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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

Fri, 23 Dec 2011 11:14:37 -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/23/t1324656910tixg7jvg90mebm7.htm/, Retrieved Mon, 29 Apr 2024 19:19:04 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160552, Retrieved Mon, 29 Apr 2024 19:19:04 +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] [] [2010-12-05 18:04:16] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kendall tau Correlation Matrix] [Kendall's Tau Cor...] [2011-12-09 12:39:26] [74b1e5a3104ff0b2404b2865a63336ad]
-   PD    [Kendall tau Correlation Matrix] [Kendall's Tau Cor...] [2011-12-09 13:55:36] [74b1e5a3104ff0b2404b2865a63336ad]
-   P       [Kendall tau Correlation Matrix] [] [2011-12-23 14:03:51] [74be16979710d4c4e7c6647856088456]
- RMPD          [Recursive Partitioning (Regression Trees)] [Paper 18] [2011-12-23 16:14:37] [8829043a11b4adcf2fcb2d15cd36bb4f] [Current]
-                 [Recursive Partitioning (Regression Trees)] [Paper 19] [2011-12-23 16:28:41] [ec29c78521a0445a37e4526edb78f709] 
- R                 [Recursive Partitioning (Regression Trees)] [Paper 20] [2011-12-23 16:34:43] [ec29c78521a0445a37e4526edb78f709] 

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Dataseries X:

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Histogram

Boxplots

165119	62	438	92	34	104	124252	252101
107269	59	330	58	30	111	98956	134577
93497	62	609	62	38	93	98073	198520
100269	94	1015	108	34	119	106816	189326
91627	44	294	55	25	57	41449	137449
47552	27	164	8	31	80	76173	65295
233933	103	1912	134	29	107	177551	439387
6853	19	111	1	18	22	22807	33186
104380	51	698	64	30	103	126938	178368
98431	38	556	77	29	72	61680	186657
156949	97	717	86	39	127	72117	265539
81817	96	495	93	50	168	79738	191088
59238	57	544	44	33	100	57793	138866
101138	66	959	106	46	143	91677	296878
107158	72	540	63	38	79	64631	192648
155499	162	1486	160	52	183	106385	333462
156274	58	635	104	32	123	161961	243571
121777	130	940	86	35	81	112669	263451
105037	49	452	93	25	74	114029	155679
118661	71	617	119	42	158	124550	227053
131187	63	695	107	40	133	105416	240028
145026	90	1046	86	35	128	72875	388549
107016	34	405	50	25	84	81964	156540
87242	43	477	92	46	184	104880	148421
91699	97	1012	123	36	127	76302	177732
110087	106	842	81	35	128	96740	191441
145447	122	994	93	38	118	93071	249893
143307	76	530	113	35	125	78912	236812
61678	45	515	52	28	89	35224	142329
210080	53	766	113	37	122	90694	259667
165005	66	734	112	40	151	125369	231625
97806	67	551	44	42	122	80849	176062
184471	79	718	123	44	162	104434	286683
27786	33	280	38	33	121	65702	87485
184458	83	1055	111	35	132	108179	322865
98765	51	950	77	37	110	63583	247082
178441	106	1038	92	39	135	95066	346011
100619	74	552	74	32	80	62486	191653
58391	31	275	33	17	46	31081	114673
151672	162	986	105	34	127	94584	284224
124437	72	1336	108	33	103	87408	284195
79929	60	565	66	35	95	68966	155363
123064	67	571	69	32	100	88766	177306
50466	49	404	62	35	102	57139	144571
100991	73	985	50	45	45	90586	140319
79367	135	1851	91	38	122	109249	405267
56968	42	330	20	26	66	33032	78800
106257	69	611	101	45	159	96056	201970
178412	99	1249	129	44	153	146648	302674
98520	50	812	93	40	131	80613	164733
153670	68	501	89	33	113	87026	194221
15049	24	218	8	4	7	5950	24188
174478	282	787	80	41	147	131106	346142
25109	17	255	21	18	61	32551	65029
45824	64	454	30	14	41	31701	101097
116772	46	944	86	33	108	91072	246088
189150	75	600	116	49	184	159803	273108
194404	160	977	106	32	115	143950	282220
185881	120	872	127	37	132	112368	275505
67508	74	690	75	32	113	82124	214872
188597	124	1176	138	41	141	144068	335121
203618	107	1013	114	25	65	162627	267171
87232	89	894	55	42	94	55062	189637
110875	78	777	67	35	121	95329	229512
144756	61	521	45	33	112	105612	209798
129825	60	409	88	28	81	62853	201345
92189	114	493	67	31	116	125976	163833
121158	129	757	75	40	132	79146	204250
96219	67	736	114	32	104	108461	197813
84128	60	511	123	25	80	99971	132955
97960	59	789	86	42	145	77826	216092
23824	32	385	22	23	67	22618	73566
103515	67	644	67	42	159	84892	213198
91313	50	664	77	38	90	92059	181713
85407	49	505	105	34	120	77993	148698
95871	70	878	119	38	126	104155	300103
143846	78	769	88	32	118	109840	251437
155387	101	499	78	37	112	238712	197295
74429	55	546	112	34	123	67486	158163
74004	57	551	66	33	98	68007	155529
71987	41	565	58	25	78	48194	132672
150629	102	1087	132	40	119	134796	377213
68580	66	649	30	26	99	38692	145905
119855	87	540	100	40	81	93587	223701
55792	25	437	49	8	27	56622	80953
25157	47	732	26	27	77	15986	130805
90895	48	308	67	32	118	113402	135082
117510	160	1243	57	33	122	97967	305270
144774	95	783	95	50	103	74844	271806
77529	96	933	139	37	129	136051	150949
103123	79	710	73	33	69	50548	225805
104669	68	563	134	34	121	112215	197389
82414	56	508	37	28	81	59591	156583
82390	68	968	108	36	135	59938	232718
128446	70	838	58	32	116	137639	261601
111542	35	523	78	32	123	143372	178489
136048	44	500	88	31	111	138599	200657
197257	69	694	142	35	100	174110	259244
162079	130	1060	127	58	221	135062	313075
206286	100	1232	139	27	95	175681	346933
109858	104	735	108	45	153	130307	246440
182125	58	757	128	37	118	139141	252444
74168	159	574	62	32	50	44244	159965
19630	14	214	13	19	64	43750	43287
88634	68	661	89	22	34	48029	172239
128321	121	640	83	35	76	95216	185198
118936	43	1015	116	36	112	92288	227681
127044	81	893	157	36	115	94588	260464
178377	54	293	28	23	69	197426	106288
69581	77	446	83	36	108	151244	109632
168019	58	538	72	36	130	139206	268905
113598	78	627	134	42	110	106271	266805
5841	11	156	12	1	0	1168	23623
93116	66	577	106	32	83	71764	152474
24610	25	192	23	11	30	25162	61857
60611	43	437	83	40	106	45635	144889
226620	99	1054	126	34	91	101817	346600
6622	16	146	4	0	0	855	21054
121996	45	751	71	27	69	100174	224051
13155	19	200	18	8	9	14116	31414
154158	105	1050	98	35	123	85008	261043
78489	58	601	66	44	150	124254	206108
22007	74	430	44	40	125	105793	154984
72530	45	467	29	28	81	117129	112933
13983	34	276	16	8	21	8773	38214
73397	33	528	56	35	124	94747	158671
143878	71	898	112	47	168	107549	302148
119956	55	411	46	46	149	97392	177918
181558	70	1362	129	42	147	126893	350552
208236	91	743	139	48	145	118850	275578
237085	106	1069	136	49	172	234853	368746
110297	31	431	66	35	126	74783	172464
61394	35	380	42	32	89	66089	94381
81420	281	790	70	36	137	95684	244295
191154	154	1367	97	42	149	139537	382487
11798	40	449	49	35	121	144253	114525
135724	120	1495	113	42	149	153824	345884
68614	72	651	55	34	93	63995	147989
139926	45	494	100	36	119	84891	216638
105203	72	667	80	36	102	61263	192862
80338	107	510	29	32	45	106221	184818
121376	105	1472	95	33	104	113587	336707
124922	76	675	114	35	111	113864	215836
10901	63	716	41	21	78	37238	173260
135471	89	814	128	40	120	119906	271773
66395	52	556	142	49	176	135096	130908
134041	75	887	88	33	109	151611	204009
153554	92	663	147	39	132	144645	245514
0	0	0	0	0	0	0	1
7953	10	85	4	0	0	6023	14688
0	1	0	0	0	0	0	98
0	2	0	0	0	0	0	455
0	0	0	0	0	0	0	0
0	0	0	0	0	0	0	0
98922	75	607	56	33	78	77457	195765
165395	121	934	121	42	104	62464	326038
0	0	0	0	0	0	0	0
0	4	0	0	0	0	0	203
4245	5	74	7	0	0	1644	7199
21509	20	259	12	5	13	6179	46660
7670	5	69	0	1	4	3926	17547
15167	38	267	37	38	65	42087	107465
0	2	0	0	0	0	0	969
63891	58	517	47	28	55	87656	173102

