][C]45.5[/C][C]14.5[/C][/ROW]
[ROW][C]143[/C][C]7[/C][C]10.1363636363636[/C][C]-3.13636363636364[/C][/ROW]
[ROW][C]144[/C][C]98[/C][C]100.333333333333[/C][C]-2.33333333333333[/C][/ROW]
[ROW][C]145[/C][C]64[/C][C]66.3157894736842[/C][C]-2.31578947368421[/C][/ROW]
[ROW][C]146[/C][C]29[/C][C]25.7608695652174[/C][C]3.23913043478261[/C][/ROW]
[ROW][C]147[/C][C]32[/C][C]34.609756097561[/C][C]-2.60975609756098[/C][/ROW]
[ROW][C]148[/C][C]25[/C][C]45.5[/C][C]-20.5[/C][/ROW]
[ROW][C]149[/C][C]16[/C][C]10.1363636363636[/C][C]5.86363636363636[/C][/ROW]
[ROW][C]150[/C][C]48[/C][C]45.5[/C][C]2.5[/C][/ROW]
[ROW][C]151[/C][C]100[/C][C]100.333333333333[/C][C]-0.333333333333329[/C][/ROW]
[ROW][C]152[/C][C]46[/C][C]78.875[/C][C]-32.875[/C][/ROW]
[ROW][C]153[/C][C]45[/C][C]34.609756097561[/C][C]10.390243902439[/C][/ROW]
[ROW][C]154[/C][C]129[/C][C]113.40625[/C][C]15.59375[/C][/ROW]
[ROW][C]155[/C][C]130[/C][C]113.40625[/C][C]16.59375[/C][/ROW]
[ROW][C]156[/C][C]136[/C][C]113.40625[/C][C]22.59375[/C][/ROW]
[ROW][C]157[/C][C]59[/C][C]66.3157894736842[/C][C]-7.31578947368421[/C][/ROW]
[ROW][C]158[/C][C]25[/C][C]34.609756097561[/C][C]-9.60975609756098[/C][/ROW]
[ROW][C]159[/C][C]32[/C][C]34.609756097561[/C][C]-2.60975609756098[/C][/ROW]
[ROW][C]160[/C][C]63[/C][C]78.875[/C][C]-15.875[/C][/ROW]
[ROW][C]161[/C][C]95[/C][C]113.40625[/C][C]-18.40625[/C][/ROW]
[ROW][C]162[/C][C]14[/C][C]10.1363636363636[/C][C]3.86363636363636[/C][/ROW]
[ROW][C]163[/C][C]36[/C][C]45.5[/C][C]-9.5[/C][/ROW]
[ROW][C]164[/C][C]113[/C][C]113.40625[/C][C]-0.40625[/C][/ROW]
[ROW][C]165[/C][C]47[/C][C]45.5[/C][C]1.5[/C][/ROW]
[ROW][C]166[/C][C]92[/C][C]78.875[/C][C]13.125[/C][/ROW]
[ROW][C]167[/C][C]70[/C][C]78.875[/C][C]-8.875[/C][/ROW]
[ROW][C]168[/C][C]19[/C][C]45.5[/C][C]-26.5[/C][/ROW]
[ROW][C]169[/C][C]50[/C][C]45.5[/C][C]4.5[/C][/ROW]
[ROW][C]170[/C][C]41[/C][C]34.609756097561[/C][C]6.39024390243902[/C][/ROW]
[ROW][C]171[/C][C]91[/C][C]100.333333333333[/C][C]-9.33333333333333[/C][/ROW]
[ROW][C]172[/C][C]111[/C][C]113.40625[/C][C]-2.40625[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]26.5714285714286[/C][C]14.4285714285714[/C][/ROW]
[ROW][C]174[/C][C]120[/C][C]113.40625[/C][C]6.59375[/C][/ROW]
[ROW][C]175[/C][C]135[/C][C]78.875[/C][C]56.125[/C][/ROW]
[ROW][C]176[/C][C]27[/C][C]34.609756097561[/C][C]-7.60975609756098[/C][/ROW]
[ROW][C]177[/C][C]87[/C][C]100.333333333333[/C][C]-13.3333333333333[/C][/ROW]
[ROW][C]178[/C][C]25[/C][C]25.7608695652174[/C][C]-0.760869565217391[/C][/ROW]
[ROW][C]179[/C][C]131[/C][C]113.40625[/C][C]17.59375[/C][/ROW]
[ROW][C]180[/C][C]45[/C][C]25.7608695652174[/C][C]19.2391304347826[/C][/ROW]
[ROW][C]181[/C][C]29[/C][C]25.7608695652174[/C][C]3.23913043478261[/C][/ROW]
[ROW][C]182[/C][C]58[/C][C]26.5714285714286[/C][C]31.4285714285714[/C][/ROW]
[ROW][C]183[/C][C]4[/C][C]2.36363636363636[/C][C]1.63636363636364[/C][/ROW]
[ROW][C]184[/C][C]47[/C][C]78.875[/C][C]-31.875[/C][/ROW]
[ROW][C]185[/C][C]109[/C][C]113.40625[/C][C]-4.40625[/C][/ROW]
