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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

Tue, 14 Dec 2010 20:32:49 +0000

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/2010/Dec/14/t1292358710uwaub0og89hi8sd.htm/, Retrieved Thu, 02 May 2024 23:13:31 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110159, Retrieved Thu, 02 May 2024 23:13:31 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

150

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]
-   PD    [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2010-12-14 20:32:49] [278a0539dc236556c5f30b5bc56ff9eb] [Current]
-   P       [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2010-12-14 20:53:54] [b8e188bcc949964bed729335b3416734] 
-   P         [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2010-12-14 21:32:40] [b8e188bcc949964bed729335b3416734] 
- R P           [Recursive Partitioning (Regression Trees)] [ws 10] [2011-12-12 16:13:29] [27e29806e0b1d1351a97bc4ee4116294] 
- RM            [Recursive Partitioning (Regression Trees)] [] [2011-12-13 11:47:35] [74be16979710d4c4e7c6647856088456] 
-   P         [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2010-12-14 21:39:51] [b8e188bcc949964bed729335b3416734] 
- R P           [Recursive Partitioning (Regression Trees)] [ws 10] [2011-12-12 16:14:36] [27e29806e0b1d1351a97bc4ee4116294] 
- RM            [Recursive Partitioning (Regression Trees)] [] [2011-12-13 11:49:19] [74be16979710d4c4e7c6647856088456] 
-   P         [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2010-12-14 21:50:13] [b8e188bcc949964bed729335b3416734] 
- R P           [Recursive Partitioning (Regression Trees)] [ws 10] [2011-12-12 16:15:34] [27e29806e0b1d1351a97bc4ee4116294] 
- RM            [Recursive Partitioning (Regression Trees)] [] [2011-12-13 11:50:58] [74be16979710d4c4e7c6647856088456] 
-   P         [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2010-12-14 21:58:14] [b8e188bcc949964bed729335b3416734] 
- R P           [Recursive Partitioning (Regression Trees)] [ws 10] [2011-12-12 16:16:33] [27e29806e0b1d1351a97bc4ee4116294] 
- RMP           [Recursive Partitioning (Regression Trees)] [] [2011-12-13 11:52:13] [74be16979710d4c4e7c6647856088456] 
- R P         [Recursive Partitioning (Regression Trees)] [ws 10] [2011-12-12 16:12:19] [27e29806e0b1d1351a97bc4ee4116294] 
- R           [Recursive Partitioning (Regression Trees)] [] [2011-12-13 11:45:16] [74be16979710d4c4e7c6647856088456] 
-    D      [Recursive Partitioning (Regression Trees)] [recursive partiti...] [2011-12-12 15:52:23] [d95291bc5e09a8bed20558da95617a33] 
- R         [Recursive Partitioning (Regression Trees)] [ws 10] [2011-12-12 16:10:42] [27e29806e0b1d1351a97bc4ee4116294] 
- RM        [Recursive Partitioning (Regression Trees)] [] [2011-12-13 08:43:31] [74be16979710d4c4e7c6647856088456] 

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Dataseries X:

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Histogram

Boxplots

2	1	22	15	16	17	10
1	2	22	23	24	42	9
1	2	22	26	22	39	30
1	2	23	19	21	22	18
1	2	21	19	23	20	16
1	2	21	16	23	31	20
1	1	24	23	21	42	20
2	1	22	22	20	30	18
1	2	21	19	22	33	21
1	2	23	24	20	29	20
1	1	20	19	12	31	20
2	1	23	25	23	39	20
1	1	20	23	23	44	29
1	2	21	31	30	40	14
2	1	22	29	22	42	25
2	2	22	18	21	28	19
2	2	21	17	21	29	19
1	1	20	22	15	35	25
1	1	21	21	22	26	25
1	2	21	24	24	42	19
1	1	20	22	23	26	19
1	1	21	16	15	30	18
1	2	23	22	24	28	24
1	1	23	21	24	24	18
2	1	21	25	21	26	26
1	1	22	22	21	39	26
2	1	20	24	18	33	24
2	1	23	21	20	50	29
2	1	21	25	19	40	26
1	1	21	29	29	49	28
2	1	23	19	20	31	18
2	1	23	29	23	37	19
2	2	22	25	24	29	21
1	1	21	19	27	37	13
1	1	NA	27	28	16	19
1	2	21	25	24	28	26
1	2	21	23	29	29	17
1	1	22	24	24	31	19
2	2	22	23	22	34	28
1	2	22	25	25	30	15
1	1	22	26	24	31	16
1	1	23	23	14	44	18
2	1	NA	22	22	35	25
1	2	22	32	24	47	15
1	2	21	22	24	39	24
1	1	23	18	24	34	24
2	1	21	19	24	15	14
2	2	32	23	22	26	19
2	2	32	24	22	25	20
2	1	21	19	21	30	27
1	1	20	16	21	25	20
1	1	21	23	21	33	25
1	1	22	17	15	39	16
1	1	21	17	26	24	19
1	2	21	28	22	44	15
1	2	21	24	24	31	17
1	1	22	21	13	30	22
1	1	21	14	19	21	19
2	1	25	21	10	38	44
1	2	22	20	28	30	19
1	1	21	25	25	31	19
2	2	21	20	24	32	23
1	1	20	17	22	34	19
1	2	21	26	30	43	28
1	2	22	17	22	29	17
4	2	21	17	24	40	22
1	2	23	24	23	31	25
1	2	24	30	20	36	44
2	1	20	25	22	39	19
2	1	21	15	22	31	21
1	1	23	25	19	36	25
1	1	24	18	24	36	28
1	1	22	20	22	36	19
1	1	22	32	26	41	33
2	2	21	14	12	23	19
2	1	20	20	25	23	12
1	2	21	25	29	34	15
