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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 10:06:32 -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/t132387523404q3u2kaxqfbk6j.htm/, Retrieved Wed, 01 May 2024 14:58:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155031, Retrieved Wed, 01 May 2024 14:58:12 +0000

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Original text written by user:

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)

-     [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-14 13:13:32] [246430c28552f7bc561843533d7ec653]
- R     [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-14 13:25:26] [246430c28552f7bc561843533d7ec653]
-         [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-14 13:55:42] [246430c28552f7bc561843533d7ec653]
- RMPD        [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2011-12-14 15:06:32] [7c363341293f6644b8647ab9153ed4f7] [Current]

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Dataseries X:

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Histogram

Boxplots

1713	269966	66	473	90	96	38	144	140824	32033	186099	165	165
1028	146082	61	352	63	64	34	133	110459	20654	113854	135	132
1807	214542	67	660	59	69	42	162	105079	16346	99776	121	121
2613	212452	100	1126	135	126	38	148	112098	35926	106194	148	145
1117	157206	49	333	48	59	27	88	43929	10621	100792	73	71
631	70849	28	179	46	8	35	129	76173	10024	47552	49	47
4294	476347	111	2091	109	145	33	128	187326	43068	250931	185	177
381	33186	19	111	46	1	18	67	22807	1271	6853	5	5
1937	201983	56	726	75	69	34	132	144408	34416	115466	125	124
1734	211698	43	585	72	82	33	120	66485	20318	110896	93	92
2010	292874	102	754	78	92	42	155	79089	24409	169351	154	149
1988	223814	107	619	61	106	55	210	81625	20648	94853	98	93
1600	156623	65	615	58	50	35	115	68788	12347	72591	70	70
2664	327332	73	1060	109	113	51	175	103297	21857	101345	148	148
1812	205898	78	588	45	70	42	158	69446	11034	113713	100	100
4698	369527	172	1626	127	168	59	223	114948	33433	165354	150	142
2043	290571	66	717	58	111	36	140	167949	35902	164263	197	194
2690	292903	146	1053	90	92	39	144	125081	22355	135213	114	113
1381	168639	52	491	41	102	29	111	125818	31219	111669	169	162
2249	253641	79	669	54	135	46	179	136588	21983	134163	200	186
2446	269240	68	819	99	122	45	171	112431	40085	140303	148	147
2681	414808	101	1150	101	86	39	144	103037	18507	150773	140	137
1306	161910	38	421	62	50	25	89	82317	16278	111848	74	71
1649	178722	53	583	65	94	52	208	118906	24662	102509	128	123
2975	200181	109	1146	150	127	41	153	83515	31452	96785	140	134
2507	203700	111	922	71	86	38	146	104581	32580	116136	116	115
2817	267099	126	1058	91	99	41	158	103129	22883	158376	147	138
1879	262716	83	593	59	117	39	142	83243	27652	153990	132	125
1495	155915	51	559	53	57	32	117	37110	9845	64057	70	66
2661	324641	59	1001	140	125	41	158	113344	20190	230054	144	137
2154	261785	72	848	49	120	45	175	139165	46201	184531	155	152
1741	192626	71	590	77	44	46	170	86652	10971	114198	165	159
2090	318563	83	779	53	133	48	185	112302	34811	198299	161	159
940	97615	35	308	40	43	37	141	69652	3029	33750	31	31
2804	343613	88	1108	72	117	39	151	119442	38941	189723	199	185
2751	272026	55	1183	87	83	42	159	69867	4958	100826	78	78
3509	408580	115	1261	71	105	41	151	101629	32344	188355	121	117
1771	206904	78	581	67	79	36	139	70168	19433	104470	112	109
934	115469	32	276	36	33	17	55	31081	12558	58391	41	41
3000	310587	176	1061	45	111	39	151	103925	36524	164808	158	149
3178	315746	76	1471	38	121	37	139	92622	26041	134097	123	123
1489	157897	62	590	70	67	38	138	79011	16637	80238	104	103
1723	192883	72	632	82	73	36	115	93487	28395	133252	94	87
1655	165876	56	450	83	68	42	157	64520	16747	54518	73	71
2496	153778	82	1022	82	50	45	73	93473	9105	121850	52	51
4948	414493	139	1864	780	98	38	138	114360	11941	79367	71	70
918	78800	42	330	57	20	26	82	33032	7935	56968	21	21
2219	207958	74	648	79	101	52	201	96125	19499	106314	155	155
3832	323118	113	1303	116	137	47	181	151911	22938	191889	174	172
2081	175523	54	868	68	99	45	164	89256	25314	104864	136	133
1805	213050	72	554	48	94	40	158	95671	28524	160791	128	125
496	24188	24	218	20	8	4	12	5950	2694	15049	7	7
2464	364968	300	816	76	83	44	163	149695	20867	191179	165	158
744	65029	17	255	21	21	18	67	32551	3597	25109	21	21
1161	101097	64	454	70	30	14	52	31701	5296	45824	35	35
2803	263096	54	1009	124	96	37	134	100087	32982	129711	137	133
2421	302012	81	639	80	122	56	210	169707	38975	210012	174	169
3449	315753	170	1048	206	115	36	134	150491	42721	194679	257	256
2323	300531	130	934	62	139	41	150	120192	41455	197680	207	190
2084	240445	79	784	77	89	36	139	95893	23923	81180	103	100
3866	360325	135	1282	65	147	46	178	151715	26719	197765	171	171
3104	296186	113	1128	146	135	28	101	176225	53405	214738	279	267
2372	210104	97	958	71	63	42	165	59900	12526	96252	83	80
2331	247076	85	847	48	72	38	147	104767	26584	124527	130	126
1363	220722	64	540	58	47	37	139	114799	37062	153242	131	132
1646	216027	65	436	58	96	30	116	72128	25696	145707	126	121
1841	187773	124	557	54	79	35	137	143592	24634	113963	158	156
2587	227055	137	794	89	85	44	167	89626	27269	134904	138	133
2254	229181	76	826	78	135	36	135	131072	25270	114268	200	199
1580	159082	63	580	62	142	28	102	126817	24634	94333	104	98
2449	232624	65	838	59	97	45	173	81351	17828	102204	111	109
893	73566	32	385	39	22	23	88	22618	3007	23824	26	25
2113	231827	76	698	55	75	45	175	88977	20065	111563	115	113
1593	181728	50	667	94	77	38	133	92059	24648	91313	127	126
1644	162366	57	548	61	110	38	148	81897	21588	89770	140	137
2153	329583	75	932	87	132	42	157	108146	25217	100125	121	121
2350	303317	87	941	48	111	36	140	126372	30927	165278	183	178
1770	205630	104	512	50	78	41	154	249771	18487	181712	68	63
2110	184970	60	648	58	126	38	148	71154	18050	80906	112	109
1601	168990	60	588	67	73	37	134	71571	17696	75881	103	101
1643	151231	45	608	41	62	28	109	55918	17326	83963	63	61
3559	421615	108	1165	114	141	45	175	160141	39361	175721	166	157
1358	145916	67	649	45	30	26	99	38692	9648	68580	38	38