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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160552&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160552&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160552&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	'Gwilym Jenkins' @ jenkins.wessa.net

Goodness of Fit
Correlation	0.9052
R-squared	0.8194
RMSE	24345.2835

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.9052 \tabularnewline
R-squared & 0.8194 \tabularnewline
RMSE & 24345.2835 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160552&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.9052[/C][/ROW]
[ROW][C]R-squared[/C][C]0.8194[/C][/ROW]
[ROW][C]RMSE[/C][C]24345.2835[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160552&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160552&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	0.9052
R-squared	0.8194
RMSE	24345.2835

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	165119	151052.393939394	14066.606060606
2	107269	84415.5833333333	22853.4166666667
3	93497	107902.214285714	-14405.2142857143
4	100269	107902.214285714	-7633.21428571429
5	91627	56769.85	34857.15
6	47552	25173.8571428571	22378.1428571429
7	233933	192751.076923077	41181.9230769231
8	6853	4211.75	2641.25
9	104380	136232.111111111	-31852.1111111111
10	98431	107902.214285714	-9471.21428571429
11	156949	151052.393939394	5896.60606060605
12	81817	107902.214285714	-26085.2142857143
13	59238	56769.85	2468.15
14	101138	151052.393939394	-49914.393939394
15	107158	107902.214285714	-744.21428571429
16	155499	151052.393939394	4446.60606060605
17	156274	136232.111111111	20041.8888888889
18	121777	151052.393939394	-29275.393939394
19	105037	84415.5833333333	20621.4166666667
20	118661	107902.214285714	10758.7857142857
21	131187	107902.214285714	23284.7857142857
22	145026	151052.393939394	-6026.39393939395
23	107016	84415.5833333333	22600.4166666667
24	87242	84415.5833333333	2826.41666666667
25	91699	107902.214285714	-16203.2142857143
26	110087	107902.214285714	2184.78571428571
27	145447	151052.393939394	-5605.39393939395
28	143307	107902.214285714	35404.7857142857
29	61678	56769.85	4908.15
30	210080	151052.393939394	59027.606060606
31	165005	136232.111111111	28772.8888888889
32	97806	107902.214285714	-10096.2142857143
33	184471	151052.393939394	33418.606060606
34	27786	56769.85	-28983.85
35	184458	151052.393939394	33405.606060606
36	98765	107902.214285714	-9137.21428571429
37	178441	151052.393939394	27388.606060606
38	100619	107902.214285714	-7283.21428571429
39	58391	56769.85	1621.15
40	151672	151052.393939394	619.606060606049
41	124437	151052.393939394	-26615.393939394
42	79929	84415.5833333333	-4486.58333333333
43	123064	107902.214285714	15161.7857142857
44	50466	56769.85	-6303.85
45	100991	84415.5833333333	16575.4166666667
46	79367	151052.393939394	-71685.393939394
47	56968	56769.85	198.150000000001
48	106257	107902.214285714	-1645.21428571429
49	178412	192751.076923077	-14339.0769230769
50	98520	84415.5833333333	14104.4166666667
51	153670	107902.214285714	45767.7857142857
52	15049	4211.75	10837.25
53	174478	151052.393939394	23425.606060606
54	25109	25173.8571428571	-64.8571428571413
55	45824	56769.85	-10945.85
56	116772	107902.214285714	8869.78571428571
57	189150	192751.076923077	-3601.07692307694
58	194404	192751.076923077	1652.92307692306
59	185881	151052.393939394	34828.606060606
60	67508	107902.214285714	-40394.2142857143
61	188597	192751.076923077	-4154.07692307694
62	203618	192751.076923077	10866.9230769231
63	87232	107902.214285714	-20670.2142857143
64	110875	107902.214285714	2972.78571428571
65	144756	107902.214285714	36853.7857142857
66	129825	107902.214285714	21922.7857142857
67	92189	84415.5833333333	7773.41666666667
68	121158	107902.214285714	13255.7857142857
69	96219	107902.214285714	-11683.2142857143
70	84128	84415.5833333333	-287.583333333328
71	97960	107902.214285714	-9942.21428571429
72	23824	25173.8571428571	-1349.85714285714
73	103515	107902.214285714	-4387.21428571429
74	91313	107902.214285714	-16589.2142857143
75	85407	84415.5833333333	991.416666666672
76	95871	151052.393939394	-55181.393939394
77	143846	151052.393939394	-7206.39393939395
78	155387	136232.111111111	19154.8888888889
79	74429	84415.5833333333	-9986.58333333333
80	74004	84415.5833333333	-10411.5833333333
81	71987	56769.85	15217.15
82	150629	151052.393939394	-423.393939393951
83	68580	56769.85	11810.15
84	119855	107902.214285714	11952.7857142857
85	55792	56769.85	-977.849999999999
86	25157	56769.85	-31612.85
87	90895	84415.5833333333	6479.41666666667
88	117510	151052.393939394	-33542.393939394
89	144774	151052.393939394	-6278.39393939395
90	77529	84415.5833333333	-6886.58333333333
91	103123	107902.214285714	-4779.21428571429
92	104669	107902.214285714	-3233.21428571429
93	82414	56769.85	25644.15
94	82390	107902.214285714	-25512.2142857143
95	128446	151052.393939394	-22606.393939394
96	111542	136232.111111111	-24690.1111111111
97	136048	136232.111111111	-184.111111111124
98	197257	192751.076923077	4505.92307692306
99	162079	151052.393939394	11026.606060606
100	206286	192751.076923077	13534.9230769231
101	109858	136232.111111111	-26374.1111111111
102	182125	192751.076923077	-10626.0769230769
103	74168	56769.85	17398.15
104	19630	25173.8571428571	-5543.85714285714
105	88634	56769.85	31864.15
106	128321	107902.214285714	20418.7857142857
107	118936	107902.214285714	11033.7857142857
108	127044	151052.393939394	-24008.393939394
109	178377	84415.5833333333	93961.4166666667
110	69581	84415.5833333333	-14834.5833333333
111	168019	192751.076923077	-24732.0769230769
112	113598	151052.393939394	-37454.393939394
113	5841	4211.75	1629.25
114	93116	84415.5833333333	8700.41666666667
115	24610	25173.8571428571	-563.857142857141
116	60611	56769.85	3841.15
117	226620	151052.393939394	75567.606060606
118	6622	4211.75	2410.25
119	121996	107902.214285714	14093.7857142857
120	13155	4211.75	8943.25
121	154158	151052.393939394	3105.60606060605
122	78489	107902.214285714	-29413.2142857143
123	22007	84415.5833333333	-62408.5833333333
124	72530	84415.5833333333	-11885.5833333333
125	13983	25173.8571428571	-11190.8571428571
126	73397	84415.5833333333	-11018.5833333333
127	143878	151052.393939394	-7174.39393939395
128	119956	107902.214285714	12053.7857142857
129	181558	151052.393939394	30505.606060606
130	208236	151052.393939394	57183.606060606
131	237085	192751.076923077	44333.9230769231
132	110297	84415.5833333333	25881.4166666667
133	61394	56769.85	4624.15
134	81420	107902.214285714	-26482.2142857143
135	191154	192751.076923077	-1597.07692307694
136	11798	84415.5833333333	-72617.5833333333
137	135724	192751.076923077	-57027.0769230769
138	68614	56769.85	11844.15
139	139926	107902.214285714	32023.7857142857
140	105203	107902.214285714	-2699.21428571429
141	80338	107902.214285714	-27564.2142857143
142	121376	151052.393939394	-29676.393939394
143	124922	107902.214285714	17019.7857142857
144	10901	56769.85	-45868.85
145	135471	151052.393939394	-15581.393939394
146	66395	84415.5833333333	-18020.5833333333
147	134041	136232.111111111	-2191.11111111112
148	153554	136232.111111111	17321.8888888889
149	0	4211.75	-4211.75
150	7953	4211.75	3741.25
151	0	4211.75	-4211.75
152	0	4211.75	-4211.75
153	0	4211.75	-4211.75
154	0	4211.75	-4211.75
155	98922	107902.214285714	-8980.21428571429
156	165395	151052.393939394	14342.606060606
157	0	4211.75	-4211.75
158	0	4211.75	-4211.75
159	4245	4211.75	33.25
160	21509	25173.8571428571	-3664.85714285714
161	7670	4211.75	3458.25
162	15167	56769.85	-41602.85
163	0	4211.75	-4211.75
164	63891	84415.5833333333	-20524.5833333333

