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R Software Module

rwasp_regression_trees1.wasp

Title produced by software

Recursive Partitioning (Regression Trees)

Date of computation

Fri, 23 Dec 2011 10:58:21 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/23/t1324656097rcgu6lm0g0fwimv.htm/, Retrieved Mon, 29 Apr 2024 20:11:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160536, Retrieved Mon, 29 Apr 2024 20:11:40 +0000

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Recursive Partitioning (Regression Trees)] [] [2010-12-05 18:59:57] [b98453cac15ba1066b407e146608df68]
- R PD  [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2011-12-15 19:58:07] [298b545ca29b1a60cbb481c5dea313ae]
-         [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2011-12-15 20:11:10] [298b545ca29b1a60cbb481c5dea313ae]
-   PD      [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2011-12-22 20:50:11] [298b545ca29b1a60cbb481c5dea313ae]
-   PD          [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2011-12-23 15:58:21] [ccdbcd1f4b80805a70032cb1a2c4c931] [Current]
-   P             [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2011-12-23 16:48:21] [298b545ca29b1a60cbb481c5dea313ae] 

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Dataseries X:

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Histogram

Boxplots

162687	0	48	21	20465	23975	39
201906	1	58	20	33629	85634	46
7215	0	0	0	1423	1929	0
146367	0	67	27	25629	36294	54
257045	0	83	31	54002	72255	93
524450	1	136	36	151036	189748	198
188294	1	65	23	33287	61834	42
195674	0	86	30	31172	68167	59
177020	0	62	30	28113	38462	49
325899	1	71	27	57803	101219	83
121844	2	50	24	49830	43270	49
203938	0	88	30	52143	76183	83
113213	0	61	22	21055	31476	39
220751	4	79	28	47007	62157	93
172905	4	56	18	28735	46261	31
156326	3	54	22	59147	50063	29
145178	0	81	37	78950	64483	104
89171	5	13	15	13497	2341	2
172624	0	74	34	46154	48149	46
39790	0	18	18	53249	12743	27
87927	0	31	15	10726	18743	16
241285	0	99	30	83700	97057	108
195820	1	38	25	40400	17675	36
146946	1	59	34	33797	33106	33
159763	1	54	21	36205	53311	46
207078	0	63	21	30165	42754	65
212394	0	66	25	58534	59056	80
201536	0	90	31	44663	101621	81
394662	0	72	31	92556	118120	69
217892	0	61	20	40078	79572	69
182286	0	61	28	34711	42744	37
181740	2	61	22	31076	65931	45
137978	4	53	17	74608	38575	62
255929	0	118	25	58092	28795	33
236489	1	73	25	42009	94440	77
0	0	0	0	0	0	0
230761	0	54	31	36022	38229	34
132807	3	54	14	23333	31972	44
157118	9	46	35	53349	40071	43
253254	0	83	34	92596	132480	117
269329	2	106	22	49598	62797	125
161273	0	44	34	44093	40429	49
107181	2	27	23	84205	45545	76
195891	1	64	24	63369	57568	81
139667	2	71	26	60132	39019	111
171101	2	44	23	37403	53866	61
81407	1	23	35	24460	38345	56
247563	0	78	24	46456	50210	54
239807	1	60	31	66616	80947	47
172743	8	73	30	41554	43461	55
48188	0	12	22	22346	14812	14
169355	0	104	23	30874	37819	44
315622	0	83	27	68701	102738	115
241518	0	57	30	35728	54509	57
195583	1	67	33	29010	62956	48
159913	8	44	12	23110	55411	40
220241	0	53	26	38844	50611	51
101694	1	26	26	27084	26692	32
157258	0	67	23	35139	60056	36
202536	10	36	38	57476	25155	47
173505	6	56	32	33277	42840	51
150518	0	52	21	31141	39358	37
141491	11	54	22	61281	47241	52
125612	3	57	26	25820	49611	42
166049	0	27	28	23284	41833	11
124197	0	58	33	35378	48930	47
195043	8	76	36	74990	110600	59
138708	2	93	25	29653	52235	82
116552	0	59	25	64622	53986	49
31970	0	5	21	4157	4105	6
258158	3	57	19	29245	59331	83
151184	1	42	12	50008	47796	56
135926	2	88	30	52338	38302	114
119629	1	53	21	13310	14063	46
171518	0	81	39	92901	54414	46
108949	2	35	32	10956	9903	2
183471	1	102	28	34241	53987	51
159966	0	71	29	75043	88937	96
93786	0	28	21	21152	21928	20
84971	0	34	31	42249	29487	57
88882	0	54	26	42005	35334	49
304603	0	49	29	41152	57596	51
75101	1	30	23	14399	29750	40
145043	0	57	25	28263	41029	40
95827	0	54	22	17215	12416	36
173924	0	38	26	48140	51158	64
241957	0	63	33	62897	79935	117
115367	0	58	24	22883	26552	40
118408	7	46	24	41622	25807	46
164078	0	46	21	40715	50620	61
158931	5	51	28	65897	61467	59
184139	1	87	28	76542	65292	94
152856	0	39	25	37477	55516	36
144014	0	28	15	53216	42006	51
62535	0	26	13	40911	26273	39
245196	0	52	36	57021	90248	62
199841	0	96	27	73116	61476	79
19349	0	13	1	3895	9604	14
247280	3	43	24	46609	45108	45
159408	0	42	31	29351	47232	43
72128	0	30	4	2325	3439	8
104253	0	59	21	31747	30553	41
151090	0	73	27	32665	24751	25
137382	1	39	23	19249	34458	22
87448	1	36	12	15292	24649	18
27676	0	2	16	5842	2342	3
165507	0	102	29	33994	52739	54
132148	1	30	26	13018	6245	6
0	0	0	0	0	0	0
95778	0	46	25	98177	35381	50
109001	0	25	21	37941	19595	33
158833	0	59	24	31032	50848	54
147690	1	60	21	32683	39443	63
89887	0	36	21	34545	27023	56
3616	0	0	0	0	0	0
0	0	0	0	0	0	0
199005	0	45	23	27525	61022	49
160930	0	79	33	66856	63528	90
177948	2	30	32	28549	34835	51
136061	0	43	23	38610	37172	29
43410	0	7	1	2781	13	1
184277	1	80	29	41211	62548	68
108858	0	32	20	22698	31334	29
141744	8	81	33	41194	20839	27
60493	3	3	12	32689	5084	4
19764	1	10	2	5752	9927	10
177559	3	47	21	26757	53229	47
140281	0	35	28	22527	29877	44
164249	0	54	35	44810	37310	53
11796	0	1	2	0	0	0
10674	0	0	0	0	0	0
151322	0	46	18	100674	50067	40
6836	0	0	1	0	0	0
174712	6	51	21	57786	47708	57
5118	0	5	0	0	0	0
40248	1	8	4	5444	6012	6
0	0	0	0	0	0	0
127628	0	38	29	28470	27749	24
88837	0	21	26	61849	47555	34
7131	1	0	0	0	0	0
9056	0	0	4	2179	1336	10
87957	1	18	19	8019	11017	16
144470	0	53	22	39644	55184	93
111408	1	17	22	23494	43485	28