1	NA	21	25	23	31	23
1	1	22	25	23	26	21
1	1	21	35	17	32	29
1	2	21	29	26	48	15
1	1	22	25	27	37	23
1	2	23	21	23	31	25
1	1	23	21	20	29	18
1	1	21	24	24	44	24
1	1	22	26	22	27	20
1	1	24	24	26	31	19
1	2	21	20	29	37	21
1	1	25	24	20	31	33
2	1	24	18	17	29	17
1	1	21	17	16	25	19
1	2	21	22	24	39	19
1	1	22	22	24	33	23
1	1	22	22	19	26	21
2	1	21	24	29	39	20
1	1	24	32	25	33	19
1	2	21	19	25	22	16
1	2	21	21	24	27	20
1	2	22	23	29	31	18
2	1	22	26	22	40	11
1	2	21	18	23	45	18
2	1	21	19	15	33	23
1	1	22	22	29	26	19
1	2	21	27	21	28	21
2	1	21	21	23	28	16
2	1	22	20	20	30	24
2	2	21	21	25	47	23
1	1	21	20	28	30	20
1	1	21	29	18	37	23
1	1	23	30	25	23	25
1	1	22	23	24	24	24
2	1	21	29	23	15	19
1	2	22	19	25	39	15
1	1	22	26	27	32	20
1	1	22	22	24	23	14
2	1	23	26	24	41	34
2	1	24	27	26	39	24
2	1	22	19	18	42	26
2	2	21	24	26	38	23
1	2	21	26	23	30	18
2	2	22	22	28	19	11
1	1	20	23	20	45	28
1	1	23	25	23	36	15
1	2	21	19	24	36	26
1	1	22	20	21	33	20
2	1	23	25	25	35	21
2	1	21	14	16	29	21
1	2	21	20	19	28	15
1	1	23	27	22	40	30
1	2	21	21	27	28	21
1	2	21	21	24	36	12
1	2	21	14	17	28	23
2	1	23	21	21	42	30
1	1	21	23	21	27	22
2	1	22	18	19	32	21
1	2	22	20	25	27	19
1	2	21	19	24	30	22
1	2	21	15	21	31	18
1	2	24	23	26	26	16
1	1	21	26	25	47	19
1	1	21	21	25	28	20
1	2	20	13	13	31	12
2	2	21	24	25	26	21
1	2	NA	17	23	27	14
1	1	24	21	26	28	23
1	1	22	28	22	44	30
1	1	22	22	20	32	21
1	1	22	25	14	25	25
1	1	22	18	23	24	13
1	1	23	27	24	45	17
1	1	22	25	21	37	24
2	1	22	21	24	25	21

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	7 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 7 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110159&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110159&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110159&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	7 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Goodness of Fit
Correlation	0.4502
R-squared	0.2027
RMSE	3.6947

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.4502 \tabularnewline
R-squared & 0.2027 \tabularnewline
RMSE & 3.6947 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110159&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.4502[/C][/ROW]
[ROW][C]R-squared[/C][C]0.2027[/C][/ROW]
[ROW][C]RMSE[/C][C]3.6947[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110159&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110159&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	0.4502
R-squared	0.2027
RMSE	3.6947

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	15	17.2857142857143	-2.28571428571428
2	23	23.7777777777778	-0.777777777777779
3	26	23.7777777777778	2.22222222222222
4	19	21.7727272727273	-2.77272727272727
5	19	21.7727272727273	-2.77272727272727
6	16	21.7727272727273	-5.77272727272727
7	23	23.7777777777778	-0.777777777777779
8	22	21.7727272727273	0.227272727272727
9	19	23.7777777777778	-4.77777777777778
10	24	21.7727272727273	2.22727272727273
11	19	17.2857142857143	1.71428571428572
12	25	23.7777777777778	1.22222222222222
13	23	23.7777777777778	-0.777777777777779
14	31	23.7777777777778	7.22222222222222
15	29	23.7777777777778	5.22222222222222
16	18	21.7727272727273	-3.77272727272727
17	17	21.7727272727273	-4.77272727272727
18	22	23.7777777777778	-1.77777777777778
19	21	21.7727272727273	-0.772727272727273
20	24	23.7777777777778	0.222222222222221
21	22	21.7727272727273	0.227272727272727
22	16	17.2857142857143	-1.28571428571428
23	22	21.7727272727273	0.227272727272727
24	21	21.7727272727273	-0.772727272727273
25	25	21.7727272727273	3.22727272727273
26	22	23.7777777777778	-1.77777777777778
27	24	23.7777777777778	0.222222222222221
28	21	23.7777777777778	-2.77777777777778
29	25	23.7777777777778	1.22222222222222
30	29	23.7777777777778	5.22222222222222
31	19	21.7727272727273	-2.77272727272727
32	29	23.7777777777778	5.22222222222222
33	25	21.7727272727273	3.22727272727273
34	19	23.7777777777778	-4.77777777777778
35	27	21.7727272727273	5.22727272727273
36	25	21.7727272727273	3.22727272727273
37	23	21.7727272727273	1.22727272727273
38	24	21.7727272727273	2.22727272727273
39	23	23.7777777777778	-0.777777777777779
40	25	21.7727272727273	3.22727272727273
41	26	21.7727272727273	4.22727272727273
42	23	23.7777777777778	-0.777777777777779
43	22	23.7777777777778	-1.77777777777778
44	32	23.7777777777778	8.22222222222222
45	22	23.7777777777778	-1.77777777777778
46	18	23.7777777777778	-5.77777777777778
47	19	21.7727272727273	-2.77272727272727
48	23	21.7727272727273	1.22727272727273
49	24	21.7727272727273	2.22727272727273