2204	270487	99	623	57	116	44	122	102812	26759	136323	163	159
870	80953	25	437	31	49	8	28	56622	7905	55792	59	58
1773	139193	53	752	175	26	27	101	15986	4527	25157	27	27
1202	146777	53	342	63	71	35	129	123534	41517	100922	108	108
3422	335969	174	1351	276	59	37	143	108535	21261	118845	88	83
2417	297676	105	835	91	114	57	206	93879	36099	170492	92	88
3016	175232	101	1027	67	161	41	155	144551	39039	81716	170	164
2233	238938	87	770	58	74	37	138	56750	13841	115750	98	96
1992	228459	71	614	71	151	38	141	127654	23841	105590	205	192
1689	175244	61	545	86	41	31	114	65594	8589	92795	96	94
2916	256299	71	1046	89	121	36	140	59938	15049	82390	107	107
2342	288728	75	907	134	66	36	140	146975	39038	135599	150	144
1624	189252	36	555	64	83	36	140	143372	30391	111542	123	123
1579	222324	49	540	72	94	35	127	168553	39932	162519	176	170
1997	277755	74	736	61	154	39	141	183500	43840	211381	213	210
3760	364710	141	1247	121	151	58	223	165986	43146	189944	208	193
3611	392346	105	1389	73	164	30	114	184923	50099	226168	307	297
2355	260478	112	777	60	115	45	174	140358	40312	117495	125	125
2192	273240	62	802	85	140	41	155	149959	32616	195894	208	204
1984	186310	173	636	116	73	36	138	57224	11338	80684	73	70
602	43287	14	214	43	13	19	71	43750	7409	19630	49	49
2133	185181	78	711	85	89	23	84	48029	18213	88634	82	82
1927	202989	130	685	72	90	40	151	104978	45873	139292	206	205
2535	259498	46	1135	110	128	40	155	100046	39844	128602	112	111
2586	295230	86	999	54	169	40	150	101047	28317	135848	139	135
1072	114156	61	343	44	28	30	112	197426	24797	178377	60	59
3031	151624	82	880	79	116	41	161	160902	7471	106330	70	70
1855	306941	66	604	58	76	40	149	147172	27259	178303	112	108
2237	289398	84	660	70	145	45	164	109432	23201	116938	142	141
398	23623	11	156	9	12	1	0	1168	238	5841	11	11
1821	174970	69	648	49	120	36	139	83248	28830	106020	130	130
530	61857	25	192	25	23	11	32	25162	3913	24610	31	28
1596	163766	48	457	107	83	45	169	45724	9935	74151	132	101
2796	364027	108	1110	63	130	38	140	110529	27738	232241	219	216
387	21054	16	146	2	4	0	0	855	338	6622	4	4
2137	252805	52	866	67	81	30	111	101382	13326	127097	102	97
484	31929	22	200	22	18	8	25	14116	3988	13155	39	39
3223	294609	110	1163	152	103	39	146	89506	24347	160501	125	119
1878	217893	59	639	70	75	44	167	135356	27111	91502	121	118
1521	167612	81	463	95	55	44	165	116066	3938	24469	42	41
1652	149905	51	654	47	43	29	107	144244	17416	88229	111	107
568	38214	34	276	52	16	8	27	8773	1888	13983	16	16
1853	189451	39	646	108	66	39	147	102153	18700	80716	70	69
2627	339683	78	976	105	137	47	178	117440	36809	157384	162	160
1239	186627	57	434	58	50	48	185	104128	24959	122975	173	158
3411	386918	77	1517	131	134	46	179	134238	37343	191469	171	161
2311	302392	95	795	120	152	48	187	134047	21849	231257	172	165
3200	384345	118	1108	107	136	50	186	279488	49809	258287	254	246
1250	187992	35	473	49	71	40	151	79756	21654	122531	90	89
1121	102424	42	401	55	42	36	131	66089	8728	61394	50	49
2793	281117	310	922	149	83	40	155	102070	20920	86480	113	107
4014	399991	163	1426	155	103	46	172	146760	27195	195791	187	182
1628	131692	48	509	100	55	39	148	154771	1037	18284	16	16
3921	371090	127	1652	139	127	42	156	165933	42570	147581	175	173
1830	157429	76	689	76	55	39	143	64593	17672	72558	90	90
1627	236370	46	528	83	104	41	151	92280	34245	147341	140	140
2209	227299	84	775	185	92	42	145	67150	16786	114651	145	142
1738	209904	110	585	69	35	32	125	128692	20954	100187	141	126
3748	355457	111	1516	106	95	39	145	124089	16378	130332	125	123
2103	230883	83	743	61	121	35	129	125386	31852	134218	241	239
2035	173260	63	716	37	41	21	79	37238	2805	10901	16	15
2763	306577	96	891	56	136	45	174	140015	38086	145758	175	170
1705	141789	54	611	122	147	50	192	150047	21166	75767	132	123
2319	210565	78	901	52	88	36	132	154451	34672	134969	154	151
2393	273544	99	750	60	170	44	159	156349	36171	169216	198	194
2	1	0	0	0	0	0	0	0	0	0	0	0
207	14688	10	85	0	4	0	0	6023	2065	7953	5	5
5	98	1	0	0	0	0	0	0	0	0	0	0
8	455	2	0	0	0	0	0	0	0	0	0	0
0	0	0	0	0	0	0	0	0	0	0	0	0
0	0	0	0	0	0	0	0	0	0	0	0	0
1931	216803	82	662	58	61	37	133	84601	19354	105406	125	122
2965	347930	136	981	108	125	47	185	68946	22124	174586	174	173
0	0	0	0	0	0	0	0	0	0	0	0	0
4	203	4	0	0	0	0	0	0	0	0	0	0
151	7199	5	74	0	7	0	0	1644	556	4245	6	6
474	46660	20	259	7	12	5	15	6179	2089	21509	13	13
141	17547	5	69	3	0	1	4	3926	2658	7670	3	3
1031	112892	42	277	88	37	43	152	52789	1813	15673	35	35
29	969	2	0	0	0	0	0	0	0	0	0	0
1650	189334	62	544	46	47	31	113	100350	17372	75882	80	72

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 5 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155031&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155031&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155031&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	5 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Goodness of Fit
Correlation	0.9452
R-squared	0.8933
RMSE	34839.0388

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.9452 \tabularnewline
R-squared & 0.8933 \tabularnewline
RMSE & 34839.0388 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155031&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.9452[/C][/ROW]
[ROW][C]R-squared[/C][C]0.8933[/C][/ROW]
[ROW][C]RMSE[/C][C]34839.0388[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155031&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155031&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	0.9452
R-squared	0.8933
RMSE	34839.0388

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	269966	290110.3125	-20144.3125
2	146082	104493.928571429	41588.0714285714
3	214542	191246.928571429	23295.0714285714
4	212452	219248.375	-6796.375
5	157206	104493.928571429	52712.0714285714
6	70849	104493.928571429	-33644.9285714286
7	476347	370981.944444444	105365.055555556
8	33186	32384.8181818182	801.18181818182
9	201983	219248.375	-17265.375
10	211698	191246.928571429	20451.0714285714
11	292874	290110.3125	2763.6875
12	223814	219248.375	4565.625
13	156623	160551.95	-3928.95000000001