[ROW][C]186[/C][C]7[/C][C]10.1363636363636[/C][C]-3.13636363636364[/C][/ROW]
[ROW][C]187[/C][C]12[/C][C]10.1363636363636[/C][C]1.86363636363636[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]2.36363636363636[/C][C]-2.36363636363636[/C][/ROW]
[ROW][C]189[/C][C]37[/C][C]45.5[/C][C]-8.5[/C][/ROW]
[ROW][C]190[/C][C]37[/C][C]25.7608695652174[/C][C]11.2391304347826[/C][/ROW]
[ROW][C]191[/C][C]46[/C][C]45.5[/C][C]0.5[/C][/ROW]
[ROW][C]192[/C][C]15[/C][C]26.5714285714286[/C][C]-11.5714285714286[/C][/ROW]
[ROW][C]193[/C][C]42[/C][C]34.609756097561[/C][C]7.39024390243902[/C][/ROW]
[ROW][C]194[/C][C]7[/C][C]10.1363636363636[/C][C]-3.13636363636364[/C][/ROW]
[ROW][C]195[/C][C]54[/C][C]45.5[/C][C]8.5[/C][/ROW]
[ROW][C]196[/C][C]54[/C][C]78.875[/C][C]-24.875[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]25.7608695652174[/C][C]-11.7608695652174[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]45.5[/C][C]-29.5[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]45.5[/C][C]-12.5[/C][/ROW]
[ROW][C]200[/C][C]32[/C][C]45.5[/C][C]-13.5[/C][/ROW]
[ROW][C]201[/C][C]21[/C][C]34.609756097561[/C][C]-13.609756097561[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]16.5833333333333[/C][C]-1.58333333333333[/C][/ROW]
[ROW][C]203[/C][C]38[/C][C]34.609756097561[/C][C]3.39024390243902[/C][/ROW]
[ROW][C]204[/C][C]22[/C][C]25.7608695652174[/C][C]-3.76086956521739[/C][/ROW]
[ROW][C]205[/C][C]28[/C][C]34.609756097561[/C][C]-6.60975609756098[/C][/ROW]
[ROW][C]206[/C][C]10[/C][C]10.1363636363636[/C][C]-0.136363636363637[/C][/ROW]
[ROW][C]207[/C][C]31[/C][C]25.7608695652174[/C][C]5.23913043478261[/C][/ROW]
[ROW][C]208[/C][C]32[/C][C]34.609756097561[/C][C]-2.60975609756098[/C][/ROW]
[ROW][C]209[/C][C]32[/C][C]34.609756097561[/C][C]-2.60975609756098[/C][/ROW]
[ROW][C]210[/C][C]43[/C][C]34.609756097561[/C][C]8.39024390243902[/C][/ROW]
[ROW][C]211[/C][C]27[/C][C]25.7608695652174[/C][C]1.23913043478261[/C][/ROW]
[ROW][C]212[/C][C]37[/C][C]34.609756097561[/C][C]2.39024390243902[/C][/ROW]
[ROW][C]213[/C][C]20[/C][C]16.5833333333333[/C][C]3.41666666666667[/C][/ROW]
[ROW][C]214[/C][C]32[/C][C]25.7608695652174[/C][C]6.23913043478261[/C][/ROW]
[ROW][C]215[/C][C]0[/C][C]10.1363636363636[/C][C]-10.1363636363636[/C][/ROW]
[ROW][C]216[/C][C]5[/C][C]10.1363636363636[/C][C]-5.13636363636364[/C][/ROW]
[ROW][C]217[/C][C]26[/C][C]25.7608695652174[/C][C]0.239130434782609[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]25.7608695652174[/C][C]-15.7608695652174[/C][/ROW]
[ROW][C]219[/C][C]27[/C][C]25.7608695652174[/C][C]1.23913043478261[/C][/ROW]
[ROW][C]220[/C][C]11[/C][C]10.1363636363636[/C][C]0.863636363636363[/C][/ROW]
[ROW][C]221[/C][C]29[/C][C]25.7608695652174[/C][C]3.23913043478261[/C][/ROW]
[ROW][C]222[/C][C]25[/C][C]34.609756097561[/C][C]-9.60975609756098[/C][/ROW]
[ROW][C]223[/C][C]55[/C][C]45.5[/C][C]9.5[/C][/ROW]
[ROW][C]224[/C][C]23[/C][C]25.7608695652174[/C][C]-2.76086956521739[/C][/ROW]
[ROW][C]225[/C][C]5[/C][C]10.1363636363636[/C][C]-5.13636363636364[/C][/ROW]