50	19	21.7727272727273	-2.77272727272727
51	16	21.7727272727273	-5.77272727272727
52	23	23.7777777777778	-0.777777777777779
53	17	23.7777777777778	-6.77777777777778
54	17	21.7727272727273	-4.77272727272727
55	28	23.7777777777778	4.22222222222222
56	24	21.7727272727273	2.22727272727273
57	21	17.2857142857143	3.71428571428572
58	14	17.2857142857143	-3.28571428571428
59	21	23.7777777777778	-2.77777777777778
60	20	21.7727272727273	-1.77272727272727
61	25	21.7727272727273	3.22727272727273
62	20	23.7777777777778	-3.77777777777778
63	17	23.7777777777778	-6.77777777777778
64	26	23.7777777777778	2.22222222222222
65	17	21.7727272727273	-4.77272727272727
66	17	23.7777777777778	-6.77777777777778
67	24	21.7727272727273	2.22727272727273
68	30	23.7777777777778	6.22222222222222
69	25	23.7777777777778	1.22222222222222
70	15	21.7727272727273	-6.77272727272727
71	25	23.7777777777778	1.22222222222222
72	18	23.7777777777778	-5.77777777777778
73	20	23.7777777777778	-3.77777777777778
74	32	23.7777777777778	8.22222222222222
75	14	17.2857142857143	-3.28571428571428
76	20	21.7727272727273	-1.77272727272727
77	25	23.7777777777778	1.22222222222222
78	25	21.7727272727273	3.22727272727273
79	25	21.7727272727273	3.22727272727273
80	35	23.7777777777778	11.2222222222222
81	29	23.7777777777778	5.22222222222222
82	25	23.7777777777778	1.22222222222222
83	21	21.7727272727273	-0.772727272727273
84	21	21.7727272727273	-0.772727272727273
85	24	23.7777777777778	0.222222222222221
86	26	21.7727272727273	4.22727272727273
87	24	21.7727272727273	2.22727272727273
88	20	23.7777777777778	-3.77777777777778
89	24	21.7727272727273	2.22727272727273
90	18	17.2857142857143	0.714285714285715
91	17	17.2857142857143	-0.285714285714285
92	22	23.7777777777778	-1.77777777777778
93	22	23.7777777777778	-1.77777777777778
94	22	17.2857142857143	4.71428571428572
95	24	23.7777777777778	0.222222222222221
96	32	23.7777777777778	8.22222222222222
97	19	21.7727272727273	-2.77272727272727
98	21	21.7727272727273	-0.772727272727273
99	23	21.7727272727273	1.22727272727273
100	26	23.7777777777778	2.22222222222222
101	18	23.7777777777778	-5.77777777777778
102	19	23.7777777777778	-4.77777777777778
103	22	21.7727272727273	0.227272727272727
104	27	21.7727272727273	5.22727272727273
105	21	21.7727272727273	-0.772727272727273
106	20	21.7727272727273	-1.77272727272727
107	21	23.7777777777778	-2.77777777777778
108	20	21.7727272727273	-1.77272727272727
109	29	23.7777777777778	5.22222222222222
110	30	21.7727272727273	8.22727272727273
111	23	21.7727272727273	1.22727272727273
112	29	21.7727272727273	7.22727272727273
113	19	23.7777777777778	-4.77777777777778
114	26	23.7777777777778	2.22222222222222
115	22	21.7727272727273	0.227272727272727
116	26	23.7777777777778	2.22222222222222
117	27	23.7777777777778	3.22222222222222
118	19	23.7777777777778	-4.77777777777778
119	24	23.7777777777778	0.222222222222221
120	26	21.7727272727273	4.22727272727273
121	22	21.7727272727273	0.227272727272727
122	23	23.7777777777778	-0.777777777777779
123	25	23.7777777777778	1.22222222222222
124	19	23.7777777777778	-4.77777777777778
125	20	23.7777777777778	-3.77777777777778
126	25	23.7777777777778	1.22222222222222
127	14	17.2857142857143	-3.28571428571428
128	20	17.2857142857143	2.71428571428572
129	27	23.7777777777778	3.22222222222222
130	21	21.7727272727273	-0.772727272727273
131	21	23.7777777777778	-2.77777777777778
132	14	17.2857142857143	-3.28571428571428
133	21	23.7777777777778	-2.77777777777778
134	23	21.7727272727273	1.22727272727273
135	18	23.7777777777778	-5.77777777777778
136	20	21.7727272727273	-1.77272727272727
137	19	21.7727272727273	-2.77272727272727
138	15	21.7727272727273	-6.77272727272727
139	23	21.7727272727273	1.22727272727273
140	26	23.7777777777778	2.22222222222222
141	21	21.7727272727273	-0.772727272727273
142	13	17.2857142857143	-4.28571428571428
143	24	21.7727272727273	2.22727272727273
144	17	21.7727272727273	-4.77272727272727
145	21	21.7727272727273	-0.772727272727273
146	28	23.7777777777778	4.22222222222222
147	22	23.7777777777778	-1.77777777777778
148	25	17.2857142857143	7.71428571428572
149	18	21.7727272727273	-3.77272727272727
150	27	23.7777777777778	3.22222222222222
151	25	23.7777777777778	1.22222222222222
152	21	21.7727272727273	-0.772727272727273

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 15 & 17.2857142857143 & -2.28571428571428 \tabularnewline
2 & 23 & 23.7777777777778 & -0.777777777777779 \tabularnewline