14	327332	292011.842105263	35320.1578947369
15	205898	191246.928571429	14651.0714285714
16	369527	370981.944444444	-1454.94444444444
17	290571	290110.3125	460.6875
18	292903	292011.842105263	891.157894736854
19	168639	191246.928571429	-22607.9285714286
20	253641	240646.789473684	12994.2105263158
21	269240	240646.789473684	28593.2105263158
22	414808	370981.944444444	43826.0555555556
23	161910	191246.928571429	-29336.9285714286
24	178722	191246.928571429	-12524.9285714286
25	200181	292011.842105263	-91830.8421052631
26	203700	219248.375	-15548.375
27	267099	292011.842105263	-24912.8421052631
28	262716	240646.789473684	22069.2105263158
29	155915	160551.95	-4636.95000000001
30	324641	292011.842105263	32629.1578947369
31	261785	290110.3125	-28325.3125
32	192626	191246.928571429	1379.07142857142
33	318563	290110.3125	28452.6875
34	97615	104493.928571429	-6878.92857142857
35	343613	292011.842105263	51601.1578947369
36	272026	370981.944444444	-98955.9444444444
37	408580	370981.944444444	37598.0555555556
38	206904	191246.928571429	15657.0714285714
39	115469	104493.928571429	10975.0714285714
40	310587	292011.842105263	18575.1578947369
41	315746	370981.944444444	-55235.9444444444
42	157897	160551.95	-2654.95000000001
43	192883	240646.789473684	-47763.7894736842
44	165876	160551.95	5324.04999999999
45	153778	219248.375	-65470.375
46	414493	370981.944444444	43511.0555555556
47	78800	104493.928571429	-25693.9285714286
48	207958	219248.375	-11290.375
49	323118	370981.944444444	-47863.9444444444
50	175523	219248.375	-43725.375
51	213050	240646.789473684	-27596.7894736842
52	24188	32384.8181818182	-8196.81818181818
53	364968	290110.3125	74857.6875
54	65029	104493.928571429	-39464.9285714286
55	101097	104493.928571429	-3396.92857142857
56	263096	292011.842105263	-28915.8421052631
57	302012	290110.3125	11901.6875
58	315753	292011.842105263	23741.1578947369
59	300531	290110.3125	10420.6875
60	240445	219248.375	21196.625
61	360325	370981.944444444	-10656.9444444444
62	296186	292011.842105263	4174.15789473685
63	210104	219248.375	-9144.375
64	247076	240646.789473684	6429.21052631579
65	220722	240646.789473684	-19924.7894736842
66	216027	240646.789473684	-24619.7894736842
67	187773	191246.928571429	-3473.92857142858
68	227055	240646.789473684	-13591.7894736842
69	229181	219248.375	9932.625
70	159082	160551.95	-1469.95000000001
71	232624	219248.375	13375.625
72	73566	104493.928571429	-30927.9285714286
73	231827	219248.375	12578.625
74	181728	160551.95	21176.05
75	162366	160551.95	1814.04999999999
76	329583	219248.375	110334.625
77	303317	290110.3125	13206.6875
78	205630	290110.3125	-84480.3125
79	184970	219248.375	-34278.375
80	168990	160551.95	8438.04999999999
81	151231	160551.95	-9320.95000000001
82	421615	370981.944444444	50633.0555555556
83	145916	160551.95	-14635.95
84	270487	240646.789473684	29840.2105263158
85	80953	104493.928571429	-23540.9285714286
86	139193	160551.95	-21358.95
87	146777	104493.928571429	42283.0714285714
88	335969	370981.944444444	-35012.9444444444
89	297676	290110.3125	7565.6875
90	175232	292011.842105263	-116779.842105263
91	238938	219248.375	19689.625
92	228459	219248.375	9210.625
93	175244	160551.95	14692.05
94	256299	292011.842105263	-35712.8421052631
95	288728	240646.789473684	48081.2105263158
96	189252	191246.928571429	-1994.92857142858
97	222324	240646.789473684	-18322.7894736842
98	277755	290110.3125	-12355.3125
99	364710	370981.944444444	-6271.94444444444
100	392346	370981.944444444	21364.0555555556
101	260478	219248.375	41229.625
102	273240	290110.3125	-16870.3125
103	186310	219248.375	-32938.375
104	43287	32384.8181818182	10902.1818181818
105	185181	219248.375	-34067.375
106	202989	240646.789473684	-37657.7894736842
107	259498	240646.789473684	18851.2105263158
108	295230	240646.789473684	54583.2105263158
109	114156	104493.928571429	9662.07142857143
110	151624	292011.842105263	-140387.842105263
111	306941	290110.3125	16830.6875
112	289398	219248.375	70149.625
113	23623	32384.8181818182	-8761.81818181818
114	174970	191246.928571429	-16276.9285714286
115	61857	32384.8181818182	29472.1818181818
116	163766	160551.95	3214.04999999999
117	364027	292011.842105263	72015.1578947369
118	21054	32384.8181818182	-11330.8181818182
119	252805	240646.789473684	12158.2105263158
120	31929	32384.8181818182	-455.81818181818
121	294609	370981.944444444	-76372.9444444444
122	217893	219248.375	-1355.375
123	167612	160551.95	7060.04999999999
124	149905	160551.95	-10646.95
125	38214	32384.8181818182	5829.18181818182
126	189451	160551.95	28899.05
127	339683	292011.842105263	47671.1578947369
128	186627	191246.928571429	-4619.92857142858
129	386918	370981.944444444	15936.0555555556
130	302392	290110.3125	12281.6875
131	384345	292011.842105263	92333.1578947369
132	187992	191246.928571429	-3254.92857142858
133	102424	104493.928571429	-2069.92857142857
134	281117	292011.842105263	-10894.8421052631
135	399991	370981.944444444	29009.0555555556
136	131692	160551.95	-28859.95
137	371090	370981.944444444	108.055555555562
138	157429	160551.95	-3122.95000000001
139	236370	240646.789473684	-4276.78947368421
140	227299	219248.375	8050.625
141	209904	191246.928571429	18657.0714285714
142	355457	370981.944444444	-15524.9444444444
143	230883	240646.789473684	-9763.78947368421
144	173260	219248.375	-45988.375
145	306577	292011.842105263	14565.1578947369
146	141789	160551.95	-18762.95
147	210565	240646.789473684	-30081.7894736842
148	273544	290110.3125	-16566.3125
149	1	991.666666666667	-990.666666666667
150	14688	32384.8181818182	-17696.8181818182
151	98	991.666666666667	-893.666666666667
152	455	991.666666666667	-536.666666666667
153	0	991.666666666667	-991.666666666667
154	0	991.666666666667	-991.666666666667
155	216803	219248.375	-2445.375
156	347930	292011.842105263	55918.1578947369
157	0	991.666666666667	-991.666666666667
158	203	991.666666666667	-788.666666666667
159	7199	991.666666666667	6207.33333333333
160	46660	32384.8181818182	14275.1818181818
161	17547	32384.8181818182	-14837.8181818182