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 165119 & 151052.393939394 & 14066.606060606 \tabularnewline
2 & 107269 & 84415.5833333333 & 22853.4166666667 \tabularnewline
3 & 93497 & 107902.214285714 & -14405.2142857143 \tabularnewline
4 & 100269 & 107902.214285714 & -7633.21428571429 \tabularnewline
5 & 91627 & 56769.85 & 34857.15 \tabularnewline
6 & 47552 & 25173.8571428571 & 22378.1428571429 \tabularnewline
7 & 233933 & 192751.076923077 & 41181.9230769231 \tabularnewline
8 & 6853 & 4211.75 & 2641.25 \tabularnewline
9 & 104380 & 136232.111111111 & -31852.1111111111 \tabularnewline
10 & 98431 & 107902.214285714 & -9471.21428571429 \tabularnewline
11 & 156949 & 151052.393939394 & 5896.60606060605 \tabularnewline
12 & 81817 & 107902.214285714 & -26085.2142857143 \tabularnewline
13 & 59238 & 56769.85 & 2468.15 \tabularnewline
14 & 101138 & 151052.393939394 & -49914.393939394 \tabularnewline
15 & 107158 & 107902.214285714 & -744.21428571429 \tabularnewline
16 & 155499 & 151052.393939394 & 4446.60606060605 \tabularnewline
17 & 156274 & 136232.111111111 & 20041.8888888889 \tabularnewline
18 & 121777 & 151052.393939394 & -29275.393939394 \tabularnewline
19 & 105037 & 84415.5833333333 & 20621.4166666667 \tabularnewline
20 & 118661 & 107902.214285714 & 10758.7857142857 \tabularnewline
21 & 131187 & 107902.214285714 & 23284.7857142857 \tabularnewline
22 & 145026 & 151052.393939394 & -6026.39393939395 \tabularnewline
23 & 107016 & 84415.5833333333 & 22600.4166666667 \tabularnewline
24 & 87242 & 84415.5833333333 & 2826.41666666667 \tabularnewline
25 & 91699 & 107902.214285714 & -16203.2142857143 \tabularnewline
26 & 110087 & 107902.214285714 & 2184.78571428571 \tabularnewline
27 & 145447 & 151052.393939394 & -5605.39393939395 \tabularnewline
28 & 143307 & 107902.214285714 & 35404.7857142857 \tabularnewline
29 & 61678 & 56769.85 & 4908.15 \tabularnewline
30 & 210080 & 151052.393939394 & 59027.606060606 \tabularnewline
31 & 165005 & 136232.111111111 & 28772.8888888889 \tabularnewline
32 & 97806 & 107902.214285714 & -10096.2142857143 \tabularnewline
33 & 184471 & 151052.393939394 & 33418.606060606 \tabularnewline
34 & 27786 & 56769.85 & -28983.85 \tabularnewline
35 & 184458 & 151052.393939394 & 33405.606060606 \tabularnewline
36 & 98765 & 107902.214285714 & -9137.21428571429 \tabularnewline
37 & 178441 & 151052.393939394 & 27388.606060606 \tabularnewline
38 & 100619 & 107902.214285714 & -7283.21428571429 \tabularnewline
39 & 58391 & 56769.85 & 1621.15 \tabularnewline
40 & 151672 & 151052.393939394 & 619.606060606049 \tabularnewline
41 & 124437 & 151052.393939394 & -26615.393939394 \tabularnewline
42 & 79929 & 84415.5833333333 & -4486.58333333333 \tabularnewline
43 & 123064 & 107902.214285714 & 15161.7857142857 \tabularnewline
44 & 50466 & 56769.85 & -6303.85 \tabularnewline
45 & 100991 & 84415.5833333333 & 16575.4166666667 \tabularnewline
46 & 79367 & 151052.393939394 & -71685.393939394 \tabularnewline
47 & 56968 & 56769.85 & 198.150000000001 \tabularnewline
48 & 106257 & 107902.214285714 & -1645.21428571429 \tabularnewline
49 & 178412 & 192751.076923077 & -14339.0769230769 \tabularnewline
50 & 98520 & 84415.5833333333 & 14104.4166666667 \tabularnewline
51 & 153670 & 107902.214285714 & 45767.7857142857 \tabularnewline
52 & 15049 & 4211.75 & 10837.25 \tabularnewline
53 & 174478 & 151052.393939394 & 23425.606060606 \tabularnewline
54 & 25109 & 25173.8571428571 & -64.8571428571413 \tabularnewline
55 & 45824 & 56769.85 & -10945.85 \tabularnewline
56 & 116772 & 107902.214285714 & 8869.78571428571 \tabularnewline
57 & 189150 & 192751.076923077 & -3601.07692307694 \tabularnewline
58 & 194404 & 192751.076923077 & 1652.92307692306 \tabularnewline
59 & 185881 & 151052.393939394 & 34828.606060606 \tabularnewline
60 & 67508 & 107902.214285714 & -40394.2142857143 \tabularnewline
61 & 188597 & 192751.076923077 & -4154.07692307694 \tabularnewline
62 & 203618 & 192751.076923077 & 10866.9230769231 \tabularnewline
63 & 87232 & 107902.214285714 & -20670.2142857143 \tabularnewline
64 & 110875 & 107902.214285714 & 2972.78571428571 \tabularnewline
65 & 144756 & 107902.214285714 & 36853.7857142857 \tabularnewline
66 & 129825 & 107902.214285714 & 21922.7857142857 \tabularnewline
67 & 92189 & 84415.5833333333 & 7773.41666666667 \tabularnewline
68 & 121158 & 107902.214285714 & 13255.7857142857 \tabularnewline
69 & 96219 & 107902.214285714 & -11683.2142857143 \tabularnewline
70 & 84128 & 84415.5833333333 & -287.583333333328 \tabularnewline
71 & 97960 & 107902.214285714 & -9942.21428571429 \tabularnewline
72 & 23824 & 25173.8571428571 & -1349.85714285714 \tabularnewline
73 & 103515 & 107902.214285714 & -4387.21428571429 \tabularnewline
74 & 91313 & 107902.214285714 & -16589.2142857143 \tabularnewline
75 & 85407 & 84415.5833333333 & 991.416666666672 \tabularnewline
76 & 95871 & 151052.393939394 & -55181.393939394 \tabularnewline
77 & 143846 & 151052.393939394 & -7206.39393939395 \tabularnewline
78 & 155387 & 136232.111111111 & 19154.8888888889 \tabularnewline
79 & 74429 & 84415.5833333333 & -9986.58333333333 \tabularnewline
80 & 74004 & 84415.5833333333 & -10411.5833333333 \tabularnewline
81 & 71987 & 56769.85 & 15217.15 \tabularnewline
82 & 150629 & 151052.393939394 & -423.393939393951 \tabularnewline
83 & 68580 & 56769.85 & 11810.15 \tabularnewline
84 & 119855 & 107902.214285714 & 11952.7857142857 \tabularnewline
85 & 55792 & 56769.85 & -977.849999999999 \tabularnewline
86 & 25157 & 56769.85 & -31612.85 \tabularnewline
87 & 90895 & 84415.5833333333 & 6479.41666666667 \tabularnewline
88 & 117510 & 151052.393939394 & -33542.393939394 \tabularnewline
89 & 144774 & 151052.393939394 & -6278.39393939395 \tabularnewline
90 & 77529 & 84415.5833333333 & -6886.58333333333 \tabularnewline
91 & 103123 & 107902.214285714 & -4779.21428571429 \tabularnewline
92 & 104669 & 107902.214285714 & -3233.21428571429 \tabularnewline
93 & 82414 & 56769.85 & 25644.15 \tabularnewline