[ROW][C]226[/C][C]43[/C][C]45.5[/C][C]-2.5[/C][/ROW]
[ROW][C]227[/C][C]23[/C][C]25.7608695652174[/C][C]-2.76086956521739[/C][/ROW]
[ROW][C]228[/C][C]34[/C][C]45.5[/C][C]-11.5[/C][/ROW]
[ROW][C]229[/C][C]36[/C][C]34.609756097561[/C][C]1.39024390243902[/C][/ROW]
[ROW][C]230[/C][C]35[/C][C]25.7608695652174[/C][C]9.23913043478261[/C][/ROW]
[ROW][C]231[/C][C]0[/C][C]2.36363636363636[/C][C]-2.36363636363636[/C][/ROW]
[ROW][C]232[/C][C]37[/C][C]34.609756097561[/C][C]2.39024390243902[/C][/ROW]
[ROW][C]233[/C][C]28[/C][C]34.609756097561[/C][C]-6.60975609756098[/C][/ROW]
[ROW][C]234[/C][C]16[/C][C]10.1363636363636[/C][C]5.86363636363636[/C][/ROW]
[ROW][C]235[/C][C]26[/C][C]34.609756097561[/C][C]-8.60975609756098[/C][/ROW]
[ROW][C]236[/C][C]38[/C][C]25.7608695652174[/C][C]12.2391304347826[/C][/ROW]
[ROW][C]237[/C][C]23[/C][C]25.7608695652174[/C][C]-2.76086956521739[/C][/ROW]
[ROW][C]238[/C][C]22[/C][C]25.7608695652174[/C][C]-3.76086956521739[/C][/ROW]
[ROW][C]239[/C][C]30[/C][C]25.7608695652174[/C][C]4.23913043478261[/C][/ROW]
[ROW][C]240[/C][C]16[/C][C]16.5833333333333[/C][C]-0.583333333333332[/C][/ROW]
[ROW][C]241[/C][C]18[/C][C]25.7608695652174[/C][C]-7.76086956521739[/C][/ROW]
[ROW][C]242[/C][C]28[/C][C]45.5[/C][C]-17.5[/C][/ROW]
[ROW][C]243[/C][C]32[/C][C]25.7608695652174[/C][C]6.23913043478261[/C][/ROW]
[ROW][C]244[/C][C]21[/C][C]16.5833333333333[/C][C]4.41666666666667[/C][/ROW]
[ROW][C]245[/C][C]23[/C][C]34.609756097561[/C][C]-11.609756097561[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]34.609756097561[/C][C]-5.60975609756098[/C][/ROW]
[ROW][C]247[/C][C]50[/C][C]45.5[/C][C]4.5[/C][/ROW]
[ROW][C]248[/C][C]12[/C][C]26.5714285714286[/C][C]-14.5714285714286[/C][/ROW]
[ROW][C]249[/C][C]21[/C][C]25.7608695652174[/C][C]-4.76086956521739[/C][/ROW]
[ROW][C]250[/C][C]18[/C][C]16.5833333333333[/C][C]1.41666666666667[/C][/ROW]
[ROW][C]251[/C][C]27[/C][C]34.609756097561[/C][C]-7.60975609756098[/C][/ROW]
[ROW][C]252[/C][C]41[/C][C]45.5[/C][C]-4.5[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]10.1363636363636[/C][C]2.86363636363636[/C][/ROW]
[ROW][C]254[/C][C]12[/C][C]25.7608695652174[/C][C]-13.7608695652174[/C][/ROW]
[ROW][C]255[/C][C]21[/C][C]25.7608695652174[/C][C]-4.76086956521739[/C][/ROW]
[ROW][C]256[/C][C]8[/C][C]10.1363636363636[/C][C]-2.13636363636364[/C][/ROW]
[ROW][C]257[/C][C]26[/C][C]16.5833333333333[/C][C]9.41666666666667[/C][/ROW]
[ROW][C]258[/C][C]27[/C][C]26.5714285714286[/C][C]0.428571428571427[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]10.1363636363636[/C][C]2.86363636363636[/C][/ROW]
[ROW][C]260[/C][C]16[/C][C]10.1363636363636[/C][C]5.86363636363636[/C][/ROW]
[ROW][C]261[/C][C]2[/C][C]2.36363636363636[/C][C]-0.363636363636364[/C][/ROW]
[ROW][C]262[/C][C]42[/C][C]34.609756097561[/C][C]7.39024390243902[/C][/ROW]
[ROW][C]263[/C][C]5[/C][C]2.36363636363636[/C][C]2.63636363636364[/C][/ROW]
[ROW][C]264[/C][C]37[/C][C]34.609756097561[/C][C]2.39024390243902[/C][/ROW]