162	112892	104493.928571429	8398.07142857143
163	969	991.666666666667	-22.6666666666666
164	189334	160551.95	28782.05

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 269966 & 290110.3125 & -20144.3125 \tabularnewline
2 & 146082 & 104493.928571429 & 41588.0714285714 \tabularnewline
3 & 214542 & 191246.928571429 & 23295.0714285714 \tabularnewline
4 & 212452 & 219248.375 & -6796.375 \tabularnewline
5 & 157206 & 104493.928571429 & 52712.0714285714 \tabularnewline
6 & 70849 & 104493.928571429 & -33644.9285714286 \tabularnewline
7 & 476347 & 370981.944444444 & 105365.055555556 \tabularnewline
8 & 33186 & 32384.8181818182 & 801.18181818182 \tabularnewline
9 & 201983 & 219248.375 & -17265.375 \tabularnewline
10 & 211698 & 191246.928571429 & 20451.0714285714 \tabularnewline
11 & 292874 & 290110.3125 & 2763.6875 \tabularnewline
12 & 223814 & 219248.375 & 4565.625 \tabularnewline
13 & 156623 & 160551.95 & -3928.95000000001 \tabularnewline
14 & 327332 & 292011.842105263 & 35320.1578947369 \tabularnewline
15 & 205898 & 191246.928571429 & 14651.0714285714 \tabularnewline
16 & 369527 & 370981.944444444 & -1454.94444444444 \tabularnewline
17 & 290571 & 290110.3125 & 460.6875 \tabularnewline
18 & 292903 & 292011.842105263 & 891.157894736854 \tabularnewline
19 & 168639 & 191246.928571429 & -22607.9285714286 \tabularnewline
20 & 253641 & 240646.789473684 & 12994.2105263158 \tabularnewline
21 & 269240 & 240646.789473684 & 28593.2105263158 \tabularnewline
22 & 414808 & 370981.944444444 & 43826.0555555556 \tabularnewline
23 & 161910 & 191246.928571429 & -29336.9285714286 \tabularnewline
24 & 178722 & 191246.928571429 & -12524.9285714286 \tabularnewline
25 & 200181 & 292011.842105263 & -91830.8421052631 \tabularnewline
26 & 203700 & 219248.375 & -15548.375 \tabularnewline
27 & 267099 & 292011.842105263 & -24912.8421052631 \tabularnewline
28 & 262716 & 240646.789473684 & 22069.2105263158 \tabularnewline
29 & 155915 & 160551.95 & -4636.95000000001 \tabularnewline
30 & 324641 & 292011.842105263 & 32629.1578947369 \tabularnewline
31 & 261785 & 290110.3125 & -28325.3125 \tabularnewline
32 & 192626 & 191246.928571429 & 1379.07142857142 \tabularnewline
33 & 318563 & 290110.3125 & 28452.6875 \tabularnewline
34 & 97615 & 104493.928571429 & -6878.92857142857 \tabularnewline
35 & 343613 & 292011.842105263 & 51601.1578947369 \tabularnewline
36 & 272026 & 370981.944444444 & -98955.9444444444 \tabularnewline
37 & 408580 & 370981.944444444 & 37598.0555555556 \tabularnewline
38 & 206904 & 191246.928571429 & 15657.0714285714 \tabularnewline
39 & 115469 & 104493.928571429 & 10975.0714285714 \tabularnewline
40 & 310587 & 292011.842105263 & 18575.1578947369 \tabularnewline
41 & 315746 & 370981.944444444 & -55235.9444444444 \tabularnewline
42 & 157897 & 160551.95 & -2654.95000000001 \tabularnewline
43 & 192883 & 240646.789473684 & -47763.7894736842 \tabularnewline
44 & 165876 & 160551.95 & 5324.04999999999 \tabularnewline
45 & 153778 & 219248.375 & -65470.375 \tabularnewline
46 & 414493 & 370981.944444444 & 43511.0555555556 \tabularnewline
47 & 78800 & 104493.928571429 & -25693.9285714286 \tabularnewline
48 & 207958 & 219248.375 & -11290.375 \tabularnewline
49 & 323118 & 370981.944444444 & -47863.9444444444 \tabularnewline
50 & 175523 & 219248.375 & -43725.375 \tabularnewline
51 & 213050 & 240646.789473684 & -27596.7894736842 \tabularnewline
52 & 24188 & 32384.8181818182 & -8196.81818181818 \tabularnewline
53 & 364968 & 290110.3125 & 74857.6875 \tabularnewline
54 & 65029 & 104493.928571429 & -39464.9285714286 \tabularnewline
55 & 101097 & 104493.928571429 & -3396.92857142857 \tabularnewline
56 & 263096 & 292011.842105263 & -28915.8421052631 \tabularnewline
57 & 302012 & 290110.3125 & 11901.6875 \tabularnewline
58 & 315753 & 292011.842105263 & 23741.1578947369 \tabularnewline
59 & 300531 & 290110.3125 & 10420.6875 \tabularnewline
60 & 240445 & 219248.375 & 21196.625 \tabularnewline
61 & 360325 & 370981.944444444 & -10656.9444444444 \tabularnewline
62 & 296186 & 292011.842105263 & 4174.15789473685 \tabularnewline
63 & 210104 & 219248.375 & -9144.375 \tabularnewline
64 & 247076 & 240646.789473684 & 6429.21052631579 \tabularnewline
65 & 220722 & 240646.789473684 & -19924.7894736842 \tabularnewline
66 & 216027 & 240646.789473684 & -24619.7894736842 \tabularnewline
67 & 187773 & 191246.928571429 & -3473.92857142858 \tabularnewline
68 & 227055 & 240646.789473684 & -13591.7894736842 \tabularnewline
69 & 229181 & 219248.375 & 9932.625 \tabularnewline
70 & 159082 & 160551.95 & -1469.95000000001 \tabularnewline
71 & 232624 & 219248.375 & 13375.625 \tabularnewline
72 & 73566 & 104493.928571429 & -30927.9285714286 \tabularnewline
73 & 231827 & 219248.375 & 12578.625 \tabularnewline
74 & 181728 & 160551.95 & 21176.05 \tabularnewline
75 & 162366 & 160551.95 & 1814.04999999999 \tabularnewline
76 & 329583 & 219248.375 & 110334.625 \tabularnewline
77 & 303317 & 290110.3125 & 13206.6875 \tabularnewline
78 & 205630 & 290110.3125 & -84480.3125 \tabularnewline
79 & 184970 & 219248.375 & -34278.375 \tabularnewline
80 & 168990 & 160551.95 & 8438.04999999999 \tabularnewline
81 & 151231 & 160551.95 & -9320.95000000001 \tabularnewline
82 & 421615 & 370981.944444444 & 50633.0555555556 \tabularnewline
83 & 145916 & 160551.95 & -14635.95 \tabularnewline
84 & 270487 & 240646.789473684 & 29840.2105263158 \tabularnewline
85 & 80953 & 104493.928571429 & -23540.9285714286 \tabularnewline
86 & 139193 & 160551.95 & -21358.95 \tabularnewline
87 & 146777 & 104493.928571429 & 42283.0714285714 \tabularnewline
88 & 335969 & 370981.944444444 & -35012.9444444444 \tabularnewline
89 & 297676 & 290110.3125 & 7565.6875 \tabularnewline
90 & 175232 & 292011.842105263 & -116779.842105263 \tabularnewline
91 & 238938 & 219248.375 & 19689.625 \tabularnewline
92 & 228459 & 219248.375 & 9210.625 \tabularnewline
93 & 175244 & 160551.95 & 14692.05 \tabularnewline
94 & 256299 & 292011.842105263 & -35712.8421052631 \tabularnewline
95 & 288728 & 240646.789473684 & 48081.2105263158 \tabularnewline