94 & 82390 & 107902.214285714 & -25512.2142857143 \tabularnewline
95 & 128446 & 151052.393939394 & -22606.393939394 \tabularnewline
96 & 111542 & 136232.111111111 & -24690.1111111111 \tabularnewline
97 & 136048 & 136232.111111111 & -184.111111111124 \tabularnewline
98 & 197257 & 192751.076923077 & 4505.92307692306 \tabularnewline
99 & 162079 & 151052.393939394 & 11026.606060606 \tabularnewline
100 & 206286 & 192751.076923077 & 13534.9230769231 \tabularnewline
101 & 109858 & 136232.111111111 & -26374.1111111111 \tabularnewline
102 & 182125 & 192751.076923077 & -10626.0769230769 \tabularnewline
103 & 74168 & 56769.85 & 17398.15 \tabularnewline
104 & 19630 & 25173.8571428571 & -5543.85714285714 \tabularnewline
105 & 88634 & 56769.85 & 31864.15 \tabularnewline
106 & 128321 & 107902.214285714 & 20418.7857142857 \tabularnewline
107 & 118936 & 107902.214285714 & 11033.7857142857 \tabularnewline
108 & 127044 & 151052.393939394 & -24008.393939394 \tabularnewline
109 & 178377 & 84415.5833333333 & 93961.4166666667 \tabularnewline
110 & 69581 & 84415.5833333333 & -14834.5833333333 \tabularnewline
111 & 168019 & 192751.076923077 & -24732.0769230769 \tabularnewline
112 & 113598 & 151052.393939394 & -37454.393939394 \tabularnewline
113 & 5841 & 4211.75 & 1629.25 \tabularnewline
114 & 93116 & 84415.5833333333 & 8700.41666666667 \tabularnewline
115 & 24610 & 25173.8571428571 & -563.857142857141 \tabularnewline
116 & 60611 & 56769.85 & 3841.15 \tabularnewline
117 & 226620 & 151052.393939394 & 75567.606060606 \tabularnewline
118 & 6622 & 4211.75 & 2410.25 \tabularnewline
119 & 121996 & 107902.214285714 & 14093.7857142857 \tabularnewline
120 & 13155 & 4211.75 & 8943.25 \tabularnewline
121 & 154158 & 151052.393939394 & 3105.60606060605 \tabularnewline
122 & 78489 & 107902.214285714 & -29413.2142857143 \tabularnewline
123 & 22007 & 84415.5833333333 & -62408.5833333333 \tabularnewline
124 & 72530 & 84415.5833333333 & -11885.5833333333 \tabularnewline
125 & 13983 & 25173.8571428571 & -11190.8571428571 \tabularnewline
126 & 73397 & 84415.5833333333 & -11018.5833333333 \tabularnewline
127 & 143878 & 151052.393939394 & -7174.39393939395 \tabularnewline
128 & 119956 & 107902.214285714 & 12053.7857142857 \tabularnewline
129 & 181558 & 151052.393939394 & 30505.606060606 \tabularnewline
130 & 208236 & 151052.393939394 & 57183.606060606 \tabularnewline
131 & 237085 & 192751.076923077 & 44333.9230769231 \tabularnewline
132 & 110297 & 84415.5833333333 & 25881.4166666667 \tabularnewline
133 & 61394 & 56769.85 & 4624.15 \tabularnewline
134 & 81420 & 107902.214285714 & -26482.2142857143 \tabularnewline
135 & 191154 & 192751.076923077 & -1597.07692307694 \tabularnewline
136 & 11798 & 84415.5833333333 & -72617.5833333333 \tabularnewline
137 & 135724 & 192751.076923077 & -57027.0769230769 \tabularnewline
138 & 68614 & 56769.85 & 11844.15 \tabularnewline
139 & 139926 & 107902.214285714 & 32023.7857142857 \tabularnewline
140 & 105203 & 107902.214285714 & -2699.21428571429 \tabularnewline
141 & 80338 & 107902.214285714 & -27564.2142857143 \tabularnewline
142 & 121376 & 151052.393939394 & -29676.393939394 \tabularnewline
143 & 124922 & 107902.214285714 & 17019.7857142857 \tabularnewline
144 & 10901 & 56769.85 & -45868.85 \tabularnewline
145 & 135471 & 151052.393939394 & -15581.393939394 \tabularnewline
146 & 66395 & 84415.5833333333 & -18020.5833333333 \tabularnewline
147 & 134041 & 136232.111111111 & -2191.11111111112 \tabularnewline
148 & 153554 & 136232.111111111 & 17321.8888888889 \tabularnewline
149 & 0 & 4211.75 & -4211.75 \tabularnewline
150 & 7953 & 4211.75 & 3741.25 \tabularnewline
151 & 0 & 4211.75 & -4211.75 \tabularnewline
152 & 0 & 4211.75 & -4211.75 \tabularnewline
153 & 0 & 4211.75 & -4211.75 \tabularnewline
154 & 0 & 4211.75 & -4211.75 \tabularnewline
155 & 98922 & 107902.214285714 & -8980.21428571429 \tabularnewline
156 & 165395 & 151052.393939394 & 14342.606060606 \tabularnewline
157 & 0 & 4211.75 & -4211.75 \tabularnewline
158 & 0 & 4211.75 & -4211.75 \tabularnewline
159 & 4245 & 4211.75 & 33.25 \tabularnewline
160 & 21509 & 25173.8571428571 & -3664.85714285714 \tabularnewline
161 & 7670 & 4211.75 & 3458.25 \tabularnewline
162 & 15167 & 56769.85 & -41602.85 \tabularnewline
163 & 0 & 4211.75 & -4211.75 \tabularnewline
164 & 63891 & 84415.5833333333 & -20524.5833333333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160552&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]165119[/C][C]151052.393939394[/C][C]14066.606060606[/C][/ROW]
[ROW][C]2[/C][C]107269[/C][C]84415.5833333333[/C][C]22853.4166666667[/C][/ROW]
[ROW][C]3[/C][C]93497[/C][C]107902.214285714[/C][C]-14405.2142857143[/C][/ROW]
[ROW][C]4[/C][C]100269[/C][C]107902.214285714[/C][C]-7633.21428571429[/C][/ROW]
[ROW][C]5[/C][C]91627[/C][C]56769.85[/C][C]34857.15[/C][/ROW]
[ROW][C]6[/C][C]47552[/C][C]25173.8571428571[/C][C]22378.1428571429[/C][/ROW]
[ROW][C]7[/C][C]233933[/C][C]192751.076923077[/C][C]41181.9230769231[/C][/ROW]
[ROW][C]8[/C][C]6853[/C][C]4211.75[/C][C]2641.25[/C][/ROW]
[ROW][C]9[/C][C]104380[/C][C]136232.111111111[/C][C]-31852.1111111111[/C][/ROW]
[ROW][C]10[/C][C]98431[/C][C]107902.214285714[/C][C]-9471.21428571429[/C][/ROW]
[ROW][C]11[/C][C]156949[/C][C]151052.393939394[/C][C]5896.60606060605[/C][/ROW]
[ROW][C]12[/C][C]81817[/C][C]107902.214285714[/C][C]-26085.2142857143[/C][/ROW]
[ROW][C]13[/C][C]59238[/C][C]56769.85[/C][C]2468.15[/C][/ROW]
[ROW][C]14[/C][C]101138[/C][C]151052.393939394[/C][C]-49914.393939394[/C][/ROW]
[ROW][C]15[/C][C]107158[/C][C]107902.214285714[/C][C]-744.21428571429[/C][/ROW]
[ROW][C]16[/C][C]155499[/C][C]151052.393939394[/C][C]4446.60606060605[/C][/ROW]
[ROW][C]17[/C][C]156274[/C][C]136232.111111111[/C][C]20041.8888888889[/C][/ROW]
[ROW][C]18[/C][C]121777[/C][C]151052.393939394[/C][C]-29275.393939394[/C][/ROW]
[ROW][C]19[/C][C]105037[/C][C]84415.5833333333[/C][C]20621.4166666667[/C][/ROW]
[ROW][C]20[/C][C]118661[/C][C]107902.214285714[/C][C]10758.7857142857[/C][/ROW]