[ROW][C]265[/C][C]17[/C][C]16.5833333333333[/C][C]0.416666666666668[/C][/ROW]
[ROW][C]266[/C][C]38[/C][C]34.609756097561[/C][C]3.39024390243902[/C][/ROW]
[ROW][C]267[/C][C]37[/C][C]34.609756097561[/C][C]2.39024390243902[/C][/ROW]
[ROW][C]268[/C][C]29[/C][C]34.609756097561[/C][C]-5.60975609756098[/C][/ROW]
[ROW][C]269[/C][C]32[/C][C]34.609756097561[/C][C]-2.60975609756098[/C][/ROW]
[ROW][C]270[/C][C]35[/C][C]45.5[/C][C]-10.5[/C][/ROW]
[ROW][C]271[/C][C]17[/C][C]34.609756097561[/C][C]-17.609756097561[/C][/ROW]
[ROW][C]272[/C][C]20[/C][C]25.7608695652174[/C][C]-5.76086956521739[/C][/ROW]
[ROW][C]273[/C][C]7[/C][C]2.36363636363636[/C][C]4.63636363636364[/C][/ROW]
[ROW][C]274[/C][C]46[/C][C]34.609756097561[/C][C]11.390243902439[/C][/ROW]
[ROW][C]275[/C][C]24[/C][C]25.7608695652174[/C][C]-1.76086956521739[/C][/ROW]
[ROW][C]276[/C][C]40[/C][C]25.7608695652174[/C][C]14.2391304347826[/C][/ROW]
[ROW][C]277[/C][C]3[/C][C]2.36363636363636[/C][C]0.636363636363636[/C][/ROW]
[ROW][C]278[/C][C]10[/C][C]10.1363636363636[/C][C]-0.136363636363637[/C][/ROW]
[ROW][C]279[/C][C]37[/C][C]34.609756097561[/C][C]2.39024390243902[/C][/ROW]
[ROW][C]280[/C][C]17[/C][C]25.7608695652174[/C][C]-8.76086956521739[/C][/ROW]
[ROW][C]281[/C][C]28[/C][C]25.7608695652174[/C][C]2.23913043478261[/C][/ROW]
[ROW][C]282[/C][C]19[/C][C]26.5714285714286[/C][C]-7.57142857142857[/C][/ROW]
[ROW][C]283[/C][C]29[/C][C]25.7608695652174[/C][C]3.23913043478261[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]10.1363636363636[/C][C]-2.13636363636364[/C][/ROW]
[ROW][C]285[/C][C]10[/C][C]10.1363636363636[/C][C]-0.136363636363637[/C][/ROW]
[ROW][C]286[/C][C]15[/C][C]25.7608695652174[/C][C]-10.7608695652174[/C][/ROW]
[ROW][C]287[/C][C]15[/C][C]10.1363636363636[/C][C]4.86363636363636[/C][/ROW]
[ROW][C]288[/C][C]28[/C][C]45.5[/C][C]-17.5[/C][/ROW]
[ROW][C]289[/C][C]17[/C][C]25.7608695652174[/C][C]-8.76086956521739[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197683&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197683&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	79	113.40625	-34.40625
2	58	78.875	-20.875
3	60	78.875	-18.875
4	108	100.333333333333	7.66666666666667
5	49	45.5	3.5
6	0	16.5833333333333	-16.5833333333333
7	121	113.40625	7.59375
8	1	2.36363636363636	-1.36363636363636
9	20	25.7608695652174	-5.76086956521739
10	43	45.5	-2.5
11	69	66.3157894736842	2.68421052631579
12	78	78.875	-0.875
13	86	66.3157894736842	19.6842105263158
14	44	45.5	-1.5
15	104	100.333333333333	3.66666666666667
16	63	66.3157894736842	-3.31578947368421
17	158	113.40625	44.59375
18	102	113.40625	-11.40625
19	77	100.333333333333	-23.3333333333333
20	82	78.875	3.125
21	115	113.40625	1.59375
22	101	78.875	22.125
23	80	100.333333333333	-20.3333333333333
24	50	45.5	4.5
25	83	78.875	4.125
26	123	100.333333333333	22.6666666666667
27	73	78.875	-5.875
28	81	100.333333333333	-19.3333333333333
29	105	78.875	26.125
30	47	45.5	1.5
31	105	78.875	26.125
32	94	78.875	15.125
33	44	78.875	-34.875