96 & 189252 & 191246.928571429 & -1994.92857142858 \tabularnewline
97 & 222324 & 240646.789473684 & -18322.7894736842 \tabularnewline
98 & 277755 & 290110.3125 & -12355.3125 \tabularnewline
99 & 364710 & 370981.944444444 & -6271.94444444444 \tabularnewline
100 & 392346 & 370981.944444444 & 21364.0555555556 \tabularnewline
101 & 260478 & 219248.375 & 41229.625 \tabularnewline
102 & 273240 & 290110.3125 & -16870.3125 \tabularnewline
103 & 186310 & 219248.375 & -32938.375 \tabularnewline
104 & 43287 & 32384.8181818182 & 10902.1818181818 \tabularnewline
105 & 185181 & 219248.375 & -34067.375 \tabularnewline
106 & 202989 & 240646.789473684 & -37657.7894736842 \tabularnewline
107 & 259498 & 240646.789473684 & 18851.2105263158 \tabularnewline
108 & 295230 & 240646.789473684 & 54583.2105263158 \tabularnewline
109 & 114156 & 104493.928571429 & 9662.07142857143 \tabularnewline
110 & 151624 & 292011.842105263 & -140387.842105263 \tabularnewline
111 & 306941 & 290110.3125 & 16830.6875 \tabularnewline
112 & 289398 & 219248.375 & 70149.625 \tabularnewline
113 & 23623 & 32384.8181818182 & -8761.81818181818 \tabularnewline
114 & 174970 & 191246.928571429 & -16276.9285714286 \tabularnewline
115 & 61857 & 32384.8181818182 & 29472.1818181818 \tabularnewline
116 & 163766 & 160551.95 & 3214.04999999999 \tabularnewline
117 & 364027 & 292011.842105263 & 72015.1578947369 \tabularnewline
118 & 21054 & 32384.8181818182 & -11330.8181818182 \tabularnewline
119 & 252805 & 240646.789473684 & 12158.2105263158 \tabularnewline
120 & 31929 & 32384.8181818182 & -455.81818181818 \tabularnewline
121 & 294609 & 370981.944444444 & -76372.9444444444 \tabularnewline
122 & 217893 & 219248.375 & -1355.375 \tabularnewline
123 & 167612 & 160551.95 & 7060.04999999999 \tabularnewline
124 & 149905 & 160551.95 & -10646.95 \tabularnewline
125 & 38214 & 32384.8181818182 & 5829.18181818182 \tabularnewline
126 & 189451 & 160551.95 & 28899.05 \tabularnewline
127 & 339683 & 292011.842105263 & 47671.1578947369 \tabularnewline
128 & 186627 & 191246.928571429 & -4619.92857142858 \tabularnewline
129 & 386918 & 370981.944444444 & 15936.0555555556 \tabularnewline
130 & 302392 & 290110.3125 & 12281.6875 \tabularnewline
131 & 384345 & 292011.842105263 & 92333.1578947369 \tabularnewline
132 & 187992 & 191246.928571429 & -3254.92857142858 \tabularnewline
133 & 102424 & 104493.928571429 & -2069.92857142857 \tabularnewline
134 & 281117 & 292011.842105263 & -10894.8421052631 \tabularnewline
135 & 399991 & 370981.944444444 & 29009.0555555556 \tabularnewline
136 & 131692 & 160551.95 & -28859.95 \tabularnewline
137 & 371090 & 370981.944444444 & 108.055555555562 \tabularnewline
138 & 157429 & 160551.95 & -3122.95000000001 \tabularnewline
139 & 236370 & 240646.789473684 & -4276.78947368421 \tabularnewline
140 & 227299 & 219248.375 & 8050.625 \tabularnewline
141 & 209904 & 191246.928571429 & 18657.0714285714 \tabularnewline
142 & 355457 & 370981.944444444 & -15524.9444444444 \tabularnewline
143 & 230883 & 240646.789473684 & -9763.78947368421 \tabularnewline
144 & 173260 & 219248.375 & -45988.375 \tabularnewline
145 & 306577 & 292011.842105263 & 14565.1578947369 \tabularnewline
146 & 141789 & 160551.95 & -18762.95 \tabularnewline
147 & 210565 & 240646.789473684 & -30081.7894736842 \tabularnewline
148 & 273544 & 290110.3125 & -16566.3125 \tabularnewline
149 & 1 & 991.666666666667 & -990.666666666667 \tabularnewline
150 & 14688 & 32384.8181818182 & -17696.8181818182 \tabularnewline
151 & 98 & 991.666666666667 & -893.666666666667 \tabularnewline
152 & 455 & 991.666666666667 & -536.666666666667 \tabularnewline
153 & 0 & 991.666666666667 & -991.666666666667 \tabularnewline
154 & 0 & 991.666666666667 & -991.666666666667 \tabularnewline
155 & 216803 & 219248.375 & -2445.375 \tabularnewline
156 & 347930 & 292011.842105263 & 55918.1578947369 \tabularnewline
157 & 0 & 991.666666666667 & -991.666666666667 \tabularnewline
158 & 203 & 991.666666666667 & -788.666666666667 \tabularnewline
159 & 7199 & 991.666666666667 & 6207.33333333333 \tabularnewline
160 & 46660 & 32384.8181818182 & 14275.1818181818 \tabularnewline
161 & 17547 & 32384.8181818182 & -14837.8181818182 \tabularnewline
162 & 112892 & 104493.928571429 & 8398.07142857143 \tabularnewline
163 & 969 & 991.666666666667 & -22.6666666666666 \tabularnewline
164 & 189334 & 160551.95 & 28782.05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155031&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]269966[/C][C]290110.3125[/C][C]-20144.3125[/C][/ROW]
[ROW][C]2[/C][C]146082[/C][C]104493.928571429[/C][C]41588.0714285714[/C][/ROW]
[ROW][C]3[/C][C]214542[/C][C]191246.928571429[/C][C]23295.0714285714[/C][/ROW]
[ROW][C]4[/C][C]212452[/C][C]219248.375[/C][C]-6796.375[/C][/ROW]
[ROW][C]5[/C][C]157206[/C][C]104493.928571429[/C][C]52712.0714285714[/C][/ROW]
[ROW][C]6[/C][C]70849[/C][C]104493.928571429[/C][C]-33644.9285714286[/C][/ROW]
[ROW][C]7[/C][C]476347[/C][C]370981.944444444[/C][C]105365.055555556[/C][/ROW]
[ROW][C]8[/C][C]33186[/C][C]32384.8181818182[/C][C]801.18181818182[/C][/ROW]
[ROW][C]9[/C][C]201983[/C][C]219248.375[/C][C]-17265.375[/C][/ROW]
[ROW][C]10[/C][C]211698[/C][C]191246.928571429[/C][C]20451.0714285714[/C][/ROW]
[ROW][C]11[/C][C]292874[/C][C]290110.3125[/C][C]2763.6875[/C][/ROW]
[ROW][C]12[/C][C]223814[/C][C]219248.375[/C][C]4565.625[/C][/ROW]
[ROW][C]13[/C][C]156623[/C][C]160551.95[/C][C]-3928.95000000001[/C][/ROW]
[ROW][C]14[/C][C]327332[/C][C]292011.842105263[/C][C]35320.1578947369[/C][/ROW]
[ROW][C]15[/C][C]205898[/C][C]191246.928571429[/C][C]14651.0714285714[/C][/ROW]
[ROW][C]16[/C][C]369527[/C][C]370981.944444444[/C][C]-1454.94444444444[/C][/ROW]
[ROW][C]17[/C][C]290571[/C][C]290110.3125[/C][C]460.6875[/C][/ROW]
[ROW][C]18[/C][C]292903[/C][C]292011.842105263[/C][C]891.157894736854[/C][/ROW]
[ROW][C]19[/C][C]168639[/C][C]191246.928571429[/C][C]-22607.9285714286[/C][/ROW]
[ROW][C]20[/C][C]253641[/C][C]240646.789473684[/C][C]12994.2105263158[/C][/ROW]