[ROW][C]21[/C][C]131187[/C][C]107902.214285714[/C][C]23284.7857142857[/C][/ROW]
[ROW][C]22[/C][C]145026[/C][C]151052.393939394[/C][C]-6026.39393939395[/C][/ROW]
[ROW][C]23[/C][C]107016[/C][C]84415.5833333333[/C][C]22600.4166666667[/C][/ROW]
[ROW][C]24[/C][C]87242[/C][C]84415.5833333333[/C][C]2826.41666666667[/C][/ROW]
[ROW][C]25[/C][C]91699[/C][C]107902.214285714[/C][C]-16203.2142857143[/C][/ROW]
[ROW][C]26[/C][C]110087[/C][C]107902.214285714[/C][C]2184.78571428571[/C][/ROW]
[ROW][C]27[/C][C]145447[/C][C]151052.393939394[/C][C]-5605.39393939395[/C][/ROW]
[ROW][C]28[/C][C]143307[/C][C]107902.214285714[/C][C]35404.7857142857[/C][/ROW]
[ROW][C]29[/C][C]61678[/C][C]56769.85[/C][C]4908.15[/C][/ROW]
[ROW][C]30[/C][C]210080[/C][C]151052.393939394[/C][C]59027.606060606[/C][/ROW]
[ROW][C]31[/C][C]165005[/C][C]136232.111111111[/C][C]28772.8888888889[/C][/ROW]
[ROW][C]32[/C][C]97806[/C][C]107902.214285714[/C][C]-10096.2142857143[/C][/ROW]
[ROW][C]33[/C][C]184471[/C][C]151052.393939394[/C][C]33418.606060606[/C][/ROW]
[ROW][C]34[/C][C]27786[/C][C]56769.85[/C][C]-28983.85[/C][/ROW]
[ROW][C]35[/C][C]184458[/C][C]151052.393939394[/C][C]33405.606060606[/C][/ROW]
[ROW][C]36[/C][C]98765[/C][C]107902.214285714[/C][C]-9137.21428571429[/C][/ROW]
[ROW][C]37[/C][C]178441[/C][C]151052.393939394[/C][C]27388.606060606[/C][/ROW]
[ROW][C]38[/C][C]100619[/C][C]107902.214285714[/C][C]-7283.21428571429[/C][/ROW]
[ROW][C]39[/C][C]58391[/C][C]56769.85[/C][C]1621.15[/C][/ROW]
[ROW][C]40[/C][C]151672[/C][C]151052.393939394[/C][C]619.606060606049[/C][/ROW]
[ROW][C]41[/C][C]124437[/C][C]151052.393939394[/C][C]-26615.393939394[/C][/ROW]
[ROW][C]42[/C][C]79929[/C][C]84415.5833333333[/C][C]-4486.58333333333[/C][/ROW]
[ROW][C]43[/C][C]123064[/C][C]107902.214285714[/C][C]15161.7857142857[/C][/ROW]
[ROW][C]44[/C][C]50466[/C][C]56769.85[/C][C]-6303.85[/C][/ROW]
[ROW][C]45[/C][C]100991[/C][C]84415.5833333333[/C][C]16575.4166666667[/C][/ROW]
[ROW][C]46[/C][C]79367[/C][C]151052.393939394[/C][C]-71685.393939394[/C][/ROW]
[ROW][C]47[/C][C]56968[/C][C]56769.85[/C][C]198.150000000001[/C][/ROW]
[ROW][C]48[/C][C]106257[/C][C]107902.214285714[/C][C]-1645.21428571429[/C][/ROW]
[ROW][C]49[/C][C]178412[/C][C]192751.076923077[/C][C]-14339.0769230769[/C][/ROW]
[ROW][C]50[/C][C]98520[/C][C]84415.5833333333[/C][C]14104.4166666667[/C][/ROW]
[ROW][C]51[/C][C]153670[/C][C]107902.214285714[/C][C]45767.7857142857[/C][/ROW]
[ROW][C]52[/C][C]15049[/C][C]4211.75[/C][C]10837.25[/C][/ROW]
[ROW][C]53[/C][C]174478[/C][C]151052.393939394[/C][C]23425.606060606[/C][/ROW]
[ROW][C]54[/C][C]25109[/C][C]25173.8571428571[/C][C]-64.8571428571413[/C][/ROW]
[ROW][C]55[/C][C]45824[/C][C]56769.85[/C][C]-10945.85[/C][/ROW]
[ROW][C]56[/C][C]116772[/C][C]107902.214285714[/C][C]8869.78571428571[/C][/ROW]
[ROW][C]57[/C][C]189150[/C][C]192751.076923077[/C][C]-3601.07692307694[/C][/ROW]
[ROW][C]58[/C][C]194404[/C][C]192751.076923077[/C][C]1652.92307692306[/C][/ROW]
[ROW][C]59[/C][C]185881[/C][C]151052.393939394[/C][C]34828.606060606[/C][/ROW]
[ROW][C]60[/C][C]67508[/C][C]107902.214285714[/C][C]-40394.2142857143[/C][/ROW]
[ROW][C]61[/C][C]188597[/C][C]192751.076923077[/C][C]-4154.07692307694[/C][/ROW]
[ROW][C]62[/C][C]203618[/C][C]192751.076923077[/C][C]10866.9230769231[/C][/ROW]
[ROW][C]63[/C][C]87232[/C][C]107902.214285714[/C][C]-20670.2142857143[/C][/ROW]
[ROW][C]64[/C][C]110875[/C][C]107902.214285714[/C][C]2972.78571428571[/C][/ROW]
[ROW][C]65[/C][C]144756[/C][C]107902.214285714[/C][C]36853.7857142857[/C][/ROW]
[ROW][C]66[/C][C]129825[/C][C]107902.214285714[/C][C]21922.7857142857[/C][/ROW]
[ROW][C]67[/C][C]92189[/C][C]84415.5833333333[/C][C]7773.41666666667[/C][/ROW]
[ROW][C]68[/C][C]121158[/C][C]107902.214285714[/C][C]13255.7857142857[/C][/ROW]
[ROW][C]69[/C][C]96219[/C][C]107902.214285714[/C][C]-11683.2142857143[/C][/ROW]
[ROW][C]70[/C][C]84128[/C][C]84415.5833333333[/C][C]-287.583333333328[/C][/ROW]
[ROW][C]71[/C][C]97960[/C][C]107902.214285714[/C][C]-9942.21428571429[/C][/ROW]
[ROW][C]72[/C][C]23824[/C][C]25173.8571428571[/C][C]-1349.85714285714[/C][/ROW]
[ROW][C]73[/C][C]103515[/C][C]107902.214285714[/C][C]-4387.21428571429[/C][/ROW]
[ROW][C]74[/C][C]91313[/C][C]107902.214285714[/C][C]-16589.2142857143[/C][/ROW]
[ROW][C]75[/C][C]85407[/C][C]84415.5833333333[/C][C]991.416666666672[/C][/ROW]
[ROW][C]76[/C][C]95871[/C][C]151052.393939394[/C][C]-55181.393939394[/C][/ROW]
[ROW][C]77[/C][C]143846[/C][C]151052.393939394[/C][C]-7206.39393939395[/C][/ROW]
[ROW][C]78[/C][C]155387[/C][C]136232.111111111[/C][C]19154.8888888889[/C][/ROW]
[ROW][C]79[/C][C]74429[/C][C]84415.5833333333[/C][C]-9986.58333333333[/C][/ROW]
[ROW][C]80[/C][C]74004[/C][C]84415.5833333333[/C][C]-10411.5833333333[/C][/ROW]
[ROW][C]81[/C][C]71987[/C][C]56769.85[/C][C]15217.15[/C][/ROW]
[ROW][C]82[/C][C]150629[/C][C]151052.393939394[/C][C]-423.393939393951[/C][/ROW]
[ROW][C]83[/C][C]68580[/C][C]56769.85[/C][C]11810.15[/C][/ROW]
[ROW][C]84[/C][C]119855[/C][C]107902.214285714[/C][C]11952.7857142857[/C][/ROW]
[ROW][C]85[/C][C]55792[/C][C]56769.85[/C][C]-977.849999999999[/C][/ROW]
[ROW][C]86[/C][C]25157[/C][C]56769.85[/C][C]-31612.85[/C][/ROW]
[ROW][C]87[/C][C]90895[/C][C]84415.5833333333[/C][C]6479.41666666667[/C][/ROW]
[ROW][C]88[/C][C]117510[/C][C]151052.393939394[/C][C]-33542.393939394[/C][/ROW]
[ROW][C]89[/C][C]144774[/C][C]151052.393939394[/C][C]-6278.39393939395[/C][/ROW]
[ROW][C]90[/C][C]77529[/C][C]84415.5833333333[/C][C]-6886.58333333333[/C][/ROW]
[ROW][C]91[/C][C]103123[/C][C]107902.214285714[/C][C]-4779.21428571429[/C][/ROW]
[ROW][C]92[/C][C]104669[/C][C]107902.214285714[/C][C]-3233.21428571429[/C][/ROW]
[ROW][C]93[/C][C]82414[/C][C]56769.85[/C][C]25644.15[/C][/ROW]
[ROW][C]94[/C][C]82390[/C][C]107902.214285714[/C][C]-25512.2142857143[/C][/ROW]
[ROW][C]95[/C][C]128446[/C][C]151052.393939394[/C][C]-22606.393939394[/C][/ROW]
[ROW][C]96[/C][C]111542[/C][C]136232.111111111[/C][C]-24690.1111111111[/C][/ROW]