3 & 26 & 23.7777777777778 & 2.22222222222222 \tabularnewline
4 & 19 & 21.7727272727273 & -2.77272727272727 \tabularnewline
5 & 19 & 21.7727272727273 & -2.77272727272727 \tabularnewline
6 & 16 & 21.7727272727273 & -5.77272727272727 \tabularnewline
7 & 23 & 23.7777777777778 & -0.777777777777779 \tabularnewline
8 & 22 & 21.7727272727273 & 0.227272727272727 \tabularnewline
9 & 19 & 23.7777777777778 & -4.77777777777778 \tabularnewline
10 & 24 & 21.7727272727273 & 2.22727272727273 \tabularnewline
11 & 19 & 17.2857142857143 & 1.71428571428572 \tabularnewline
12 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
13 & 23 & 23.7777777777778 & -0.777777777777779 \tabularnewline
14 & 31 & 23.7777777777778 & 7.22222222222222 \tabularnewline
15 & 29 & 23.7777777777778 & 5.22222222222222 \tabularnewline
16 & 18 & 21.7727272727273 & -3.77272727272727 \tabularnewline
17 & 17 & 21.7727272727273 & -4.77272727272727 \tabularnewline
18 & 22 & 23.7777777777778 & -1.77777777777778 \tabularnewline
19 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
20 & 24 & 23.7777777777778 & 0.222222222222221 \tabularnewline
21 & 22 & 21.7727272727273 & 0.227272727272727 \tabularnewline
22 & 16 & 17.2857142857143 & -1.28571428571428 \tabularnewline
23 & 22 & 21.7727272727273 & 0.227272727272727 \tabularnewline
24 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
25 & 25 & 21.7727272727273 & 3.22727272727273 \tabularnewline
26 & 22 & 23.7777777777778 & -1.77777777777778 \tabularnewline
27 & 24 & 23.7777777777778 & 0.222222222222221 \tabularnewline
28 & 21 & 23.7777777777778 & -2.77777777777778 \tabularnewline
29 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
30 & 29 & 23.7777777777778 & 5.22222222222222 \tabularnewline
31 & 19 & 21.7727272727273 & -2.77272727272727 \tabularnewline
32 & 29 & 23.7777777777778 & 5.22222222222222 \tabularnewline
33 & 25 & 21.7727272727273 & 3.22727272727273 \tabularnewline
34 & 19 & 23.7777777777778 & -4.77777777777778 \tabularnewline
35 & 27 & 21.7727272727273 & 5.22727272727273 \tabularnewline
36 & 25 & 21.7727272727273 & 3.22727272727273 \tabularnewline
37 & 23 & 21.7727272727273 & 1.22727272727273 \tabularnewline
38 & 24 & 21.7727272727273 & 2.22727272727273 \tabularnewline
39 & 23 & 23.7777777777778 & -0.777777777777779 \tabularnewline
40 & 25 & 21.7727272727273 & 3.22727272727273 \tabularnewline
41 & 26 & 21.7727272727273 & 4.22727272727273 \tabularnewline
42 & 23 & 23.7777777777778 & -0.777777777777779 \tabularnewline
43 & 22 & 23.7777777777778 & -1.77777777777778 \tabularnewline
44 & 32 & 23.7777777777778 & 8.22222222222222 \tabularnewline
45 & 22 & 23.7777777777778 & -1.77777777777778 \tabularnewline
46 & 18 & 23.7777777777778 & -5.77777777777778 \tabularnewline
47 & 19 & 21.7727272727273 & -2.77272727272727 \tabularnewline
48 & 23 & 21.7727272727273 & 1.22727272727273 \tabularnewline
49 & 24 & 21.7727272727273 & 2.22727272727273 \tabularnewline
50 & 19 & 21.7727272727273 & -2.77272727272727 \tabularnewline
51 & 16 & 21.7727272727273 & -5.77272727272727 \tabularnewline
52 & 23 & 23.7777777777778 & -0.777777777777779 \tabularnewline
53 & 17 & 23.7777777777778 & -6.77777777777778 \tabularnewline
54 & 17 & 21.7727272727273 & -4.77272727272727 \tabularnewline
55 & 28 & 23.7777777777778 & 4.22222222222222 \tabularnewline
56 & 24 & 21.7727272727273 & 2.22727272727273 \tabularnewline
57 & 21 & 17.2857142857143 & 3.71428571428572 \tabularnewline
58 & 14 & 17.2857142857143 & -3.28571428571428 \tabularnewline
59 & 21 & 23.7777777777778 & -2.77777777777778 \tabularnewline
60 & 20 & 21.7727272727273 & -1.77272727272727 \tabularnewline
61 & 25 & 21.7727272727273 & 3.22727272727273 \tabularnewline
62 & 20 & 23.7777777777778 & -3.77777777777778 \tabularnewline
63 & 17 & 23.7777777777778 & -6.77777777777778 \tabularnewline
64 & 26 & 23.7777777777778 & 2.22222222222222 \tabularnewline
65 & 17 & 21.7727272727273 & -4.77272727272727 \tabularnewline
66 & 17 & 23.7777777777778 & -6.77777777777778 \tabularnewline
67 & 24 & 21.7727272727273 & 2.22727272727273 \tabularnewline
68 & 30 & 23.7777777777778 & 6.22222222222222 \tabularnewline
69 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
70 & 15 & 21.7727272727273 & -6.77272727272727 \tabularnewline
71 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
72 & 18 & 23.7777777777778 & -5.77777777777778 \tabularnewline
73 & 20 & 23.7777777777778 & -3.77777777777778 \tabularnewline
74 & 32 & 23.7777777777778 & 8.22222222222222 \tabularnewline