34	114	78.875	35.125
35	38	25.7608695652174	12.2391304347826
36	107	113.40625	-6.40625
37	30	25.7608695652174	4.23913043478261
38	71	66.3157894736842	4.68421052631579
39	84	100.333333333333	-16.3333333333333
40	0	2.36363636363636	-2.36363636363636
41	59	66.3157894736842	-7.31578947368421
42	33	34.609756097561	-1.60975609756098
43	42	34.609756097561	7.39024390243902
44	96	100.333333333333	-4.33333333333333
45	106	100.333333333333	5.66666666666667
46	56	45.5	10.5
47	57	66.3157894736842	-9.31578947368421
48	59	45.5	13.5
49	39	45.5	-6.5
50	34	34.609756097561	-0.609756097560975
51	76	66.3157894736842	9.68421052631579
52	20	25.7608695652174	-5.76086956521739
53	91	78.875	12.125
54	115	113.40625	1.59375
55	85	78.875	6.125
56	76	78.875	-2.875
57	8	10.1363636363636	-2.13636363636364
58	79	113.40625	-34.40625
59	21	25.7608695652174	-4.76086956521739
60	30	25.7608695652174	4.23913043478261
61	76	100.333333333333	-24.3333333333333
62	101	113.40625	-12.40625
63	94	100.333333333333	-6.33333333333333
64	27	25.7608695652174	1.23913043478261
65	92	113.40625	-21.40625
66	123	113.40625	9.59375
67	75	66.3157894736842	8.68421052631579
68	128	113.40625	14.59375
69	105	113.40625	-8.40625
70	55	66.3157894736842	-11.3157894736842
71	56	78.875	-22.875
72	41	78.875	-37.875
73	72	78.875	-6.875
74	67	78.875	-11.875
75	75	78.875	-3.875
76	114	113.40625	0.59375
77	118	45.5	72.5
78	77	78.875	-1.875
79	22	25.7608695652174	-3.76086956521739
80	66	66.3157894736842	-0.315789473684205
81	69	78.875	-9.875
82	105	78.875	26.125
83	116	100.333333333333	15.6666666666667
84	88	78.875	9.125
85	73	66.3157894736842	6.68421052631579
86	99	78.875	20.125
87	62	45.5	16.5
88	53	34.609756097561	18.390243902439
89	118	100.333333333333	17.6666666666667
90	30	34.609756097561	-4.60975609756098
91	100	113.40625	-13.40625
92	49	45.5	3.5
93	24	25.7608695652174	-1.76086956521739
94	67	78.875	-11.875
95	46	34.609756097561	11.390243902439
96	57	66.3157894736842	-9.31578947368421
97	75	66.3157894736842	8.68421052631579
98	135	113.40625	21.59375
99	68	66.3157894736842	1.68421052631579
100	124	113.40625	10.59375
101	33	45.5	-12.5
102	98	100.333333333333	-2.33333333333333
103	58	78.875	-20.875
104	68	78.875	-10.875
105	81	113.40625	-32.40625
106	131	113.40625	17.59375
107	110	100.333333333333	9.66666666666667
108	37	34.609756097561	2.39024390243902
109	130	113.40625	16.59375
110	93	78.875	14.125
111	118	113.40625	4.59375
112	39	34.609756097561	4.39024390243902
113	13	16.5833333333333	-3.58333333333333
114	74	66.3157894736842	7.68421052631579
115	81	113.40625	-32.40625
116	109	100.333333333333	8.66666666666667
117	151	100.333333333333	50.6666666666667
118	51	66.3157894736842	-15.3157894736842
119	28	45.5	-17.5
120	40	34.609756097561	5.39024390243902
121	56	45.5	10.5
122	27	25.7608695652174	1.23913043478261
123	37	45.5	-8.5
124	83	45.5	37.5
125	54	78.875	-24.875
126	27	25.7608695652174	1.23913043478261
127	28	25.7608695652174	2.23913043478261
128	59	45.5	13.5
129	133	78.875	54.125