[ROW][C]97[/C][C]136048[/C][C]136232.111111111[/C][C]-184.111111111124[/C][/ROW]
[ROW][C]98[/C][C]197257[/C][C]192751.076923077[/C][C]4505.92307692306[/C][/ROW]
[ROW][C]99[/C][C]162079[/C][C]151052.393939394[/C][C]11026.606060606[/C][/ROW]
[ROW][C]100[/C][C]206286[/C][C]192751.076923077[/C][C]13534.9230769231[/C][/ROW]
[ROW][C]101[/C][C]109858[/C][C]136232.111111111[/C][C]-26374.1111111111[/C][/ROW]
[ROW][C]102[/C][C]182125[/C][C]192751.076923077[/C][C]-10626.0769230769[/C][/ROW]
[ROW][C]103[/C][C]74168[/C][C]56769.85[/C][C]17398.15[/C][/ROW]
[ROW][C]104[/C][C]19630[/C][C]25173.8571428571[/C][C]-5543.85714285714[/C][/ROW]
[ROW][C]105[/C][C]88634[/C][C]56769.85[/C][C]31864.15[/C][/ROW]
[ROW][C]106[/C][C]128321[/C][C]107902.214285714[/C][C]20418.7857142857[/C][/ROW]
[ROW][C]107[/C][C]118936[/C][C]107902.214285714[/C][C]11033.7857142857[/C][/ROW]
[ROW][C]108[/C][C]127044[/C][C]151052.393939394[/C][C]-24008.393939394[/C][/ROW]
[ROW][C]109[/C][C]178377[/C][C]84415.5833333333[/C][C]93961.4166666667[/C][/ROW]
[ROW][C]110[/C][C]69581[/C][C]84415.5833333333[/C][C]-14834.5833333333[/C][/ROW]
[ROW][C]111[/C][C]168019[/C][C]192751.076923077[/C][C]-24732.0769230769[/C][/ROW]
[ROW][C]112[/C][C]113598[/C][C]151052.393939394[/C][C]-37454.393939394[/C][/ROW]
[ROW][C]113[/C][C]5841[/C][C]4211.75[/C][C]1629.25[/C][/ROW]
[ROW][C]114[/C][C]93116[/C][C]84415.5833333333[/C][C]8700.41666666667[/C][/ROW]
[ROW][C]115[/C][C]24610[/C][C]25173.8571428571[/C][C]-563.857142857141[/C][/ROW]
[ROW][C]116[/C][C]60611[/C][C]56769.85[/C][C]3841.15[/C][/ROW]
[ROW][C]117[/C][C]226620[/C][C]151052.393939394[/C][C]75567.606060606[/C][/ROW]
[ROW][C]118[/C][C]6622[/C][C]4211.75[/C][C]2410.25[/C][/ROW]
[ROW][C]119[/C][C]121996[/C][C]107902.214285714[/C][C]14093.7857142857[/C][/ROW]
[ROW][C]120[/C][C]13155[/C][C]4211.75[/C][C]8943.25[/C][/ROW]
[ROW][C]121[/C][C]154158[/C][C]151052.393939394[/C][C]3105.60606060605[/C][/ROW]
[ROW][C]122[/C][C]78489[/C][C]107902.214285714[/C][C]-29413.2142857143[/C][/ROW]
[ROW][C]123[/C][C]22007[/C][C]84415.5833333333[/C][C]-62408.5833333333[/C][/ROW]
[ROW][C]124[/C][C]72530[/C][C]84415.5833333333[/C][C]-11885.5833333333[/C][/ROW]
[ROW][C]125[/C][C]13983[/C][C]25173.8571428571[/C][C]-11190.8571428571[/C][/ROW]
[ROW][C]126[/C][C]73397[/C][C]84415.5833333333[/C][C]-11018.5833333333[/C][/ROW]
[ROW][C]127[/C][C]143878[/C][C]151052.393939394[/C][C]-7174.39393939395[/C][/ROW]
[ROW][C]128[/C][C]119956[/C][C]107902.214285714[/C][C]12053.7857142857[/C][/ROW]
[ROW][C]129[/C][C]181558[/C][C]151052.393939394[/C][C]30505.606060606[/C][/ROW]
[ROW][C]130[/C][C]208236[/C][C]151052.393939394[/C][C]57183.606060606[/C][/ROW]
[ROW][C]131[/C][C]237085[/C][C]192751.076923077[/C][C]44333.9230769231[/C][/ROW]
[ROW][C]132[/C][C]110297[/C][C]84415.5833333333[/C][C]25881.4166666667[/C][/ROW]
[ROW][C]133[/C][C]61394[/C][C]56769.85[/C][C]4624.15[/C][/ROW]
[ROW][C]134[/C][C]81420[/C][C]107902.214285714[/C][C]-26482.2142857143[/C][/ROW]
[ROW][C]135[/C][C]191154[/C][C]192751.076923077[/C][C]-1597.07692307694[/C][/ROW]
[ROW][C]136[/C][C]11798[/C][C]84415.5833333333[/C][C]-72617.5833333333[/C][/ROW]
[ROW][C]137[/C][C]135724[/C][C]192751.076923077[/C][C]-57027.0769230769[/C][/ROW]
[ROW][C]138[/C][C]68614[/C][C]56769.85[/C][C]11844.15[/C][/ROW]
[ROW][C]139[/C][C]139926[/C][C]107902.214285714[/C][C]32023.7857142857[/C][/ROW]
[ROW][C]140[/C][C]105203[/C][C]107902.214285714[/C][C]-2699.21428571429[/C][/ROW]
[ROW][C]141[/C][C]80338[/C][C]107902.214285714[/C][C]-27564.2142857143[/C][/ROW]
[ROW][C]142[/C][C]121376[/C][C]151052.393939394[/C][C]-29676.393939394[/C][/ROW]
[ROW][C]143[/C][C]124922[/C][C]107902.214285714[/C][C]17019.7857142857[/C][/ROW]
[ROW][C]144[/C][C]10901[/C][C]56769.85[/C][C]-45868.85[/C][/ROW]
[ROW][C]145[/C][C]135471[/C][C]151052.393939394[/C][C]-15581.393939394[/C][/ROW]
[ROW][C]146[/C][C]66395[/C][C]84415.5833333333[/C][C]-18020.5833333333[/C][/ROW]
[ROW][C]147[/C][C]134041[/C][C]136232.111111111[/C][C]-2191.11111111112[/C][/ROW]
[ROW][C]148[/C][C]153554[/C][C]136232.111111111[/C][C]17321.8888888889[/C][/ROW]
[ROW][C]149[/C][C]0[/C][C]4211.75[/C][C]-4211.75[/C][/ROW]
[ROW][C]150[/C][C]7953[/C][C]4211.75[/C][C]3741.25[/C][/ROW]
[ROW][C]151[/C][C]0[/C][C]4211.75[/C][C]-4211.75[/C][/ROW]
[ROW][C]152[/C][C]0[/C][C]4211.75[/C][C]-4211.75[/C][/ROW]
[ROW][C]153[/C][C]0[/C][C]4211.75[/C][C]-4211.75[/C][/ROW]
[ROW][C]154[/C][C]0[/C][C]4211.75[/C][C]-4211.75[/C][/ROW]
[ROW][C]155[/C][C]98922[/C][C]107902.214285714[/C][C]-8980.21428571429[/C][/ROW]
[ROW][C]156[/C][C]165395[/C][C]151052.393939394[/C][C]14342.606060606[/C][/ROW]
[ROW][C]157[/C][C]0[/C][C]4211.75[/C][C]-4211.75[/C][/ROW]
[ROW][C]158[/C][C]0[/C][C]4211.75[/C][C]-4211.75[/C][/ROW]
[ROW][C]159[/C][C]4245[/C][C]4211.75[/C][C]33.25[/C][/ROW]
[ROW][C]160[/C][C]21509[/C][C]25173.8571428571[/C][C]-3664.85714285714[/C][/ROW]
[ROW][C]161[/C][C]7670[/C][C]4211.75[/C][C]3458.25[/C][/ROW]
[ROW][C]162[/C][C]15167[/C][C]56769.85[/C][C]-41602.85[/C][/ROW]
[ROW][C]163[/C][C]0[/C][C]4211.75[/C][C]-4211.75[/C][/ROW]
[ROW][C]164[/C][C]63891[/C][C]84415.5833333333[/C][C]-20524.5833333333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160552&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160552&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	165119	151052.393939394	14066.606060606
2	107269	84415.5833333333	22853.4166666667
3	93497	107902.214285714	-14405.2142857143
4	100269	107902.214285714	-7633.21428571429
5	91627	56769.85	34857.15
6	47552	25173.8571428571	22378.1428571429
7	233933	192751.076923077	41181.9230769231
8	6853	4211.75	2641.25
9	104380	136232.111111111	-31852.1111111111
10	98431	107902.214285714	-9471.21428571429
11	156949	151052.393939394	5896.60606060605
12	81817	107902.214285714	-26085.2142857143
13	59238	56769.85	2468.15
14	101138	151052.393939394	-49914.393939394
15	107158	107902.214285714	-744.21428571429
16	155499	151052.393939394	4446.60606060605
17	156274	136232.111111111	20041.8888888889