75 & 14 & 17.2857142857143 & -3.28571428571428 \tabularnewline
76 & 20 & 21.7727272727273 & -1.77272727272727 \tabularnewline
77 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
78 & 25 & 21.7727272727273 & 3.22727272727273 \tabularnewline
79 & 25 & 21.7727272727273 & 3.22727272727273 \tabularnewline
80 & 35 & 23.7777777777778 & 11.2222222222222 \tabularnewline
81 & 29 & 23.7777777777778 & 5.22222222222222 \tabularnewline
82 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
83 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
84 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
85 & 24 & 23.7777777777778 & 0.222222222222221 \tabularnewline
86 & 26 & 21.7727272727273 & 4.22727272727273 \tabularnewline
87 & 24 & 21.7727272727273 & 2.22727272727273 \tabularnewline
88 & 20 & 23.7777777777778 & -3.77777777777778 \tabularnewline
89 & 24 & 21.7727272727273 & 2.22727272727273 \tabularnewline
90 & 18 & 17.2857142857143 & 0.714285714285715 \tabularnewline
91 & 17 & 17.2857142857143 & -0.285714285714285 \tabularnewline
92 & 22 & 23.7777777777778 & -1.77777777777778 \tabularnewline
93 & 22 & 23.7777777777778 & -1.77777777777778 \tabularnewline
94 & 22 & 17.2857142857143 & 4.71428571428572 \tabularnewline
95 & 24 & 23.7777777777778 & 0.222222222222221 \tabularnewline
96 & 32 & 23.7777777777778 & 8.22222222222222 \tabularnewline
97 & 19 & 21.7727272727273 & -2.77272727272727 \tabularnewline
98 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
99 & 23 & 21.7727272727273 & 1.22727272727273 \tabularnewline
100 & 26 & 23.7777777777778 & 2.22222222222222 \tabularnewline
101 & 18 & 23.7777777777778 & -5.77777777777778 \tabularnewline
102 & 19 & 23.7777777777778 & -4.77777777777778 \tabularnewline
103 & 22 & 21.7727272727273 & 0.227272727272727 \tabularnewline
104 & 27 & 21.7727272727273 & 5.22727272727273 \tabularnewline
105 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
106 & 20 & 21.7727272727273 & -1.77272727272727 \tabularnewline
107 & 21 & 23.7777777777778 & -2.77777777777778 \tabularnewline
108 & 20 & 21.7727272727273 & -1.77272727272727 \tabularnewline
109 & 29 & 23.7777777777778 & 5.22222222222222 \tabularnewline
110 & 30 & 21.7727272727273 & 8.22727272727273 \tabularnewline
111 & 23 & 21.7727272727273 & 1.22727272727273 \tabularnewline
112 & 29 & 21.7727272727273 & 7.22727272727273 \tabularnewline
113 & 19 & 23.7777777777778 & -4.77777777777778 \tabularnewline
114 & 26 & 23.7777777777778 & 2.22222222222222 \tabularnewline
115 & 22 & 21.7727272727273 & 0.227272727272727 \tabularnewline
116 & 26 & 23.7777777777778 & 2.22222222222222 \tabularnewline
117 & 27 & 23.7777777777778 & 3.22222222222222 \tabularnewline
118 & 19 & 23.7777777777778 & -4.77777777777778 \tabularnewline
119 & 24 & 23.7777777777778 & 0.222222222222221 \tabularnewline
120 & 26 & 21.7727272727273 & 4.22727272727273 \tabularnewline
121 & 22 & 21.7727272727273 & 0.227272727272727 \tabularnewline
122 & 23 & 23.7777777777778 & -0.777777777777779 \tabularnewline
123 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
124 & 19 & 23.7777777777778 & -4.77777777777778 \tabularnewline
125 & 20 & 23.7777777777778 & -3.77777777777778 \tabularnewline
126 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
127 & 14 & 17.2857142857143 & -3.28571428571428 \tabularnewline
128 & 20 & 17.2857142857143 & 2.71428571428572 \tabularnewline
129 & 27 & 23.7777777777778 & 3.22222222222222 \tabularnewline
130 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
131 & 21 & 23.7777777777778 & -2.77777777777778 \tabularnewline
132 & 14 & 17.2857142857143 & -3.28571428571428 \tabularnewline
133 & 21 & 23.7777777777778 & -2.77777777777778 \tabularnewline
134 & 23 & 21.7727272727273 & 1.22727272727273 \tabularnewline
135 & 18 & 23.7777777777778 & -5.77777777777778 \tabularnewline
136 & 20 & 21.7727272727273 & -1.77272727272727 \tabularnewline
137 & 19 & 21.7727272727273 & -2.77272727272727 \tabularnewline
138 & 15 & 21.7727272727273 & -6.77272727272727 \tabularnewline
139 & 23 & 21.7727272727273 & 1.22727272727273 \tabularnewline
140 & 26 & 23.7777777777778 & 2.22222222222222 \tabularnewline
141 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
142 & 13 & 17.2857142857143 & -4.28571428571428 \tabularnewline
143 & 24 & 21.7727272727273 & 2.22727272727273 \tabularnewline
144 & 17 & 21.7727272727273 & -4.77272727272727 \tabularnewline
145 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