130	12	10.1363636363636	1.86363636363636
131	0	2.36363636363636	-2.36363636363636
132	106	78.875	27.125
133	23	16.5833333333333	6.41666666666667
134	44	34.609756097561	9.39024390243902
135	71	78.875	-7.875
136	116	113.40625	2.59375
137	4	2.36363636363636	1.63636363636364
138	62	66.3157894736842	-4.31578947368421
139	12	16.5833333333333	-4.58333333333333
140	18	16.5833333333333	1.41666666666667
141	14	26.5714285714286	-12.5714285714286
142	60	45.5	14.5
143	7	10.1363636363636	-3.13636363636364
144	98	100.333333333333	-2.33333333333333
145	64	66.3157894736842	-2.31578947368421
146	29	25.7608695652174	3.23913043478261
147	32	34.609756097561	-2.60975609756098
148	25	45.5	-20.5
149	16	10.1363636363636	5.86363636363636
150	48	45.5	2.5
151	100	100.333333333333	-0.333333333333329
152	46	78.875	-32.875
153	45	34.609756097561	10.390243902439
154	129	113.40625	15.59375
155	130	113.40625	16.59375
156	136	113.40625	22.59375
157	59	66.3157894736842	-7.31578947368421
158	25	34.609756097561	-9.60975609756098
159	32	34.609756097561	-2.60975609756098
160	63	78.875	-15.875
161	95	113.40625	-18.40625
162	14	10.1363636363636	3.86363636363636
163	36	45.5	-9.5
164	113	113.40625	-0.40625
165	47	45.5	1.5
166	92	78.875	13.125
167	70	78.875	-8.875
168	19	45.5	-26.5
169	50	45.5	4.5
170	41	34.609756097561	6.39024390243902
171	91	100.333333333333	-9.33333333333333
172	111	113.40625	-2.40625
173	41	26.5714285714286	14.4285714285714
174	120	113.40625	6.59375
175	135	78.875	56.125
176	27	34.609756097561	-7.60975609756098
177	87	100.333333333333	-13.3333333333333
178	25	25.7608695652174	-0.760869565217391
179	131	113.40625	17.59375
180	45	25.7608695652174	19.2391304347826
181	29	25.7608695652174	3.23913043478261
182	58	26.5714285714286	31.4285714285714
183	4	2.36363636363636	1.63636363636364
184	47	78.875	-31.875
185	109	113.40625	-4.40625
186	7	10.1363636363636	-3.13636363636364
187	12	10.1363636363636	1.86363636363636
188	0	2.36363636363636	-2.36363636363636
189	37	45.5	-8.5
190	37	25.7608695652174	11.2391304347826
191	46	45.5	0.5
192	15	26.5714285714286	-11.5714285714286
193	42	34.609756097561	7.39024390243902
194	7	10.1363636363636	-3.13636363636364
195	54	45.5	8.5
196	54	78.875	-24.875
197	14	25.7608695652174	-11.7608695652174
198	16	45.5	-29.5
199	33	45.5	-12.5
200	32	45.5	-13.5
201	21	34.609756097561	-13.609756097561
202	15	16.5833333333333	-1.58333333333333
203	38	34.609756097561	3.39024390243902
204	22	25.7608695652174	-3.76086956521739
205	28	34.609756097561	-6.60975609756098
206	10	10.1363636363636	-0.136363636363637
207	31	25.7608695652174	5.23913043478261
208	32	34.609756097561	-2.60975609756098
209	32	34.609756097561	-2.60975609756098
210	43	34.609756097561	8.39024390243902
211	27	25.7608695652174	1.23913043478261
212	37	34.609756097561	2.39024390243902
213	20	16.5833333333333	3.41666666666667
214	32	25.7608695652174	6.23913043478261
215	0	10.1363636363636	-10.1363636363636
216	5	10.1363636363636	-5.13636363636364
217	26	25.7608695652174	0.239130434782609