18	121777	151052.393939394	-29275.393939394
19	105037	84415.5833333333	20621.4166666667
20	118661	107902.214285714	10758.7857142857
21	131187	107902.214285714	23284.7857142857
22	145026	151052.393939394	-6026.39393939395
23	107016	84415.5833333333	22600.4166666667
24	87242	84415.5833333333	2826.41666666667
25	91699	107902.214285714	-16203.2142857143
26	110087	107902.214285714	2184.78571428571
27	145447	151052.393939394	-5605.39393939395
28	143307	107902.214285714	35404.7857142857
29	61678	56769.85	4908.15
30	210080	151052.393939394	59027.606060606
31	165005	136232.111111111	28772.8888888889
32	97806	107902.214285714	-10096.2142857143
33	184471	151052.393939394	33418.606060606
34	27786	56769.85	-28983.85
35	184458	151052.393939394	33405.606060606
36	98765	107902.214285714	-9137.21428571429
37	178441	151052.393939394	27388.606060606
38	100619	107902.214285714	-7283.21428571429
39	58391	56769.85	1621.15
40	151672	151052.393939394	619.606060606049
41	124437	151052.393939394	-26615.393939394
42	79929	84415.5833333333	-4486.58333333333
43	123064	107902.214285714	15161.7857142857
44	50466	56769.85	-6303.85
45	100991	84415.5833333333	16575.4166666667
46	79367	151052.393939394	-71685.393939394
47	56968	56769.85	198.150000000001
48	106257	107902.214285714	-1645.21428571429
49	178412	192751.076923077	-14339.0769230769
50	98520	84415.5833333333	14104.4166666667
51	153670	107902.214285714	45767.7857142857
52	15049	4211.75	10837.25
53	174478	151052.393939394	23425.606060606
54	25109	25173.8571428571	-64.8571428571413
55	45824	56769.85	-10945.85
56	116772	107902.214285714	8869.78571428571
57	189150	192751.076923077	-3601.07692307694
58	194404	192751.076923077	1652.92307692306
59	185881	151052.393939394	34828.606060606
60	67508	107902.214285714	-40394.2142857143
61	188597	192751.076923077	-4154.07692307694
62	203618	192751.076923077	10866.9230769231
63	87232	107902.214285714	-20670.2142857143
64	110875	107902.214285714	2972.78571428571
65	144756	107902.214285714	36853.7857142857
66	129825	107902.214285714	21922.7857142857
67	92189	84415.5833333333	7773.41666666667
68	121158	107902.214285714	13255.7857142857
69	96219	107902.214285714	-11683.2142857143
70	84128	84415.5833333333	-287.583333333328
71	97960	107902.214285714	-9942.21428571429
72	23824	25173.8571428571	-1349.85714285714
73	103515	107902.214285714	-4387.21428571429
74	91313	107902.214285714	-16589.2142857143
75	85407	84415.5833333333	991.416666666672
76	95871	151052.393939394	-55181.393939394
77	143846	151052.393939394	-7206.39393939395
78	155387	136232.111111111	19154.8888888889
79	74429	84415.5833333333	-9986.58333333333
80	74004	84415.5833333333	-10411.5833333333
81	71987	56769.85	15217.15
82	150629	151052.393939394	-423.393939393951
83	68580	56769.85	11810.15
84	119855	107902.214285714	11952.7857142857
85	55792	56769.85	-977.849999999999
86	25157	56769.85	-31612.85
87	90895	84415.5833333333	6479.41666666667
88	117510	151052.393939394	-33542.393939394
89	144774	151052.393939394	-6278.39393939395
90	77529	84415.5833333333	-6886.58333333333
91	103123	107902.214285714	-4779.21428571429
92	104669	107902.214285714	-3233.21428571429
93	82414	56769.85	25644.15
94	82390	107902.214285714	-25512.2142857143
95	128446	151052.393939394	-22606.393939394
96	111542	136232.111111111	-24690.1111111111
97	136048	136232.111111111	-184.111111111124
98	197257	192751.076923077	4505.92307692306
99	162079	151052.393939394	11026.606060606
100	206286	192751.076923077	13534.9230769231
101	109858	136232.111111111	-26374.1111111111
102	182125	192751.076923077	-10626.0769230769
103	74168	56769.85	17398.15
104	19630	25173.8571428571	-5543.85714285714
105	88634	56769.85	31864.15
106	128321	107902.214285714	20418.7857142857
107	118936	107902.214285714	11033.7857142857
108	127044	151052.393939394	-24008.393939394
109	178377	84415.5833333333	93961.4166666667
110	69581	84415.5833333333	-14834.5833333333
111	168019	192751.076923077	-24732.0769230769
112	113598	151052.393939394	-37454.393939394
113	5841	4211.75	1629.25
114	93116	84415.5833333333	8700.41666666667
115	24610	25173.8571428571	-563.857142857141
116	60611	56769.85	3841.15
117	226620	151052.393939394	75567.606060606
118	6622	4211.75	2410.25
119	121996	107902.214285714	14093.7857142857
120	13155	4211.75	8943.25
121	154158	151052.393939394	3105.60606060605
122	78489	107902.214285714	-29413.2142857143
123	22007	84415.5833333333	-62408.5833333333
124	72530	84415.5833333333	-11885.5833333333
125	13983	25173.8571428571	-11190.8571428571
126	73397	84415.5833333333	-11018.5833333333
127	143878	151052.393939394	-7174.39393939395
128	119956	107902.214285714	12053.7857142857
129	181558	151052.393939394	30505.606060606
130	208236	151052.393939394	57183.606060606
131	237085	192751.076923077	44333.9230769231
132	110297	84415.5833333333	25881.4166666667
133	61394	56769.85	4624.15
134	81420	107902.214285714	-26482.2142857143
135	191154	192751.076923077	-1597.07692307694
136	11798	84415.5833333333	-72617.5833333333
137	135724	192751.076923077	-57027.0769230769
138	68614	56769.85	11844.15
139	139926	107902.214285714	32023.7857142857
140	105203	107902.214285714	-2699.21428571429
141	80338	107902.214285714	-27564.2142857143
142	121376	151052.393939394	-29676.393939394
143	124922	107902.214285714	17019.7857142857
144	10901	56769.85	-45868.85
145	135471	151052.393939394	-15581.393939394
146	66395	84415.5833333333	-18020.5833333333
147	134041	136232.111111111	-2191.11111111112
148	153554	136232.111111111	17321.8888888889
149	0	4211.75	-4211.75
150	7953	4211.75	3741.25
151	0	4211.75	-4211.75
152	0	4211.75	-4211.75
153	0	4211.75	-4211.75
154	0	4211.75	-4211.75
155	98922	107902.214285714	-8980.21428571429
156	165395	151052.393939394	14342.606060606
157	0	4211.75	-4211.75
158	0	4211.75	-4211.75
159	4245	4211.75	33.25
160	21509	25173.8571428571	-3664.85714285714
161	7670	4211.75	3458.25
162	15167	56769.85	-41602.85
163	0	4211.75	-4211.75
164	63891	84415.5833333333	-20524.5833333333