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160536&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]4 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=160536&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160536&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	4 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Goodness of Fit
Correlation	0.8614
R-squared	0.7421
RMSE	40920.7472

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.8614 \tabularnewline
R-squared & 0.7421 \tabularnewline
RMSE & 40920.7472 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160536&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.8614[/C][/ROW]
[ROW][C]R-squared[/C][C]0.7421[/C][/ROW]
[ROW][C]RMSE[/C][C]40920.7472[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160536&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160536&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	0.8614
R-squared	0.7421
RMSE	40920.7472

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	162687	159178.258064516	3508.74193548388
2	201906	209194.892857143	-7288.89285714287
3	7215	17536.3684210526	-10321.3684210526
4	146367	159178.258064516	-12811.2580645161
5	257045	209194.892857143	47850.1071428571
6	524450	315780.857142857	208669.142857143
7	188294	209194.892857143	-20900.8928571429
8	195674	209194.892857143	-13520.8928571429
9	177020	159178.258064516	17841.7419354839
10	325899	315780.857142857	10118.1428571428
11	121844	159178.258064516	-37334.2580645161
12	203938	209194.892857143	-5256.89285714287
13	113213	159178.258064516	-45965.2580645161
14	220751	209194.892857143	11556.1071428571
15	172905	159178.258064516	13726.7419354839
16	156326	159178.258064516	-2852.25806451612
17	145178	209194.892857143	-64016.8928571429
18	89171	84994.2222222222	4176.77777777778
19	172624	159178.258064516	13445.7419354839
20	39790	84994.2222222222	-45204.2222222222
21	87927	111624.684210526	-23697.6842105263
22	241285	209194.892857143	32090.1071428571
23	195820	159178.258064516	36641.7419354839
24	146946	159178.258064516	-12232.2580645161
25	159763	159178.258064516	584.741935483878
26	207078	159178.258064516	47899.7419354839
27	212394	209194.892857143	3199.10714285713
28	201536	315780.857142857	-114244.857142857
29	394662	315780.857142857	78881.1428571428
30	217892	209194.892857143	8697.10714285713
31	182286	159178.258064516	23107.7419354839
32	181740	209194.892857143	-27454.8928571429
33	137978	159178.258064516	-21200.2580645161
34	255929	159178.258064516	96750.7419354839
35	236489	209194.892857143	27294.1071428571
36	0	17536.3684210526	-17536.3684210526
37	230761	159178.258064516	71582.7419354839
38	132807	159178.258064516	-26371.2580645161
39	157118	159178.258064516	-2060.25806451612
40	253254	315780.857142857	-62526.8571428572
41	269329	209194.892857143	60134.1071428571
42	161273	159178.258064516	2094.74193548388
43	107181	111624.684210526	-4443.68421052632
44	195891	209194.892857143	-13303.8928571429
45	139667	159178.258064516	-19511.2580645161
46	171101	159178.258064516	11922.7419354839
47	81407	111624.684210526	-30217.6842105263
48	247563	159178.258064516	88384.7419354839
49	239807	209194.892857143	30612.1071428571
50	172743	159178.258064516	13564.7419354839
51	48188	17536.3684210526	30651.6315789474
52	169355	159178.258064516	10176.7419354839
53	315622	315780.857142857	-158.857142857159
54	241518	159178.258064516	82339.7419354839
55	195583	209194.892857143	-13611.8928571429
56	159913	159178.258064516	734.741935483878
57	220241	159178.258064516	61062.7419354839
58	101694	111624.684210526	-9930.68421052632
59	157258	209194.892857143	-51936.8928571429
60	202536	111624.684210526	90911.3157894737
61	173505	159178.258064516	14326.7419354839
62	150518	159178.258064516	-8660.25806451612
63	141491	159178.258064516	-17687.2580645161
64	125612	159178.258064516	-33566.2580645161
65	166049	111624.684210526	54424.3157894737
66	124197	159178.258064516	-34981.2580645161
67	195043	315780.857142857	-120737.857142857
68	138708	159178.258064516	-20470.2580645161
69	116552	159178.258064516	-42626.2580645161
70	31970	17536.3684210526	14433.6315789474
71	258158	209194.892857143	48963.1071428571
72	151184	159178.258064516	-7994.25806451612
73	135926	159178.258064516	-23252.2580645161
74	119629	84994.2222222222	34634.7777777778
75	171518	159178.258064516	12339.7419354839
76	108949	84994.2222222222	23954.7777777778
77	183471	159178.258064516	24292.7419354839
78	159966	209194.892857143	-49228.8928571429
79	93786	111624.684210526	-17838.6842105263
80	84971	111624.684210526	-26653.6842105263
81	88882	159178.258064516	-70296.2580645161
82	304603	209194.892857143	95408.1071428571
83	75101	111624.684210526	-36523.6842105263
84	145043	159178.258064516	-14135.2580645161
85	95827	84994.2222222222	10832.7777777778
86	173924	159178.258064516	14745.7419354839
87	241957	209194.892857143	32762.1071428571
88	115367	159178.258064516	-43811.2580645161
89	118408	159178.258064516	-40770.2580645161
90	164078	159178.258064516	4899.74193548388
91	158931	209194.892857143	-50263.8928571429
92	184139	209194.892857143	-25055.8928571429
93	152856	159178.258064516	-6322.25806451612
94	144014	111624.684210526	32389.3157894737
95	62535	111624.684210526	-49089.6842105263
96	245196	209194.892857143	36001.1071428571
97	199841	209194.892857143	-9353.89285714287
98	19349	84994.2222222222	-65645.2222222222
99	247280	159178.258064516	88101.7419354839
100	159408	159178.258064516	229.741935483878
101	72128	84994.2222222222	-12866.2222222222
102	104253	159178.258064516	-54925.2580645161
103	151090	159178.258064516	-8088.25806451612
104	137382	159178.258064516	-21796.2580645161
105	87448	111624.684210526	-24176.6842105263
106	27676	17536.3684210526	10139.6315789474
107	165507	159178.258064516	6328.74193548388
108	132148	84994.2222222222	47153.7777777778
109	0	17536.3684210526	-17536.3684210526
110	95778	159178.258064516	-63400.2580645161
111	109001	111624.684210526	-2623.68421052632
112	158833	159178.258064516	-345.258064516122
113	147690	159178.258064516	-11488.2580645161
114	89887	111624.684210526	-21737.6842105263
115	3616	17536.3684210526	-13920.3684210526
116	0	17536.3684210526	-17536.3684210526
117	199005	209194.892857143	-10189.8928571429
118	160930	209194.892857143	-48264.8928571429
119	177948	111624.684210526	66323.3157894737
120	136061	159178.258064516	-23117.2580645161
121	43410	17536.3684210526	25873.6315789474
122	184277	209194.892857143	-24917.8928571429
123	108858	111624.684210526	-2766.68421052632
124	141744	159178.258064516	-17434.2580645161
125	60493	17536.3684210526	42956.6315789474
126	19764	17536.3684210526	2227.63157894737
127	177559	159178.258064516	18380.7419354839
128	140281	111624.684210526	28656.3157894737
129	164249	159178.258064516	5070.74193548388
130	11796	17536.3684210526	-5740.36842105263
131	10674	17536.3684210526	-6862.36842105263
132	151322	159178.258064516	-7856.25806451612
133	6836	17536.3684210526	-10700.3684210526
134	174712	159178.258064516	15533.7419354839
135	5118	17536.3684210526	-12418.3684210526
136	40248	17536.3684210526	22711.6315789474
137	0	17536.3684210526	-17536.3684210526
138	127628	159178.258064516	-31550.2580645161
139	88837	111624.684210526	-22787.6842105263
140	7131	17536.3684210526	-10405.3684210526
141	9056	17536.3684210526	-8480.36842105263
142	87957	84994.2222222222	2962.77777777778
143	144470	159178.258064516	-14708.2580645161
144	111408	111624.684210526	-216.68421052632