[ROW][C]21[/C][C]269240[/C][C]240646.789473684[/C][C]28593.2105263158[/C][/ROW]
[ROW][C]22[/C][C]414808[/C][C]370981.944444444[/C][C]43826.0555555556[/C][/ROW]
[ROW][C]23[/C][C]161910[/C][C]191246.928571429[/C][C]-29336.9285714286[/C][/ROW]
[ROW][C]24[/C][C]178722[/C][C]191246.928571429[/C][C]-12524.9285714286[/C][/ROW]
[ROW][C]25[/C][C]200181[/C][C]292011.842105263[/C][C]-91830.8421052631[/C][/ROW]
[ROW][C]26[/C][C]203700[/C][C]219248.375[/C][C]-15548.375[/C][/ROW]
[ROW][C]27[/C][C]267099[/C][C]292011.842105263[/C][C]-24912.8421052631[/C][/ROW]
[ROW][C]28[/C][C]262716[/C][C]240646.789473684[/C][C]22069.2105263158[/C][/ROW]
[ROW][C]29[/C][C]155915[/C][C]160551.95[/C][C]-4636.95000000001[/C][/ROW]
[ROW][C]30[/C][C]324641[/C][C]292011.842105263[/C][C]32629.1578947369[/C][/ROW]
[ROW][C]31[/C][C]261785[/C][C]290110.3125[/C][C]-28325.3125[/C][/ROW]
[ROW][C]32[/C][C]192626[/C][C]191246.928571429[/C][C]1379.07142857142[/C][/ROW]
[ROW][C]33[/C][C]318563[/C][C]290110.3125[/C][C]28452.6875[/C][/ROW]
[ROW][C]34[/C][C]97615[/C][C]104493.928571429[/C][C]-6878.92857142857[/C][/ROW]
[ROW][C]35[/C][C]343613[/C][C]292011.842105263[/C][C]51601.1578947369[/C][/ROW]
[ROW][C]36[/C][C]272026[/C][C]370981.944444444[/C][C]-98955.9444444444[/C][/ROW]
[ROW][C]37[/C][C]408580[/C][C]370981.944444444[/C][C]37598.0555555556[/C][/ROW]
[ROW][C]38[/C][C]206904[/C][C]191246.928571429[/C][C]15657.0714285714[/C][/ROW]
[ROW][C]39[/C][C]115469[/C][C]104493.928571429[/C][C]10975.0714285714[/C][/ROW]
[ROW][C]40[/C][C]310587[/C][C]292011.842105263[/C][C]18575.1578947369[/C][/ROW]
[ROW][C]41[/C][C]315746[/C][C]370981.944444444[/C][C]-55235.9444444444[/C][/ROW]
[ROW][C]42[/C][C]157897[/C][C]160551.95[/C][C]-2654.95000000001[/C][/ROW]
[ROW][C]43[/C][C]192883[/C][C]240646.789473684[/C][C]-47763.7894736842[/C][/ROW]
[ROW][C]44[/C][C]165876[/C][C]160551.95[/C][C]5324.04999999999[/C][/ROW]
[ROW][C]45[/C][C]153778[/C][C]219248.375[/C][C]-65470.375[/C][/ROW]
[ROW][C]46[/C][C]414493[/C][C]370981.944444444[/C][C]43511.0555555556[/C][/ROW]
[ROW][C]47[/C][C]78800[/C][C]104493.928571429[/C][C]-25693.9285714286[/C][/ROW]
[ROW][C]48[/C][C]207958[/C][C]219248.375[/C][C]-11290.375[/C][/ROW]
[ROW][C]49[/C][C]323118[/C][C]370981.944444444[/C][C]-47863.9444444444[/C][/ROW]
[ROW][C]50[/C][C]175523[/C][C]219248.375[/C][C]-43725.375[/C][/ROW]
[ROW][C]51[/C][C]213050[/C][C]240646.789473684[/C][C]-27596.7894736842[/C][/ROW]
[ROW][C]52[/C][C]24188[/C][C]32384.8181818182[/C][C]-8196.81818181818[/C][/ROW]
[ROW][C]53[/C][C]364968[/C][C]290110.3125[/C][C]74857.6875[/C][/ROW]
[ROW][C]54[/C][C]65029[/C][C]104493.928571429[/C][C]-39464.9285714286[/C][/ROW]
[ROW][C]55[/C][C]101097[/C][C]104493.928571429[/C][C]-3396.92857142857[/C][/ROW]
[ROW][C]56[/C][C]263096[/C][C]292011.842105263[/C][C]-28915.8421052631[/C][/ROW]
[ROW][C]57[/C][C]302012[/C][C]290110.3125[/C][C]11901.6875[/C][/ROW]
[ROW][C]58[/C][C]315753[/C][C]292011.842105263[/C][C]23741.1578947369[/C][/ROW]
[ROW][C]59[/C][C]300531[/C][C]290110.3125[/C][C]10420.6875[/C][/ROW]
[ROW][C]60[/C][C]240445[/C][C]219248.375[/C][C]21196.625[/C][/ROW]
[ROW][C]61[/C][C]360325[/C][C]370981.944444444[/C][C]-10656.9444444444[/C][/ROW]
[ROW][C]62[/C][C]296186[/C][C]292011.842105263[/C][C]4174.15789473685[/C][/ROW]
[ROW][C]63[/C][C]210104[/C][C]219248.375[/C][C]-9144.375[/C][/ROW]
[ROW][C]64[/C][C]247076[/C][C]240646.789473684[/C][C]6429.21052631579[/C][/ROW]
[ROW][C]65[/C][C]220722[/C][C]240646.789473684[/C][C]-19924.7894736842[/C][/ROW]
[ROW][C]66[/C][C]216027[/C][C]240646.789473684[/C][C]-24619.7894736842[/C][/ROW]
[ROW][C]67[/C][C]187773[/C][C]191246.928571429[/C][C]-3473.92857142858[/C][/ROW]
[ROW][C]68[/C][C]227055[/C][C]240646.789473684[/C][C]-13591.7894736842[/C][/ROW]
[ROW][C]69[/C][C]229181[/C][C]219248.375[/C][C]9932.625[/C][/ROW]
[ROW][C]70[/C][C]159082[/C][C]160551.95[/C][C]-1469.95000000001[/C][/ROW]
[ROW][C]71[/C][C]232624[/C][C]219248.375[/C][C]13375.625[/C][/ROW]
[ROW][C]72[/C][C]73566[/C][C]104493.928571429[/C][C]-30927.9285714286[/C][/ROW]
[ROW][C]73[/C][C]231827[/C][C]219248.375[/C][C]12578.625[/C][/ROW]
[ROW][C]74[/C][C]181728[/C][C]160551.95[/C][C]21176.05[/C][/ROW]
[ROW][C]75[/C][C]162366[/C][C]160551.95[/C][C]1814.04999999999[/C][/ROW]
[ROW][C]76[/C][C]329583[/C][C]219248.375[/C][C]110334.625[/C][/ROW]
[ROW][C]77[/C][C]303317[/C][C]290110.3125[/C][C]13206.6875[/C][/ROW]
[ROW][C]78[/C][C]205630[/C][C]290110.3125[/C][C]-84480.3125[/C][/ROW]
[ROW][C]79[/C][C]184970[/C][C]219248.375[/C][C]-34278.375[/C][/ROW]
[ROW][C]80[/C][C]168990[/C][C]160551.95[/C][C]8438.04999999999[/C][/ROW]
[ROW][C]81[/C][C]151231[/C][C]160551.95[/C][C]-9320.95000000001[/C][/ROW]
[ROW][C]82[/C][C]421615[/C][C]370981.944444444[/C][C]50633.0555555556[/C][/ROW]
[ROW][C]83[/C][C]145916[/C][C]160551.95[/C][C]-14635.95[/C][/ROW]
[ROW][C]84[/C][C]270487[/C][C]240646.789473684[/C][C]29840.2105263158[/C][/ROW]
[ROW][C]85[/C][C]80953[/C][C]104493.928571429[/C][C]-23540.9285714286[/C][/ROW]
[ROW][C]86[/C][C]139193[/C][C]160551.95[/C][C]-21358.95[/C][/ROW]
[ROW][C]87[/C][C]146777[/C][C]104493.928571429[/C][C]42283.0714285714[/C][/ROW]
[ROW][C]88[/C][C]335969[/C][C]370981.944444444[/C][C]-35012.9444444444[/C][/ROW]
[ROW][C]89[/C][C]297676[/C][C]290110.3125[/C][C]7565.6875[/C][/ROW]
[ROW][C]90[/C][C]175232[/C][C]292011.842105263[/C][C]-116779.842105263[/C][/ROW]
[ROW][C]91[/C][C]238938[/C][C]219248.375[/C][C]19689.625[/C][/ROW]
[ROW][C]92[/C][C]228459[/C][C]219248.375[/C][C]9210.625[/C][/ROW]
[ROW][C]93[/C][C]175244[/C][C]160551.95[/C][C]14692.05[/C][/ROW]
[ROW][C]94[/C][C]256299[/C][C]292011.842105263[/C][C]-35712.8421052631[/C][/ROW]
[ROW][C]95[/C][C]288728[/C][C]240646.789473684[/C][C]48081.2105263158[/C][/ROW]
[ROW][C]96[/C][C]189252[/C][C]191246.928571429[/C][C]-1994.92857142858[/C][/ROW]
[ROW][C]97[/C][C]222324[/C][C]240646.789473684[/C][C]-18322.7894736842[/C][/ROW]
[ROW][C]98[/C][C]277755[/C][C]290110.3125[/C][C]-12355.3125[/C][/ROW]
[ROW][C]99[/C][C]364710[/C][C]370981.944444444[/C][C]-6271.94444444444[/C][/ROW]