Figure 1

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Postscript link

PDF link

Figure 2

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Figure 3

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Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;

R code (references can be found in the software module):

library(party)
library(Hmisc)
par1 <- as.numeric(par1)
par3 <- as.numeric(par3)
x <- data.frame(t(y))
is.data.frame(x)
x <- x[!is.na(x[,par1]),]
k <- length(x[1,])
n <- length(x[,1])
colnames(x)[par1]
x[,par1]
if (par2 == 'kmeans') {
cl <- kmeans(x[,par1], par3)
print(cl)
clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
clm <- clm[sort.list(clm[,1]),]
for (i in 1:par3) {
cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
}
cl$cluster <- as.factor(cl$cluster)
print(cl$cluster)
x[,par1] <- cl$cluster
}
if (par2 == 'quantiles') {
x[,par1] <- cut2(x[,par1],g=par3)
}
if (par2 == 'hclust') {
hc <- hclust(dist(x[,par1])^2, 'cen')
print(hc)
memb <- cutree(hc, k = par3)
dum <- c(mean(x[memb==1,par1]))
for (i in 2:par3) {
dum <- c(dum, mean(x[memb==i,par1]))
}
hcm <- matrix(cbind(dum,1:par3),ncol=2)
hcm <- hcm[sort.list(hcm[,1]),]
for (i in 1:par3) {
memb[memb==hcm[i,2]] <- paste('C',i,sep='')
}
memb <- as.factor(memb)
print(memb)
x[,par1] <- memb
}
if (par2=='equal') {
ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
x[,par1] <- as.factor(ed)
}
table(x[,par1])
colnames(x)
colnames(x)[par1]
x[,par1]
if (par2 == 'none') {
m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
}
load(file='createtable')
if (par2 != 'none') {
m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
if (par4=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Prediction (training)',par3+1,TRUE)
a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Actual',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
a<-table.row.end(a)
for (i in 1:10) {
ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
if (i==1) {
m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
m.ct.i.actu <- x[ind==1,par1]
m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
m.ct.x.actu <- x[ind==2,par1]
} else {
m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
}
}
print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
numer <- numer + m.ct.i.tab[i,i]
}
print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
numer <- numer + m.ct.x.tab[i,i]
}
print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'Overall',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.i.cp,4))
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.x.cp,4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
}
}
m
bitmap(file='test1.png')
plot(m)
dev.off()
bitmap(file='test1a.png')
plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
dev.off()
if (par2 == 'none') {
forec <- predict(m)
result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
colnames(result) <- c('Actuals','Forecasts','Residuals')
print(result)
}
if (par2 != 'none') {
print(cbind(as.factor(x[,par1]),predict(m)))
myt <- table(as.factor(x[,par1]),predict(m))
print(myt)
}
bitmap(file='test2.png')
if(par2=='none') {
op <- par(mfrow=c(2,2))
plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
par(op)
}
if(par2!='none') {
plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
}
dev.off()
if (par2 == 'none') {
detcoef <- cor(result$Forecasts,result$Actuals)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goodness of Fit',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.element(a,round(detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'R-squared',1,TRUE)
a<-table.element(a,round(detcoef*detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'RMSE',1,TRUE)
a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#',header=TRUE)
a<-table.element(a,'Actuals',header=TRUE)
a<-table.element(a,'Forecasts',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(result$Actuals)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,result$Actuals[i])
a<-table.element(a,result$Forecasts[i])
a<-table.element(a,result$Residuals[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if (par2 != 'none') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
for (i in 1:par3) {
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (j in 1:par3) {
a<-table.element(a,myt[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code