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 162687 & 159178.258064516 & 3508.74193548388 \tabularnewline
2 & 201906 & 209194.892857143 & -7288.89285714287 \tabularnewline
3 & 7215 & 17536.3684210526 & -10321.3684210526 \tabularnewline
4 & 146367 & 159178.258064516 & -12811.2580645161 \tabularnewline
5 & 257045 & 209194.892857143 & 47850.1071428571 \tabularnewline
6 & 524450 & 315780.857142857 & 208669.142857143 \tabularnewline
7 & 188294 & 209194.892857143 & -20900.8928571429 \tabularnewline
8 & 195674 & 209194.892857143 & -13520.8928571429 \tabularnewline
9 & 177020 & 159178.258064516 & 17841.7419354839 \tabularnewline
10 & 325899 & 315780.857142857 & 10118.1428571428 \tabularnewline
11 & 121844 & 159178.258064516 & -37334.2580645161 \tabularnewline
12 & 203938 & 209194.892857143 & -5256.89285714287 \tabularnewline
13 & 113213 & 159178.258064516 & -45965.2580645161 \tabularnewline
14 & 220751 & 209194.892857143 & 11556.1071428571 \tabularnewline
15 & 172905 & 159178.258064516 & 13726.7419354839 \tabularnewline
16 & 156326 & 159178.258064516 & -2852.25806451612 \tabularnewline
17 & 145178 & 209194.892857143 & -64016.8928571429 \tabularnewline
18 & 89171 & 84994.2222222222 & 4176.77777777778 \tabularnewline
19 & 172624 & 159178.258064516 & 13445.7419354839 \tabularnewline
20 & 39790 & 84994.2222222222 & -45204.2222222222 \tabularnewline
21 & 87927 & 111624.684210526 & -23697.6842105263 \tabularnewline
22 & 241285 & 209194.892857143 & 32090.1071428571 \tabularnewline
23 & 195820 & 159178.258064516 & 36641.7419354839 \tabularnewline
24 & 146946 & 159178.258064516 & -12232.2580645161 \tabularnewline
25 & 159763 & 159178.258064516 & 584.741935483878 \tabularnewline
26 & 207078 & 159178.258064516 & 47899.7419354839 \tabularnewline
27 & 212394 & 209194.892857143 & 3199.10714285713 \tabularnewline
28 & 201536 & 315780.857142857 & -114244.857142857 \tabularnewline
29 & 394662 & 315780.857142857 & 78881.1428571428 \tabularnewline
30 & 217892 & 209194.892857143 & 8697.10714285713 \tabularnewline
31 & 182286 & 159178.258064516 & 23107.7419354839 \tabularnewline
32 & 181740 & 209194.892857143 & -27454.8928571429 \tabularnewline
33 & 137978 & 159178.258064516 & -21200.2580645161 \tabularnewline
34 & 255929 & 159178.258064516 & 96750.7419354839 \tabularnewline
35 & 236489 & 209194.892857143 & 27294.1071428571 \tabularnewline
36 & 0 & 17536.3684210526 & -17536.3684210526 \tabularnewline
37 & 230761 & 159178.258064516 & 71582.7419354839 \tabularnewline
38 & 132807 & 159178.258064516 & -26371.2580645161 \tabularnewline
39 & 157118 & 159178.258064516 & -2060.25806451612 \tabularnewline
40 & 253254 & 315780.857142857 & -62526.8571428572 \tabularnewline
41 & 269329 & 209194.892857143 & 60134.1071428571 \tabularnewline
42 & 161273 & 159178.258064516 & 2094.74193548388 \tabularnewline
43 & 107181 & 111624.684210526 & -4443.68421052632 \tabularnewline
44 & 195891 & 209194.892857143 & -13303.8928571429 \tabularnewline
45 & 139667 & 159178.258064516 & -19511.2580645161 \tabularnewline
46 & 171101 & 159178.258064516 & 11922.7419354839 \tabularnewline
47 & 81407 & 111624.684210526 & -30217.6842105263 \tabularnewline
48 & 247563 & 159178.258064516 & 88384.7419354839 \tabularnewline
49 & 239807 & 209194.892857143 & 30612.1071428571 \tabularnewline
50 & 172743 & 159178.258064516 & 13564.7419354839 \tabularnewline
51 & 48188 & 17536.3684210526 & 30651.6315789474 \tabularnewline
52 & 169355 & 159178.258064516 & 10176.7419354839 \tabularnewline
53 & 315622 & 315780.857142857 & -158.857142857159 \tabularnewline
54 & 241518 & 159178.258064516 & 82339.7419354839 \tabularnewline
55 & 195583 & 209194.892857143 & -13611.8928571429 \tabularnewline
56 & 159913 & 159178.258064516 & 734.741935483878 \tabularnewline
57 & 220241 & 159178.258064516 & 61062.7419354839 \tabularnewline
58 & 101694 & 111624.684210526 & -9930.68421052632 \tabularnewline
59 & 157258 & 209194.892857143 & -51936.8928571429 \tabularnewline
60 & 202536 & 111624.684210526 & 90911.3157894737 \tabularnewline
61 & 173505 & 159178.258064516 & 14326.7419354839 \tabularnewline
62 & 150518 & 159178.258064516 & -8660.25806451612 \tabularnewline
63 & 141491 & 159178.258064516 & -17687.2580645161 \tabularnewline
64 & 125612 & 159178.258064516 & -33566.2580645161 \tabularnewline
65 & 166049 & 111624.684210526 & 54424.3157894737 \tabularnewline
66 & 124197 & 159178.258064516 & -34981.2580645161 \tabularnewline
67 & 195043 & 315780.857142857 & -120737.857142857 \tabularnewline
68 & 138708 & 159178.258064516 & -20470.2580645161 \tabularnewline
69 & 116552 & 159178.258064516 & -42626.2580645161 \tabularnewline
70 & 31970 & 17536.3684210526 & 14433.6315789474 \tabularnewline