[ROW][C]100[/C][C]392346[/C][C]370981.944444444[/C][C]21364.0555555556[/C][/ROW]
[ROW][C]101[/C][C]260478[/C][C]219248.375[/C][C]41229.625[/C][/ROW]
[ROW][C]102[/C][C]273240[/C][C]290110.3125[/C][C]-16870.3125[/C][/ROW]
[ROW][C]103[/C][C]186310[/C][C]219248.375[/C][C]-32938.375[/C][/ROW]
[ROW][C]104[/C][C]43287[/C][C]32384.8181818182[/C][C]10902.1818181818[/C][/ROW]
[ROW][C]105[/C][C]185181[/C][C]219248.375[/C][C]-34067.375[/C][/ROW]
[ROW][C]106[/C][C]202989[/C][C]240646.789473684[/C][C]-37657.7894736842[/C][/ROW]
[ROW][C]107[/C][C]259498[/C][C]240646.789473684[/C][C]18851.2105263158[/C][/ROW]
[ROW][C]108[/C][C]295230[/C][C]240646.789473684[/C][C]54583.2105263158[/C][/ROW]
[ROW][C]109[/C][C]114156[/C][C]104493.928571429[/C][C]9662.07142857143[/C][/ROW]
[ROW][C]110[/C][C]151624[/C][C]292011.842105263[/C][C]-140387.842105263[/C][/ROW]
[ROW][C]111[/C][C]306941[/C][C]290110.3125[/C][C]16830.6875[/C][/ROW]
[ROW][C]112[/C][C]289398[/C][C]219248.375[/C][C]70149.625[/C][/ROW]
[ROW][C]113[/C][C]23623[/C][C]32384.8181818182[/C][C]-8761.81818181818[/C][/ROW]
[ROW][C]114[/C][C]174970[/C][C]191246.928571429[/C][C]-16276.9285714286[/C][/ROW]
[ROW][C]115[/C][C]61857[/C][C]32384.8181818182[/C][C]29472.1818181818[/C][/ROW]
[ROW][C]116[/C][C]163766[/C][C]160551.95[/C][C]3214.04999999999[/C][/ROW]
[ROW][C]117[/C][C]364027[/C][C]292011.842105263[/C][C]72015.1578947369[/C][/ROW]
[ROW][C]118[/C][C]21054[/C][C]32384.8181818182[/C][C]-11330.8181818182[/C][/ROW]
[ROW][C]119[/C][C]252805[/C][C]240646.789473684[/C][C]12158.2105263158[/C][/ROW]
[ROW][C]120[/C][C]31929[/C][C]32384.8181818182[/C][C]-455.81818181818[/C][/ROW]
[ROW][C]121[/C][C]294609[/C][C]370981.944444444[/C][C]-76372.9444444444[/C][/ROW]
[ROW][C]122[/C][C]217893[/C][C]219248.375[/C][C]-1355.375[/C][/ROW]
[ROW][C]123[/C][C]167612[/C][C]160551.95[/C][C]7060.04999999999[/C][/ROW]
[ROW][C]124[/C][C]149905[/C][C]160551.95[/C][C]-10646.95[/C][/ROW]
[ROW][C]125[/C][C]38214[/C][C]32384.8181818182[/C][C]5829.18181818182[/C][/ROW]
[ROW][C]126[/C][C]189451[/C][C]160551.95[/C][C]28899.05[/C][/ROW]
[ROW][C]127[/C][C]339683[/C][C]292011.842105263[/C][C]47671.1578947369[/C][/ROW]
[ROW][C]128[/C][C]186627[/C][C]191246.928571429[/C][C]-4619.92857142858[/C][/ROW]
[ROW][C]129[/C][C]386918[/C][C]370981.944444444[/C][C]15936.0555555556[/C][/ROW]
[ROW][C]130[/C][C]302392[/C][C]290110.3125[/C][C]12281.6875[/C][/ROW]
[ROW][C]131[/C][C]384345[/C][C]292011.842105263[/C][C]92333.1578947369[/C][/ROW]
[ROW][C]132[/C][C]187992[/C][C]191246.928571429[/C][C]-3254.92857142858[/C][/ROW]
[ROW][C]133[/C][C]102424[/C][C]104493.928571429[/C][C]-2069.92857142857[/C][/ROW]
[ROW][C]134[/C][C]281117[/C][C]292011.842105263[/C][C]-10894.8421052631[/C][/ROW]
[ROW][C]135[/C][C]399991[/C][C]370981.944444444[/C][C]29009.0555555556[/C][/ROW]
[ROW][C]136[/C][C]131692[/C][C]160551.95[/C][C]-28859.95[/C][/ROW]
[ROW][C]137[/C][C]371090[/C][C]370981.944444444[/C][C]108.055555555562[/C][/ROW]
[ROW][C]138[/C][C]157429[/C][C]160551.95[/C][C]-3122.95000000001[/C][/ROW]
[ROW][C]139[/C][C]236370[/C][C]240646.789473684[/C][C]-4276.78947368421[/C][/ROW]
[ROW][C]140[/C][C]227299[/C][C]219248.375[/C][C]8050.625[/C][/ROW]
[ROW][C]141[/C][C]209904[/C][C]191246.928571429[/C][C]18657.0714285714[/C][/ROW]
[ROW][C]142[/C][C]355457[/C][C]370981.944444444[/C][C]-15524.9444444444[/C][/ROW]
[ROW][C]143[/C][C]230883[/C][C]240646.789473684[/C][C]-9763.78947368421[/C][/ROW]
[ROW][C]144[/C][C]173260[/C][C]219248.375[/C][C]-45988.375[/C][/ROW]
[ROW][C]145[/C][C]306577[/C][C]292011.842105263[/C][C]14565.1578947369[/C][/ROW]
[ROW][C]146[/C][C]141789[/C][C]160551.95[/C][C]-18762.95[/C][/ROW]
[ROW][C]147[/C][C]210565[/C][C]240646.789473684[/C][C]-30081.7894736842[/C][/ROW]
[ROW][C]148[/C][C]273544[/C][C]290110.3125[/C][C]-16566.3125[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]991.666666666667[/C][C]-990.666666666667[/C][/ROW]
[ROW][C]150[/C][C]14688[/C][C]32384.8181818182[/C][C]-17696.8181818182[/C][/ROW]
[ROW][C]151[/C][C]98[/C][C]991.666666666667[/C][C]-893.666666666667[/C][/ROW]
[ROW][C]152[/C][C]455[/C][C]991.666666666667[/C][C]-536.666666666667[/C][/ROW]
[ROW][C]153[/C][C]0[/C][C]991.666666666667[/C][C]-991.666666666667[/C][/ROW]
[ROW][C]154[/C][C]0[/C][C]991.666666666667[/C][C]-991.666666666667[/C][/ROW]
[ROW][C]155[/C][C]216803[/C][C]219248.375[/C][C]-2445.375[/C][/ROW]
[ROW][C]156[/C][C]347930[/C][C]292011.842105263[/C][C]55918.1578947369[/C][/ROW]
[ROW][C]157[/C][C]0[/C][C]991.666666666667[/C][C]-991.666666666667[/C][/ROW]
[ROW][C]158[/C][C]203[/C][C]991.666666666667[/C][C]-788.666666666667[/C][/ROW]
[ROW][C]159[/C][C]7199[/C][C]991.666666666667[/C][C]6207.33333333333[/C][/ROW]
[ROW][C]160[/C][C]46660[/C][C]32384.8181818182[/C][C]14275.1818181818[/C][/ROW]
[ROW][C]161[/C][C]17547[/C][C]32384.8181818182[/C][C]-14837.8181818182[/C][/ROW]
[ROW][C]162[/C][C]112892[/C][C]104493.928571429[/C][C]8398.07142857143[/C][/ROW]
[ROW][C]163[/C][C]969[/C][C]991.666666666667[/C][C]-22.6666666666666[/C][/ROW]
[ROW][C]164[/C][C]189334[/C][C]160551.95[/C][C]28782.05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155031&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155031&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	269966	290110.3125	-20144.3125
2	146082	104493.928571429	41588.0714285714
3	214542	191246.928571429	23295.0714285714
4	212452	219248.375	-6796.375
5	157206	104493.928571429	52712.0714285714
6	70849	104493.928571429	-33644.9285714286
7	476347	370981.944444444	105365.055555556
8	33186	32384.8181818182	801.18181818182
9	201983	219248.375	-17265.375
10	211698	191246.928571429	20451.0714285714
11	292874	290110.3125	2763.6875
12	223814	219248.375	4565.625
13	156623	160551.95	-3928.95000000001
14	327332	292011.842105263	35320.1578947369
15	205898	191246.928571429	14651.0714285714
16	369527	370981.944444444	-1454.94444444444
17	290571	290110.3125	460.6875
18	292903	292011.842105263	891.157894736854
19	168639	191246.928571429	-22607.9285714286
20	253641	240646.789473684	12994.2105263158