146 & 28 & 23.7777777777778 & 4.22222222222222 \tabularnewline
147 & 22 & 23.7777777777778 & -1.77777777777778 \tabularnewline
148 & 25 & 17.2857142857143 & 7.71428571428572 \tabularnewline
149 & 18 & 21.7727272727273 & -3.77272727272727 \tabularnewline
150 & 27 & 23.7777777777778 & 3.22222222222222 \tabularnewline
151 & 25 & 23.7777777777778 & 1.22222222222222 \tabularnewline
152 & 21 & 21.7727272727273 & -0.772727272727273 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110159&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]15[/C][C]17.2857142857143[/C][C]-2.28571428571428[/C][/ROW]
[ROW][C]2[/C][C]23[/C][C]23.7777777777778[/C][C]-0.777777777777779[/C][/ROW]
[ROW][C]3[/C][C]26[/C][C]23.7777777777778[/C][C]2.22222222222222[/C][/ROW]
[ROW][C]4[/C][C]19[/C][C]21.7727272727273[/C][C]-2.77272727272727[/C][/ROW]
[ROW][C]5[/C][C]19[/C][C]21.7727272727273[/C][C]-2.77272727272727[/C][/ROW]
[ROW][C]6[/C][C]16[/C][C]21.7727272727273[/C][C]-5.77272727272727[/C][/ROW]
[ROW][C]7[/C][C]23[/C][C]23.7777777777778[/C][C]-0.777777777777779[/C][/ROW]
[ROW][C]8[/C][C]22[/C][C]21.7727272727273[/C][C]0.227272727272727[/C][/ROW]
[ROW][C]9[/C][C]19[/C][C]23.7777777777778[/C][C]-4.77777777777778[/C][/ROW]
[ROW][C]10[/C][C]24[/C][C]21.7727272727273[/C][C]2.22727272727273[/C][/ROW]
[ROW][C]11[/C][C]19[/C][C]17.2857142857143[/C][C]1.71428571428572[/C][/ROW]
[ROW][C]12[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]13[/C][C]23[/C][C]23.7777777777778[/C][C]-0.777777777777779[/C][/ROW]
[ROW][C]14[/C][C]31[/C][C]23.7777777777778[/C][C]7.22222222222222[/C][/ROW]
[ROW][C]15[/C][C]29[/C][C]23.7777777777778[/C][C]5.22222222222222[/C][/ROW]
[ROW][C]16[/C][C]18[/C][C]21.7727272727273[/C][C]-3.77272727272727[/C][/ROW]
[ROW][C]17[/C][C]17[/C][C]21.7727272727273[/C][C]-4.77272727272727[/C][/ROW]
[ROW][C]18[/C][C]22[/C][C]23.7777777777778[/C][C]-1.77777777777778[/C][/ROW]
[ROW][C]19[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]20[/C][C]24[/C][C]23.7777777777778[/C][C]0.222222222222221[/C][/ROW]
[ROW][C]21[/C][C]22[/C][C]21.7727272727273[/C][C]0.227272727272727[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]17.2857142857143[/C][C]-1.28571428571428[/C][/ROW]
[ROW][C]23[/C][C]22[/C][C]21.7727272727273[/C][C]0.227272727272727[/C][/ROW]
[ROW][C]24[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]25[/C][C]25[/C][C]21.7727272727273[/C][C]3.22727272727273[/C][/ROW]
[ROW][C]26[/C][C]22[/C][C]23.7777777777778[/C][C]-1.77777777777778[/C][/ROW]
[ROW][C]27[/C][C]24[/C][C]23.7777777777778[/C][C]0.222222222222221[/C][/ROW]
[ROW][C]28[/C][C]21[/C][C]23.7777777777778[/C][C]-2.77777777777778[/C][/ROW]
[ROW][C]29[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]30[/C][C]29[/C][C]23.7777777777778[/C][C]5.22222222222222[/C][/ROW]
[ROW][C]31[/C][C]19[/C][C]21.7727272727273[/C][C]-2.77272727272727[/C][/ROW]
[ROW][C]32[/C][C]29[/C][C]23.7777777777778[/C][C]5.22222222222222[/C][/ROW]
[ROW][C]33[/C][C]25[/C][C]21.7727272727273[/C][C]3.22727272727273[/C][/ROW]
[ROW][C]34[/C][C]19[/C][C]23.7777777777778[/C][C]-4.77777777777778[/C][/ROW]
[ROW][C]35[/C][C]27[/C][C]21.7727272727273[/C][C]5.22727272727273[/C][/ROW]
[ROW][C]36[/C][C]25[/C][C]21.7727272727273[/C][C]3.22727272727273[/C][/ROW]
[ROW][C]37[/C][C]23[/C][C]21.7727272727273[/C][C]1.22727272727273[/C][/ROW]
[ROW][C]38[/C][C]24[/C][C]21.7727272727273[/C][C]2.22727272727273[/C][/ROW]
[ROW][C]39[/C][C]23[/C][C]23.7777777777778[/C][C]-0.777777777777779[/C][/ROW]
[ROW][C]40[/C][C]25[/C][C]21.7727272727273[/C][C]3.22727272727273[/C][/ROW]
[ROW][C]41[/C][C]26[/C][C]21.7727272727273[/C][C]4.22727272727273[/C][/ROW]
[ROW][C]42[/C][C]23[/C][C]23.7777777777778[/C][C]-0.777777777777779[/C][/ROW]
[ROW][C]43[/C][C]22[/C][C]23.7777777777778[/C][C]-1.77777777777778[/C][/ROW]
[ROW][C]44[/C][C]32[/C][C]23.7777777777778[/C][C]8.22222222222222[/C][/ROW]
[ROW][C]45[/C][C]22[/C][C]23.7777777777778[/C][C]-1.77777777777778[/C][/ROW]
[ROW][C]46[/C][C]18[/C][C]23.7777777777778[/C][C]-5.77777777777778[/C][/ROW]
[ROW][C]47[/C][C]19[/C][C]21.7727272727273[/C][C]-2.77272727272727[/C][/ROW]
[ROW][C]48[/C][C]23[/C][C]21.7727272727273[/C][C]1.22727272727273[/C][/ROW]
[ROW][C]49[/C][C]24[/C][C]21.7727272727273[/C][C]2.22727272727273[/C][/ROW]
[ROW][C]50[/C][C]19[/C][C]21.7727272727273[/C][C]-2.77272727272727[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]21.7727272727273[/C][C]-5.77272727272727[/C][/ROW]
[ROW][C]52[/C][C]23[/C][C]23.7777777777778[/C][C]-0.777777777777779[/C][/ROW]