71 & 258158 & 209194.892857143 & 48963.1071428571 \tabularnewline
72 & 151184 & 159178.258064516 & -7994.25806451612 \tabularnewline
73 & 135926 & 159178.258064516 & -23252.2580645161 \tabularnewline
74 & 119629 & 84994.2222222222 & 34634.7777777778 \tabularnewline
75 & 171518 & 159178.258064516 & 12339.7419354839 \tabularnewline
76 & 108949 & 84994.2222222222 & 23954.7777777778 \tabularnewline
77 & 183471 & 159178.258064516 & 24292.7419354839 \tabularnewline
78 & 159966 & 209194.892857143 & -49228.8928571429 \tabularnewline
79 & 93786 & 111624.684210526 & -17838.6842105263 \tabularnewline
80 & 84971 & 111624.684210526 & -26653.6842105263 \tabularnewline
81 & 88882 & 159178.258064516 & -70296.2580645161 \tabularnewline
82 & 304603 & 209194.892857143 & 95408.1071428571 \tabularnewline
83 & 75101 & 111624.684210526 & -36523.6842105263 \tabularnewline
84 & 145043 & 159178.258064516 & -14135.2580645161 \tabularnewline
85 & 95827 & 84994.2222222222 & 10832.7777777778 \tabularnewline
86 & 173924 & 159178.258064516 & 14745.7419354839 \tabularnewline
87 & 241957 & 209194.892857143 & 32762.1071428571 \tabularnewline
88 & 115367 & 159178.258064516 & -43811.2580645161 \tabularnewline
89 & 118408 & 159178.258064516 & -40770.2580645161 \tabularnewline
90 & 164078 & 159178.258064516 & 4899.74193548388 \tabularnewline
91 & 158931 & 209194.892857143 & -50263.8928571429 \tabularnewline
92 & 184139 & 209194.892857143 & -25055.8928571429 \tabularnewline
93 & 152856 & 159178.258064516 & -6322.25806451612 \tabularnewline
94 & 144014 & 111624.684210526 & 32389.3157894737 \tabularnewline
95 & 62535 & 111624.684210526 & -49089.6842105263 \tabularnewline
96 & 245196 & 209194.892857143 & 36001.1071428571 \tabularnewline
97 & 199841 & 209194.892857143 & -9353.89285714287 \tabularnewline
98 & 19349 & 84994.2222222222 & -65645.2222222222 \tabularnewline
99 & 247280 & 159178.258064516 & 88101.7419354839 \tabularnewline
100 & 159408 & 159178.258064516 & 229.741935483878 \tabularnewline
101 & 72128 & 84994.2222222222 & -12866.2222222222 \tabularnewline
102 & 104253 & 159178.258064516 & -54925.2580645161 \tabularnewline
103 & 151090 & 159178.258064516 & -8088.25806451612 \tabularnewline
104 & 137382 & 159178.258064516 & -21796.2580645161 \tabularnewline
105 & 87448 & 111624.684210526 & -24176.6842105263 \tabularnewline
106 & 27676 & 17536.3684210526 & 10139.6315789474 \tabularnewline
107 & 165507 & 159178.258064516 & 6328.74193548388 \tabularnewline
108 & 132148 & 84994.2222222222 & 47153.7777777778 \tabularnewline
109 & 0 & 17536.3684210526 & -17536.3684210526 \tabularnewline
110 & 95778 & 159178.258064516 & -63400.2580645161 \tabularnewline
111 & 109001 & 111624.684210526 & -2623.68421052632 \tabularnewline
112 & 158833 & 159178.258064516 & -345.258064516122 \tabularnewline
113 & 147690 & 159178.258064516 & -11488.2580645161 \tabularnewline
114 & 89887 & 111624.684210526 & -21737.6842105263 \tabularnewline
115 & 3616 & 17536.3684210526 & -13920.3684210526 \tabularnewline
116 & 0 & 17536.3684210526 & -17536.3684210526 \tabularnewline
117 & 199005 & 209194.892857143 & -10189.8928571429 \tabularnewline
118 & 160930 & 209194.892857143 & -48264.8928571429 \tabularnewline
119 & 177948 & 111624.684210526 & 66323.3157894737 \tabularnewline
120 & 136061 & 159178.258064516 & -23117.2580645161 \tabularnewline
121 & 43410 & 17536.3684210526 & 25873.6315789474 \tabularnewline
122 & 184277 & 209194.892857143 & -24917.8928571429 \tabularnewline
123 & 108858 & 111624.684210526 & -2766.68421052632 \tabularnewline
124 & 141744 & 159178.258064516 & -17434.2580645161 \tabularnewline
125 & 60493 & 17536.3684210526 & 42956.6315789474 \tabularnewline
126 & 19764 & 17536.3684210526 & 2227.63157894737 \tabularnewline
127 & 177559 & 159178.258064516 & 18380.7419354839 \tabularnewline
128 & 140281 & 111624.684210526 & 28656.3157894737 \tabularnewline
129 & 164249 & 159178.258064516 & 5070.74193548388 \tabularnewline
130 & 11796 & 17536.3684210526 & -5740.36842105263 \tabularnewline
131 & 10674 & 17536.3684210526 & -6862.36842105263 \tabularnewline
132 & 151322 & 159178.258064516 & -7856.25806451612 \tabularnewline
133 & 6836 & 17536.3684210526 & -10700.3684210526 \tabularnewline
134 & 174712 & 159178.258064516 & 15533.7419354839 \tabularnewline
135 & 5118 & 17536.3684210526 & -12418.3684210526 \tabularnewline
136 & 40248 & 17536.3684210526 & 22711.6315789474 \tabularnewline
137 & 0 & 17536.3684210526 & -17536.3684210526 \tabularnewline
138 & 127628 & 159178.258064516 & -31550.2580645161 \tabularnewline
139 & 88837 & 111624.684210526 & -22787.6842105263 \tabularnewline
140 & 7131 & 17536.3684210526 & -10405.3684210526 \tabularnewline