218	10	25.7608695652174	-15.7608695652174
219	27	25.7608695652174	1.23913043478261
220	11	10.1363636363636	0.863636363636363
221	29	25.7608695652174	3.23913043478261
222	25	34.609756097561	-9.60975609756098
223	55	45.5	9.5
224	23	25.7608695652174	-2.76086956521739
225	5	10.1363636363636	-5.13636363636364
226	43	45.5	-2.5
227	23	25.7608695652174	-2.76086956521739
228	34	45.5	-11.5
229	36	34.609756097561	1.39024390243902
230	35	25.7608695652174	9.23913043478261
231	0	2.36363636363636	-2.36363636363636
232	37	34.609756097561	2.39024390243902
233	28	34.609756097561	-6.60975609756098
234	16	10.1363636363636	5.86363636363636
235	26	34.609756097561	-8.60975609756098
236	38	25.7608695652174	12.2391304347826
237	23	25.7608695652174	-2.76086956521739
238	22	25.7608695652174	-3.76086956521739
239	30	25.7608695652174	4.23913043478261
240	16	16.5833333333333	-0.583333333333332
241	18	25.7608695652174	-7.76086956521739
242	28	45.5	-17.5
243	32	25.7608695652174	6.23913043478261
244	21	16.5833333333333	4.41666666666667
245	23	34.609756097561	-11.609756097561
246	29	34.609756097561	-5.60975609756098
247	50	45.5	4.5
248	12	26.5714285714286	-14.5714285714286
249	21	25.7608695652174	-4.76086956521739
250	18	16.5833333333333	1.41666666666667
251	27	34.609756097561	-7.60975609756098
252	41	45.5	-4.5
253	13	10.1363636363636	2.86363636363636
254	12	25.7608695652174	-13.7608695652174
255	21	25.7608695652174	-4.76086956521739
256	8	10.1363636363636	-2.13636363636364
257	26	16.5833333333333	9.41666666666667
258	27	26.5714285714286	0.428571428571427
259	13	10.1363636363636	2.86363636363636
260	16	10.1363636363636	5.86363636363636
261	2	2.36363636363636	-0.363636363636364
262	42	34.609756097561	7.39024390243902
263	5	2.36363636363636	2.63636363636364
264	37	34.609756097561	2.39024390243902
265	17	16.5833333333333	0.416666666666668
266	38	34.609756097561	3.39024390243902
267	37	34.609756097561	2.39024390243902
268	29	34.609756097561	-5.60975609756098
269	32	34.609756097561	-2.60975609756098
270	35	45.5	-10.5
271	17	34.609756097561	-17.609756097561
272	20	25.7608695652174	-5.76086956521739
273	7	2.36363636363636	4.63636363636364
274	46	34.609756097561	11.390243902439
275	24	25.7608695652174	-1.76086956521739
276	40	25.7608695652174	14.2391304347826
277	3	2.36363636363636	0.636363636363636
278	10	10.1363636363636	-0.136363636363637
279	37	34.609756097561	2.39024390243902
280	17	25.7608695652174	-8.76086956521739
281	28	25.7608695652174	2.23913043478261
282	19	26.5714285714286	-7.57142857142857
283	29	25.7608695652174	3.23913043478261
284	8	10.1363636363636	-2.13636363636364
285	10	10.1363636363636	-0.136363636363637
286	15	25.7608695652174	-10.7608695652174
287	15	10.1363636363636	4.86363636363636
288	28	45.5	-17.5
289	17	25.7608695652174	-8.76086956521739

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 = pearson ;

Parameters (R input):

par1 = 7 ; par2 = none ; par3 = ; 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