[ROW][C]53[/C][C]17[/C][C]23.7777777777778[/C][C]-6.77777777777778[/C][/ROW]
[ROW][C]54[/C][C]17[/C][C]21.7727272727273[/C][C]-4.77272727272727[/C][/ROW]
[ROW][C]55[/C][C]28[/C][C]23.7777777777778[/C][C]4.22222222222222[/C][/ROW]
[ROW][C]56[/C][C]24[/C][C]21.7727272727273[/C][C]2.22727272727273[/C][/ROW]
[ROW][C]57[/C][C]21[/C][C]17.2857142857143[/C][C]3.71428571428572[/C][/ROW]
[ROW][C]58[/C][C]14[/C][C]17.2857142857143[/C][C]-3.28571428571428[/C][/ROW]
[ROW][C]59[/C][C]21[/C][C]23.7777777777778[/C][C]-2.77777777777778[/C][/ROW]
[ROW][C]60[/C][C]20[/C][C]21.7727272727273[/C][C]-1.77272727272727[/C][/ROW]
[ROW][C]61[/C][C]25[/C][C]21.7727272727273[/C][C]3.22727272727273[/C][/ROW]
[ROW][C]62[/C][C]20[/C][C]23.7777777777778[/C][C]-3.77777777777778[/C][/ROW]
[ROW][C]63[/C][C]17[/C][C]23.7777777777778[/C][C]-6.77777777777778[/C][/ROW]
[ROW][C]64[/C][C]26[/C][C]23.7777777777778[/C][C]2.22222222222222[/C][/ROW]
[ROW][C]65[/C][C]17[/C][C]21.7727272727273[/C][C]-4.77272727272727[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]23.7777777777778[/C][C]-6.77777777777778[/C][/ROW]
[ROW][C]67[/C][C]24[/C][C]21.7727272727273[/C][C]2.22727272727273[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]23.7777777777778[/C][C]6.22222222222222[/C][/ROW]
[ROW][C]69[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]21.7727272727273[/C][C]-6.77272727272727[/C][/ROW]
[ROW][C]71[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]72[/C][C]18[/C][C]23.7777777777778[/C][C]-5.77777777777778[/C][/ROW]
[ROW][C]73[/C][C]20[/C][C]23.7777777777778[/C][C]-3.77777777777778[/C][/ROW]
[ROW][C]74[/C][C]32[/C][C]23.7777777777778[/C][C]8.22222222222222[/C][/ROW]
[ROW][C]75[/C][C]14[/C][C]17.2857142857143[/C][C]-3.28571428571428[/C][/ROW]
[ROW][C]76[/C][C]20[/C][C]21.7727272727273[/C][C]-1.77272727272727[/C][/ROW]
[ROW][C]77[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]78[/C][C]25[/C][C]21.7727272727273[/C][C]3.22727272727273[/C][/ROW]
[ROW][C]79[/C][C]25[/C][C]21.7727272727273[/C][C]3.22727272727273[/C][/ROW]
[ROW][C]80[/C][C]35[/C][C]23.7777777777778[/C][C]11.2222222222222[/C][/ROW]
[ROW][C]81[/C][C]29[/C][C]23.7777777777778[/C][C]5.22222222222222[/C][/ROW]
[ROW][C]82[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]83[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]84[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]85[/C][C]24[/C][C]23.7777777777778[/C][C]0.222222222222221[/C][/ROW]
[ROW][C]86[/C][C]26[/C][C]21.7727272727273[/C][C]4.22727272727273[/C][/ROW]
[ROW][C]87[/C][C]24[/C][C]21.7727272727273[/C][C]2.22727272727273[/C][/ROW]
[ROW][C]88[/C][C]20[/C][C]23.7777777777778[/C][C]-3.77777777777778[/C][/ROW]
[ROW][C]89[/C][C]24[/C][C]21.7727272727273[/C][C]2.22727272727273[/C][/ROW]
[ROW][C]90[/C][C]18[/C][C]17.2857142857143[/C][C]0.714285714285715[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]17.2857142857143[/C][C]-0.285714285714285[/C][/ROW]
[ROW][C]92[/C][C]22[/C][C]23.7777777777778[/C][C]-1.77777777777778[/C][/ROW]
[ROW][C]93[/C][C]22[/C][C]23.7777777777778[/C][C]-1.77777777777778[/C][/ROW]
[ROW][C]94[/C][C]22[/C][C]17.2857142857143[/C][C]4.71428571428572[/C][/ROW]
[ROW][C]95[/C][C]24[/C][C]23.7777777777778[/C][C]0.222222222222221[/C][/ROW]
[ROW][C]96[/C][C]32[/C][C]23.7777777777778[/C][C]8.22222222222222[/C][/ROW]
[ROW][C]97[/C][C]19[/C][C]21.7727272727273[/C][C]-2.77272727272727[/C][/ROW]
[ROW][C]98[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]99[/C][C]23[/C][C]21.7727272727273[/C][C]1.22727272727273[/C][/ROW]
[ROW][C]100[/C][C]26[/C][C]23.7777777777778[/C][C]2.22222222222222[/C][/ROW]
[ROW][C]101[/C][C]18[/C][C]23.7777777777778[/C][C]-5.77777777777778[/C][/ROW]
[ROW][C]102[/C][C]19[/C][C]23.7777777777778[/C][C]-4.77777777777778[/C][/ROW]
[ROW][C]103[/C][C]22[/C][C]21.7727272727273[/C][C]0.227272727272727[/C][/ROW]
[ROW][C]104[/C][C]27[/C][C]21.7727272727273[/C][C]5.22727272727273[/C][/ROW]
[ROW][C]105[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]106[/C][C]20[/C][C]21.7727272727273[/C][C]-1.77272727272727[/C][/ROW]
[ROW][C]107[/C][C]21[/C][C]23.7777777777778[/C][C]-2.77777777777778[/C][/ROW]
[ROW][C]108[/C][C]20[/C][C]21.7727272727273[/C][C]-1.77272727272727[/C][/ROW]
[ROW][C]109[/C][C]29[/C][C]23.7777777777778[/C][C]5.22222222222222[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]21.7727272727273[/C][C]8.22727272727273[/C][/ROW]
[ROW][C]111[/C][C]23[/C][C]21.7727272727273[/C][C]1.22727272727273[/C][/ROW]