141 & 9056 & 17536.3684210526 & -8480.36842105263 \tabularnewline
142 & 87957 & 84994.2222222222 & 2962.77777777778 \tabularnewline
143 & 144470 & 159178.258064516 & -14708.2580645161 \tabularnewline
144 & 111408 & 111624.684210526 & -216.68421052632 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160536&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]162687[/C][C]159178.258064516[/C][C]3508.74193548388[/C][/ROW]
[ROW][C]2[/C][C]201906[/C][C]209194.892857143[/C][C]-7288.89285714287[/C][/ROW]
[ROW][C]3[/C][C]7215[/C][C]17536.3684210526[/C][C]-10321.3684210526[/C][/ROW]
[ROW][C]4[/C][C]146367[/C][C]159178.258064516[/C][C]-12811.2580645161[/C][/ROW]
[ROW][C]5[/C][C]257045[/C][C]209194.892857143[/C][C]47850.1071428571[/C][/ROW]
[ROW][C]6[/C][C]524450[/C][C]315780.857142857[/C][C]208669.142857143[/C][/ROW]
[ROW][C]7[/C][C]188294[/C][C]209194.892857143[/C][C]-20900.8928571429[/C][/ROW]
[ROW][C]8[/C][C]195674[/C][C]209194.892857143[/C][C]-13520.8928571429[/C][/ROW]
[ROW][C]9[/C][C]177020[/C][C]159178.258064516[/C][C]17841.7419354839[/C][/ROW]
[ROW][C]10[/C][C]325899[/C][C]315780.857142857[/C][C]10118.1428571428[/C][/ROW]
[ROW][C]11[/C][C]121844[/C][C]159178.258064516[/C][C]-37334.2580645161[/C][/ROW]
[ROW][C]12[/C][C]203938[/C][C]209194.892857143[/C][C]-5256.89285714287[/C][/ROW]
[ROW][C]13[/C][C]113213[/C][C]159178.258064516[/C][C]-45965.2580645161[/C][/ROW]
[ROW][C]14[/C][C]220751[/C][C]209194.892857143[/C][C]11556.1071428571[/C][/ROW]
[ROW][C]15[/C][C]172905[/C][C]159178.258064516[/C][C]13726.7419354839[/C][/ROW]
[ROW][C]16[/C][C]156326[/C][C]159178.258064516[/C][C]-2852.25806451612[/C][/ROW]
[ROW][C]17[/C][C]145178[/C][C]209194.892857143[/C][C]-64016.8928571429[/C][/ROW]
[ROW][C]18[/C][C]89171[/C][C]84994.2222222222[/C][C]4176.77777777778[/C][/ROW]
[ROW][C]19[/C][C]172624[/C][C]159178.258064516[/C][C]13445.7419354839[/C][/ROW]
[ROW][C]20[/C][C]39790[/C][C]84994.2222222222[/C][C]-45204.2222222222[/C][/ROW]
[ROW][C]21[/C][C]87927[/C][C]111624.684210526[/C][C]-23697.6842105263[/C][/ROW]
[ROW][C]22[/C][C]241285[/C][C]209194.892857143[/C][C]32090.1071428571[/C][/ROW]
[ROW][C]23[/C][C]195820[/C][C]159178.258064516[/C][C]36641.7419354839[/C][/ROW]
[ROW][C]24[/C][C]146946[/C][C]159178.258064516[/C][C]-12232.2580645161[/C][/ROW]
[ROW][C]25[/C][C]159763[/C][C]159178.258064516[/C][C]584.741935483878[/C][/ROW]
[ROW][C]26[/C][C]207078[/C][C]159178.258064516[/C][C]47899.7419354839[/C][/ROW]
[ROW][C]27[/C][C]212394[/C][C]209194.892857143[/C][C]3199.10714285713[/C][/ROW]
[ROW][C]28[/C][C]201536[/C][C]315780.857142857[/C][C]-114244.857142857[/C][/ROW]
[ROW][C]29[/C][C]394662[/C][C]315780.857142857[/C][C]78881.1428571428[/C][/ROW]
[ROW][C]30[/C][C]217892[/C][C]209194.892857143[/C][C]8697.10714285713[/C][/ROW]
[ROW][C]31[/C][C]182286[/C][C]159178.258064516[/C][C]23107.7419354839[/C][/ROW]
[ROW][C]32[/C][C]181740[/C][C]209194.892857143[/C][C]-27454.8928571429[/C][/ROW]
[ROW][C]33[/C][C]137978[/C][C]159178.258064516[/C][C]-21200.2580645161[/C][/ROW]
[ROW][C]34[/C][C]255929[/C][C]159178.258064516[/C][C]96750.7419354839[/C][/ROW]
[ROW][C]35[/C][C]236489[/C][C]209194.892857143[/C][C]27294.1071428571[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]17536.3684210526[/C][C]-17536.3684210526[/C][/ROW]
[ROW][C]37[/C][C]230761[/C][C]159178.258064516[/C][C]71582.7419354839[/C][/ROW]
[ROW][C]38[/C][C]132807[/C][C]159178.258064516[/C][C]-26371.2580645161[/C][/ROW]
[ROW][C]39[/C][C]157118[/C][C]159178.258064516[/C][C]-2060.25806451612[/C][/ROW]
[ROW][C]40[/C][C]253254[/C][C]315780.857142857[/C][C]-62526.8571428572[/C][/ROW]
[ROW][C]41[/C][C]269329[/C][C]209194.892857143[/C][C]60134.1071428571[/C][/ROW]
[ROW][C]42[/C][C]161273[/C][C]159178.258064516[/C][C]2094.74193548388[/C][/ROW]
[ROW][C]43[/C][C]107181[/C][C]111624.684210526[/C][C]-4443.68421052632[/C][/ROW]
[ROW][C]44[/C][C]195891[/C][C]209194.892857143[/C][C]-13303.8928571429[/C][/ROW]
[ROW][C]45[/C][C]139667[/C][C]159178.258064516[/C][C]-19511.2580645161[/C][/ROW]
[ROW][C]46[/C][C]171101[/C][C]159178.258064516[/C][C]11922.7419354839[/C][/ROW]
[ROW][C]47[/C][C]81407[/C][C]111624.684210526[/C][C]-30217.6842105263[/C][/ROW]
[ROW][C]48[/C][C]247563[/C][C]159178.258064516[/C][C]88384.7419354839[/C][/ROW]
[ROW][C]49[/C][C]239807[/C][C]209194.892857143[/C][C]30612.1071428571[/C][/ROW]
[ROW][C]50[/C][C]172743[/C][C]159178.258064516[/C][C]13564.7419354839[/C][/ROW]
[ROW][C]51[/C][C]48188[/C][C]17536.3684210526[/C][C]30651.6315789474[/C][/ROW]
[ROW][C]52[/C][C]169355[/C][C]159178.258064516[/C][C]10176.7419354839[/C][/ROW]
[ROW][C]53[/C][C]315622[/C][C]315780.857142857[/C][C]-158.857142857159[/C][/ROW]
[ROW][C]54[/C][C]241518[/C][C]159178.258064516[/C][C]82339.7419354839[/C][/ROW]