21	269240	240646.789473684	28593.2105263158
22	414808	370981.944444444	43826.0555555556
23	161910	191246.928571429	-29336.9285714286
24	178722	191246.928571429	-12524.9285714286
25	200181	292011.842105263	-91830.8421052631
26	203700	219248.375	-15548.375
27	267099	292011.842105263	-24912.8421052631
28	262716	240646.789473684	22069.2105263158
29	155915	160551.95	-4636.95000000001
30	324641	292011.842105263	32629.1578947369
31	261785	290110.3125	-28325.3125
32	192626	191246.928571429	1379.07142857142
33	318563	290110.3125	28452.6875
34	97615	104493.928571429	-6878.92857142857
35	343613	292011.842105263	51601.1578947369
36	272026	370981.944444444	-98955.9444444444
37	408580	370981.944444444	37598.0555555556
38	206904	191246.928571429	15657.0714285714
39	115469	104493.928571429	10975.0714285714
40	310587	292011.842105263	18575.1578947369
41	315746	370981.944444444	-55235.9444444444
42	157897	160551.95	-2654.95000000001
43	192883	240646.789473684	-47763.7894736842
44	165876	160551.95	5324.04999999999
45	153778	219248.375	-65470.375
46	414493	370981.944444444	43511.0555555556
47	78800	104493.928571429	-25693.9285714286
48	207958	219248.375	-11290.375
49	323118	370981.944444444	-47863.9444444444
50	175523	219248.375	-43725.375
51	213050	240646.789473684	-27596.7894736842
52	24188	32384.8181818182	-8196.81818181818
53	364968	290110.3125	74857.6875
54	65029	104493.928571429	-39464.9285714286
55	101097	104493.928571429	-3396.92857142857
56	263096	292011.842105263	-28915.8421052631
57	302012	290110.3125	11901.6875
58	315753	292011.842105263	23741.1578947369
59	300531	290110.3125	10420.6875
60	240445	219248.375	21196.625
61	360325	370981.944444444	-10656.9444444444
62	296186	292011.842105263	4174.15789473685
63	210104	219248.375	-9144.375
64	247076	240646.789473684	6429.21052631579
65	220722	240646.789473684	-19924.7894736842
66	216027	240646.789473684	-24619.7894736842
67	187773	191246.928571429	-3473.92857142858
68	227055	240646.789473684	-13591.7894736842
69	229181	219248.375	9932.625
70	159082	160551.95	-1469.95000000001
71	232624	219248.375	13375.625
72	73566	104493.928571429	-30927.9285714286
73	231827	219248.375	12578.625
74	181728	160551.95	21176.05
75	162366	160551.95	1814.04999999999
76	329583	219248.375	110334.625
77	303317	290110.3125	13206.6875
78	205630	290110.3125	-84480.3125
79	184970	219248.375	-34278.375
80	168990	160551.95	8438.04999999999
81	151231	160551.95	-9320.95000000001
82	421615	370981.944444444	50633.0555555556
83	145916	160551.95	-14635.95
84	270487	240646.789473684	29840.2105263158
85	80953	104493.928571429	-23540.9285714286
86	139193	160551.95	-21358.95
87	146777	104493.928571429	42283.0714285714
88	335969	370981.944444444	-35012.9444444444
89	297676	290110.3125	7565.6875
90	175232	292011.842105263	-116779.842105263
91	238938	219248.375	19689.625
92	228459	219248.375	9210.625
93	175244	160551.95	14692.05
94	256299	292011.842105263	-35712.8421052631
95	288728	240646.789473684	48081.2105263158
96	189252	191246.928571429	-1994.92857142858
97	222324	240646.789473684	-18322.7894736842
98	277755	290110.3125	-12355.3125
99	364710	370981.944444444	-6271.94444444444
100	392346	370981.944444444	21364.0555555556
101	260478	219248.375	41229.625
102	273240	290110.3125	-16870.3125
103	186310	219248.375	-32938.375
104	43287	32384.8181818182	10902.1818181818
105	185181	219248.375	-34067.375
106	202989	240646.789473684	-37657.7894736842
107	259498	240646.789473684	18851.2105263158
108	295230	240646.789473684	54583.2105263158
109	114156	104493.928571429	9662.07142857143
110	151624	292011.842105263	-140387.842105263
111	306941	290110.3125	16830.6875
112	289398	219248.375	70149.625
113	23623	32384.8181818182	-8761.81818181818
114	174970	191246.928571429	-16276.9285714286
115	61857	32384.8181818182	29472.1818181818
116	163766	160551.95	3214.04999999999
117	364027	292011.842105263	72015.1578947369
118	21054	32384.8181818182	-11330.8181818182
119	252805	240646.789473684	12158.2105263158
120	31929	32384.8181818182	-455.81818181818
121	294609	370981.944444444	-76372.9444444444
122	217893	219248.375	-1355.375
123	167612	160551.95	7060.04999999999
124	149905	160551.95	-10646.95
125	38214	32384.8181818182	5829.18181818182
126	189451	160551.95	28899.05
127	339683	292011.842105263	47671.1578947369
128	186627	191246.928571429	-4619.92857142858
129	386918	370981.944444444	15936.0555555556
130	302392	290110.3125	12281.6875
131	384345	292011.842105263	92333.1578947369
132	187992	191246.928571429	-3254.92857142858
133	102424	104493.928571429	-2069.92857142857
134	281117	292011.842105263	-10894.8421052631
135	399991	370981.944444444	29009.0555555556
136	131692	160551.95	-28859.95
137	371090	370981.944444444	108.055555555562
138	157429	160551.95	-3122.95000000001
139	236370	240646.789473684	-4276.78947368421
140	227299	219248.375	8050.625
141	209904	191246.928571429	18657.0714285714
142	355457	370981.944444444	-15524.9444444444
143	230883	240646.789473684	-9763.78947368421
144	173260	219248.375	-45988.375
145	306577	292011.842105263	14565.1578947369
146	141789	160551.95	-18762.95
147	210565	240646.789473684	-30081.7894736842
148	273544	290110.3125	-16566.3125
149	1	991.666666666667	-990.666666666667
150	14688	32384.8181818182	-17696.8181818182
151	98	991.666666666667	-893.666666666667
152	455	991.666666666667	-536.666666666667
153	0	991.666666666667	-991.666666666667
154	0	991.666666666667	-991.666666666667
155	216803	219248.375	-2445.375
156	347930	292011.842105263	55918.1578947369
157	0	991.666666666667	-991.666666666667
158	203	991.666666666667	-788.666666666667
159	7199	991.666666666667	6207.33333333333
160	46660	32384.8181818182	14275.1818181818
161	17547	32384.8181818182	-14837.8181818182
162	112892	104493.928571429	8398.07142857143
163	969	991.666666666667	-22.6666666666666
164	189334	160551.95	28782.05

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 = 2 ; par2 = none ; par4 = no ;

Parameters (R input):

par1 = 2 ; 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