[ROW][C]55[/C][C]195583[/C][C]209194.892857143[/C][C]-13611.8928571429[/C][/ROW]
[ROW][C]56[/C][C]159913[/C][C]159178.258064516[/C][C]734.741935483878[/C][/ROW]
[ROW][C]57[/C][C]220241[/C][C]159178.258064516[/C][C]61062.7419354839[/C][/ROW]
[ROW][C]58[/C][C]101694[/C][C]111624.684210526[/C][C]-9930.68421052632[/C][/ROW]
[ROW][C]59[/C][C]157258[/C][C]209194.892857143[/C][C]-51936.8928571429[/C][/ROW]
[ROW][C]60[/C][C]202536[/C][C]111624.684210526[/C][C]90911.3157894737[/C][/ROW]
[ROW][C]61[/C][C]173505[/C][C]159178.258064516[/C][C]14326.7419354839[/C][/ROW]
[ROW][C]62[/C][C]150518[/C][C]159178.258064516[/C][C]-8660.25806451612[/C][/ROW]
[ROW][C]63[/C][C]141491[/C][C]159178.258064516[/C][C]-17687.2580645161[/C][/ROW]
[ROW][C]64[/C][C]125612[/C][C]159178.258064516[/C][C]-33566.2580645161[/C][/ROW]
[ROW][C]65[/C][C]166049[/C][C]111624.684210526[/C][C]54424.3157894737[/C][/ROW]
[ROW][C]66[/C][C]124197[/C][C]159178.258064516[/C][C]-34981.2580645161[/C][/ROW]
[ROW][C]67[/C][C]195043[/C][C]315780.857142857[/C][C]-120737.857142857[/C][/ROW]
[ROW][C]68[/C][C]138708[/C][C]159178.258064516[/C][C]-20470.2580645161[/C][/ROW]
[ROW][C]69[/C][C]116552[/C][C]159178.258064516[/C][C]-42626.2580645161[/C][/ROW]
[ROW][C]70[/C][C]31970[/C][C]17536.3684210526[/C][C]14433.6315789474[/C][/ROW]
[ROW][C]71[/C][C]258158[/C][C]209194.892857143[/C][C]48963.1071428571[/C][/ROW]
[ROW][C]72[/C][C]151184[/C][C]159178.258064516[/C][C]-7994.25806451612[/C][/ROW]
[ROW][C]73[/C][C]135926[/C][C]159178.258064516[/C][C]-23252.2580645161[/C][/ROW]
[ROW][C]74[/C][C]119629[/C][C]84994.2222222222[/C][C]34634.7777777778[/C][/ROW]
[ROW][C]75[/C][C]171518[/C][C]159178.258064516[/C][C]12339.7419354839[/C][/ROW]
[ROW][C]76[/C][C]108949[/C][C]84994.2222222222[/C][C]23954.7777777778[/C][/ROW]
[ROW][C]77[/C][C]183471[/C][C]159178.258064516[/C][C]24292.7419354839[/C][/ROW]
[ROW][C]78[/C][C]159966[/C][C]209194.892857143[/C][C]-49228.8928571429[/C][/ROW]
[ROW][C]79[/C][C]93786[/C][C]111624.684210526[/C][C]-17838.6842105263[/C][/ROW]
[ROW][C]80[/C][C]84971[/C][C]111624.684210526[/C][C]-26653.6842105263[/C][/ROW]
[ROW][C]81[/C][C]88882[/C][C]159178.258064516[/C][C]-70296.2580645161[/C][/ROW]
[ROW][C]82[/C][C]304603[/C][C]209194.892857143[/C][C]95408.1071428571[/C][/ROW]
[ROW][C]83[/C][C]75101[/C][C]111624.684210526[/C][C]-36523.6842105263[/C][/ROW]
[ROW][C]84[/C][C]145043[/C][C]159178.258064516[/C][C]-14135.2580645161[/C][/ROW]
[ROW][C]85[/C][C]95827[/C][C]84994.2222222222[/C][C]10832.7777777778[/C][/ROW]
[ROW][C]86[/C][C]173924[/C][C]159178.258064516[/C][C]14745.7419354839[/C][/ROW]
[ROW][C]87[/C][C]241957[/C][C]209194.892857143[/C][C]32762.1071428571[/C][/ROW]
[ROW][C]88[/C][C]115367[/C][C]159178.258064516[/C][C]-43811.2580645161[/C][/ROW]
[ROW][C]89[/C][C]118408[/C][C]159178.258064516[/C][C]-40770.2580645161[/C][/ROW]
[ROW][C]90[/C][C]164078[/C][C]159178.258064516[/C][C]4899.74193548388[/C][/ROW]
[ROW][C]91[/C][C]158931[/C][C]209194.892857143[/C][C]-50263.8928571429[/C][/ROW]
[ROW][C]92[/C][C]184139[/C][C]209194.892857143[/C][C]-25055.8928571429[/C][/ROW]
[ROW][C]93[/C][C]152856[/C][C]159178.258064516[/C][C]-6322.25806451612[/C][/ROW]
[ROW][C]94[/C][C]144014[/C][C]111624.684210526[/C][C]32389.3157894737[/C][/ROW]
[ROW][C]95[/C][C]62535[/C][C]111624.684210526[/C][C]-49089.6842105263[/C][/ROW]
[ROW][C]96[/C][C]245196[/C][C]209194.892857143[/C][C]36001.1071428571[/C][/ROW]
[ROW][C]97[/C][C]199841[/C][C]209194.892857143[/C][C]-9353.89285714287[/C][/ROW]
[ROW][C]98[/C][C]19349[/C][C]84994.2222222222[/C][C]-65645.2222222222[/C][/ROW]
[ROW][C]99[/C][C]247280[/C][C]159178.258064516[/C][C]88101.7419354839[/C][/ROW]
[ROW][C]100[/C][C]159408[/C][C]159178.258064516[/C][C]229.741935483878[/C][/ROW]
[ROW][C]101[/C][C]72128[/C][C]84994.2222222222[/C][C]-12866.2222222222[/C][/ROW]
[ROW][C]102[/C][C]104253[/C][C]159178.258064516[/C][C]-54925.2580645161[/C][/ROW]
[ROW][C]103[/C][C]151090[/C][C]159178.258064516[/C][C]-8088.25806451612[/C][/ROW]
[ROW][C]104[/C][C]137382[/C][C]159178.258064516[/C][C]-21796.2580645161[/C][/ROW]
[ROW][C]105[/C][C]87448[/C][C]111624.684210526[/C][C]-24176.6842105263[/C][/ROW]
[ROW][C]106[/C][C]27676[/C][C]17536.3684210526[/C][C]10139.6315789474[/C][/ROW]
[ROW][C]107[/C][C]165507[/C][C]159178.258064516[/C][C]6328.74193548388[/C][/ROW]
[ROW][C]108[/C][C]132148[/C][C]84994.2222222222[/C][C]47153.7777777778[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]17536.3684210526[/C][C]-17536.3684210526[/C][/ROW]
[ROW][C]110[/C][C]95778[/C][C]159178.258064516[/C][C]-63400.2580645161[/C][/ROW]
[ROW][C]111[/C][C]109001[/C][C]111624.684210526[/C][C]-2623.68421052632[/C][/ROW]
[ROW][C]112[/C][C]158833[/C][C]159178.258064516[/C][C]-345.258064516122[/C][/ROW]
[ROW][C]113[/C][C]147690[/C][C]159178.258064516[/C][C]-11488.2580645161[/C][/ROW]
[ROW][C]114[/C][C]89887[/C][C]111624.684210526[/C][C]-21737.6842105263[/C][/ROW]
[ROW][C]115[/C][C]3616[/C][C]17536.3684210526[/C][C]-13920.3684210526[/C][/ROW]
[ROW][C]116[/C][C]0[/C][C]17536.3684210526[/C][C]-17536.3684210526[/C][/ROW]
[ROW][C]117[/C][C]199005[/C][C]209194.892857143[/C][C]-10189.8928571429[/C][/ROW]
[ROW][C]118[/C][C]160930[/C][C]209194.892857143[/C][C]-48264.8928571429[/C][/ROW]
[ROW][C]119[/C][C]177948[/C][C]111624.684210526[/C][C]66323.3157894737[/C][/ROW]
[ROW][C]120[/C][C]136061[/C][C]159178.258064516[/C][C]-23117.2580645161[/C][/ROW]
[ROW][C]121[/C][C]43410[/C][C]17536.3684210526[/C][C]25873.6315789474[/C][/ROW]
[ROW][C]122[/C][C]184277[/C][C]209194.892857143[/C][C]-24917.8928571429[/C][/ROW]
[ROW][C]123[/C][C]108858[/C][C]111624.684210526[/C][C]-2766.68421052632[/C][/ROW]
[ROW][C]124[/C][C]141744[/C][C]159178.258064516[/C][C]-17434.2580645161[/C][/ROW]
[ROW][C]125[/C][C]60493[/C][C]17536.3684210526[/C][C]42956.6315789474[/C][/ROW]
[ROW][C]126[/C][C]19764[/C][C]17536.3684210526[/C][C]2227.63157894737[/C][/ROW]
[ROW][C]127[/C][C]177559[/C][C]159178.258064516[/C][C]18380.7419354839[/C][/ROW]
[ROW][C]128[/C][C]140281[/C][C]111624.684210526[/C][C]28656.3157894737[/C][/ROW]
[ROW][C]129[/C][C]164249[/C][C]159178.258064516[/C][C]5070.74193548388[/C][/ROW]
[ROW][C]130[/C][C]11796[/C][C]17536.3684210526[/C][C]-5740.36842105263[/C][/ROW]
[ROW][C]131[/C][C]10674[/C][C]17536.3684210526[/C][C]-6862.36842105263[/C][/ROW]
[ROW][C]132[/C][C]151322[/C][C]159178.258064516[/C][C]-7856.25806451612[/C][/ROW]
[ROW][C]133[/C][C]6836[/C][C]17536.3684210526[/C][C]-10700.3684210526[/C][/ROW]
[ROW][C]134[/C][C]174712[/C][C]159178.258064516[/C][C]15533.7419354839[/C][/ROW]
[ROW][C]135[/C][C]5118[/C][C]17536.3684210526[/C][C]-12418.3684210526[/C][/ROW]
[ROW][C]136[/C][C]40248[/C][C]17536.3684210526[/C][C]22711.6315789474[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]17536.3684210526[/C][C]-17536.3684210526[/C][/ROW]
[ROW][C]138[/C][C]127628[/C][C]159178.258064516[/C][C]-31550.2580645161[/C][/ROW]
[ROW][C]139[/C][C]88837[/C][C]111624.684210526[/C][C]-22787.6842105263[/C][/ROW]
[ROW][C]140[/C][C]7131[/C][C]17536.3684210526[/C][C]-10405.3684210526[/C][/ROW]
[ROW][C]141[/C][C]9056[/C][C]17536.3684210526[/C][C]-8480.36842105263[/C][/ROW]
[ROW][C]142[/C][C]87957[/C][C]84994.2222222222[/C][C]2962.77777777778[/C][/ROW]
[ROW][C]143[/C][C]144470[/C][C]159178.258064516[/C][C]-14708.2580645161[/C][/ROW]
[ROW][C]144[/C][C]111408[/C][C]111624.684210526[/C][C]-216.68421052632[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160536&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160536&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	162687	159178.258064516	3508.74193548388
2	201906	209194.892857143	-7288.89285714287
3	7215	17536.3684210526	-10321.3684210526
4	146367	159178.258064516	-12811.2580645161
5	257045	209194.892857143	47850.1071428571
6	524450	315780.857142857	208669.142857143
7	188294	209194.892857143	-20900.8928571429
8	195674	209194.892857143	-13520.8928571429
9	177020	159178.258064516	17841.7419354839
10	325899	315780.857142857	10118.1428571428
11	121844	159178.258064516	-37334.2580645161
12	203938	209194.892857143	-5256.89285714287
13	113213	159178.258064516	-45965.2580645161
14	220751	209194.892857143	11556.1071428571
15	172905	159178.258064516	13726.7419354839
16	156326	159178.258064516	-2852.25806451612
17	145178	209194.892857143	-64016.8928571429
18	89171	84994.2222222222	4176.77777777778
19	172624	159178.258064516	13445.7419354839
20	39790	84994.2222222222	-45204.2222222222
21	87927	111624.684210526	-23697.6842105263
22	241285	209194.892857143	32090.1071428571
23	195820	159178.258064516	36641.7419354839
24	146946	159178.258064516	-12232.2580645161
25	159763	159178.258064516	584.741935483878
26	207078	159178.258064516	47899.7419354839
27	212394	209194.892857143	3199.10714285713
28	201536	315780.857142857	-114244.857142857
29	394662	315780.857142857	78881.1428571428
30	217892	209194.892857143	8697.10714285713
31	182286	159178.258064516	23107.7419354839
32	181740	209194.892857143	-27454.8928571429
33	137978	159178.258064516	-21200.2580645161
34	255929	159178.258064516	96750.7419354839
35	236489	209194.892857143	27294.1071428571
36	0	17536.3684210526	-17536.3684210526
37	230761	159178.258064516	71582.7419354839
38	132807	159178.258064516	-26371.2580645161
39	157118	159178.258064516	-2060.25806451612
40	253254	315780.857142857	-62526.8571428572
41	269329	209194.892857143	60134.1071428571
42	161273	159178.258064516	2094.74193548388
43	107181	111624.684210526	-4443.68421052632
44	195891	209194.892857143	-13303.8928571429
45	139667	159178.258064516	-19511.2580645161
46	171101	159178.258064516	11922.7419354839
47	81407	111624.684210526	-30217.6842105263
48	247563	159178.258064516	88384.7419354839
49	239807	209194.892857143	30612.1071428571
50	172743	159178.258064516	13564.7419354839
51	48188	17536.3684210526	30651.6315789474
52	169355	159178.258064516	10176.7419354839
53	315622	315780.857142857	-158.857142857159
54	241518	159178.258064516	82339.7419354839
55	195583	209194.892857143	-13611.8928571429
56	159913	159178.258064516	734.741935483878
57	220241	159178.258064516	61062.7419354839
58	101694	111624.684210526	-9930.68421052632
59	157258	209194.892857143	-51936.8928571429
60	202536	111624.684210526	90911.3157894737
61	173505	159178.258064516	14326.7419354839
62	150518	159178.258064516	-8660.25806451612
63	141491	159178.258064516	-17687.2580645161
64	125612	159178.258064516	-33566.2580645161
65	166049	111624.684210526	54424.3157894737
66	124197	159178.258064516	-34981.2580645161
67	195043	315780.857142857	-120737.857142857
68	138708	159178.258064516	-20470.2580645161
69	116552	159178.258064516	-42626.2580645161
70	31970	17536.3684210526	14433.6315789474
71	258158	209194.892857143	48963.1071428571
72	151184	159178.258064516	-7994.25806451612
73	135926	159178.258064516	-23252.2580645161
74	119629	84994.2222222222	34634.7777777778
75	171518	159178.258064516	12339.7419354839
76	108949	84994.2222222222	23954.7777777778
77	183471	159178.258064516	24292.7419354839
78	159966	209194.892857143	-49228.8928571429
79	93786	111624.684210526	-17838.6842105263
80	84971	111624.684210526	-26653.6842105263
81	88882	159178.258064516	-70296.2580645161
82	304603	209194.892857143	95408.1071428571
83	75101	111624.684210526	-36523.6842105263
84	145043	159178.258064516	-14135.2580645161
85	95827	84994.2222222222	10832.7777777778
86	173924	159178.258064516	14745.7419354839
87	241957	209194.892857143	32762.1071428571
88	115367	159178.258064516	-43811.2580645161
89	118408	159178.258064516	-40770.2580645161
90	164078	159178.258064516	4899.74193548388
91	158931	209194.892857143	-50263.8928571429
92	184139	209194.892857143	-25055.8928571429
93	152856	159178.258064516	-6322.25806451612
94	144014	111624.684210526	32389.3157894737
95	62535	111624.684210526	-49089.6842105263
96	245196	209194.892857143	36001.1071428571
97	199841	209194.892857143	-9353.89285714287
98	19349	84994.2222222222	-65645.2222222222
99	247280	159178.258064516	88101.7419354839
100	159408	159178.258064516	229.741935483878
101	72128	84994.2222222222	-12866.2222222222
102	104253	159178.258064516	-54925.2580645161
103	151090	159178.258064516	-8088.25806451612
104	137382	159178.258064516	-21796.2580645161
105	87448	111624.684210526	-24176.6842105263
106	27676	17536.3684210526	10139.6315789474
107	165507	159178.258064516	6328.74193548388
108	132148	84994.2222222222	47153.7777777778
109	0	17536.3684210526	-17536.3684210526
110	95778	159178.258064516	-63400.2580645161
111	109001	111624.684210526	-2623.68421052632
112	158833	159178.258064516	-345.258064516122
113	147690	159178.258064516	-11488.2580645161
114	89887	111624.684210526	-21737.6842105263
115	3616	17536.3684210526	-13920.3684210526
116	0	17536.3684210526	-17536.3684210526
117	199005	209194.892857143	-10189.8928571429
118	160930	209194.892857143	-48264.8928571429
119	177948	111624.684210526	66323.3157894737
120	136061	159178.258064516	-23117.2580645161
121	43410	17536.3684210526	25873.6315789474
122	184277	209194.892857143	-24917.8928571429
123	108858	111624.684210526	-2766.68421052632
124	141744	159178.258064516	-17434.2580645161
125	60493	17536.3684210526	42956.6315789474
126	19764	17536.3684210526	2227.63157894737
127	177559	159178.258064516	18380.7419354839
128	140281	111624.684210526	28656.3157894737
129	164249	159178.258064516	5070.74193548388
130	11796	17536.3684210526	-5740.36842105263
131	10674	17536.3684210526	-6862.36842105263
132	151322	159178.258064516	-7856.25806451612
133	6836	17536.3684210526	-10700.3684210526
134	174712	159178.258064516	15533.7419354839
135	5118	17536.3684210526	-12418.3684210526
136	40248	17536.3684210526	22711.6315789474
137	0	17536.3684210526	-17536.3684210526
138	127628	159178.258064516	-31550.2580645161
139	88837	111624.684210526	-22787.6842105263
140	7131	17536.3684210526	-10405.3684210526
141	9056	17536.3684210526	-8480.36842105263
142	87957	84994.2222222222	2962.77777777778
143	144470	159178.258064516	-14708.2580645161
144	111408	111624.684210526	-216.68421052632

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 = 1 ; par2 = none ; par4 = no ;

Parameters (R input):

par1 = 1 ; 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