[ROW][C]112[/C][C]29[/C][C]21.7727272727273[/C][C]7.22727272727273[/C][/ROW]
[ROW][C]113[/C][C]19[/C][C]23.7777777777778[/C][C]-4.77777777777778[/C][/ROW]
[ROW][C]114[/C][C]26[/C][C]23.7777777777778[/C][C]2.22222222222222[/C][/ROW]
[ROW][C]115[/C][C]22[/C][C]21.7727272727273[/C][C]0.227272727272727[/C][/ROW]
[ROW][C]116[/C][C]26[/C][C]23.7777777777778[/C][C]2.22222222222222[/C][/ROW]
[ROW][C]117[/C][C]27[/C][C]23.7777777777778[/C][C]3.22222222222222[/C][/ROW]
[ROW][C]118[/C][C]19[/C][C]23.7777777777778[/C][C]-4.77777777777778[/C][/ROW]
[ROW][C]119[/C][C]24[/C][C]23.7777777777778[/C][C]0.222222222222221[/C][/ROW]
[ROW][C]120[/C][C]26[/C][C]21.7727272727273[/C][C]4.22727272727273[/C][/ROW]
[ROW][C]121[/C][C]22[/C][C]21.7727272727273[/C][C]0.227272727272727[/C][/ROW]
[ROW][C]122[/C][C]23[/C][C]23.7777777777778[/C][C]-0.777777777777779[/C][/ROW]
[ROW][C]123[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]124[/C][C]19[/C][C]23.7777777777778[/C][C]-4.77777777777778[/C][/ROW]
[ROW][C]125[/C][C]20[/C][C]23.7777777777778[/C][C]-3.77777777777778[/C][/ROW]
[ROW][C]126[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]127[/C][C]14[/C][C]17.2857142857143[/C][C]-3.28571428571428[/C][/ROW]
[ROW][C]128[/C][C]20[/C][C]17.2857142857143[/C][C]2.71428571428572[/C][/ROW]
[ROW][C]129[/C][C]27[/C][C]23.7777777777778[/C][C]3.22222222222222[/C][/ROW]
[ROW][C]130[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]131[/C][C]21[/C][C]23.7777777777778[/C][C]-2.77777777777778[/C][/ROW]
[ROW][C]132[/C][C]14[/C][C]17.2857142857143[/C][C]-3.28571428571428[/C][/ROW]
[ROW][C]133[/C][C]21[/C][C]23.7777777777778[/C][C]-2.77777777777778[/C][/ROW]
[ROW][C]134[/C][C]23[/C][C]21.7727272727273[/C][C]1.22727272727273[/C][/ROW]
[ROW][C]135[/C][C]18[/C][C]23.7777777777778[/C][C]-5.77777777777778[/C][/ROW]
[ROW][C]136[/C][C]20[/C][C]21.7727272727273[/C][C]-1.77272727272727[/C][/ROW]
[ROW][C]137[/C][C]19[/C][C]21.7727272727273[/C][C]-2.77272727272727[/C][/ROW]
[ROW][C]138[/C][C]15[/C][C]21.7727272727273[/C][C]-6.77272727272727[/C][/ROW]
[ROW][C]139[/C][C]23[/C][C]21.7727272727273[/C][C]1.22727272727273[/C][/ROW]
[ROW][C]140[/C][C]26[/C][C]23.7777777777778[/C][C]2.22222222222222[/C][/ROW]
[ROW][C]141[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]142[/C][C]13[/C][C]17.2857142857143[/C][C]-4.28571428571428[/C][/ROW]
[ROW][C]143[/C][C]24[/C][C]21.7727272727273[/C][C]2.22727272727273[/C][/ROW]
[ROW][C]144[/C][C]17[/C][C]21.7727272727273[/C][C]-4.77272727272727[/C][/ROW]
[ROW][C]145[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[ROW][C]146[/C][C]28[/C][C]23.7777777777778[/C][C]4.22222222222222[/C][/ROW]
[ROW][C]147[/C][C]22[/C][C]23.7777777777778[/C][C]-1.77777777777778[/C][/ROW]
[ROW][C]148[/C][C]25[/C][C]17.2857142857143[/C][C]7.71428571428572[/C][/ROW]
[ROW][C]149[/C][C]18[/C][C]21.7727272727273[/C][C]-3.77272727272727[/C][/ROW]
[ROW][C]150[/C][C]27[/C][C]23.7777777777778[/C][C]3.22222222222222[/C][/ROW]
[ROW][C]151[/C][C]25[/C][C]23.7777777777778[/C][C]1.22222222222222[/C][/ROW]
[ROW][C]152[/C][C]21[/C][C]21.7727272727273[/C][C]-0.772727272727273[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110159&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110159&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	15	17.2857142857143	-2.28571428571428
2	23	23.7777777777778	-0.777777777777779
3	26	23.7777777777778	2.22222222222222
4	19	21.7727272727273	-2.77272727272727
5	19	21.7727272727273	-2.77272727272727
6	16	21.7727272727273	-5.77272727272727
7	23	23.7777777777778	-0.777777777777779
8	22	21.7727272727273	0.227272727272727
9	19	23.7777777777778	-4.77777777777778
10	24	21.7727272727273	2.22727272727273
11	19	17.2857142857143	1.71428571428572
12	25	23.7777777777778	1.22222222222222
13	23	23.7777777777778	-0.777777777777779
14	31	23.7777777777778	7.22222222222222
15	29	23.7777777777778	5.22222222222222
16	18	21.7727272727273	-3.77272727272727
17	17	21.7727272727273	-4.77272727272727
18	22	23.7777777777778	-1.77777777777778
19	21	21.7727272727273	-0.772727272727273
20	24	23.7777777777778	0.222222222222221
21	22	21.7727272727273	0.227272727272727
22	16	17.2857142857143	-1.28571428571428
23	22	21.7727272727273	0.227272727272727
24	21	21.7727272727273	-0.772727272727273
25	25	21.7727272727273	3.22727272727273
26	22	23.7777777777778	-1.77777777777778
27	24	23.7777777777778	0.222222222222221
28	21	23.7777777777778	-2.77777777777778
29	25	23.7777777777778	1.22222222222222
30	29	23.7777777777778	5.22222222222222
31	19	21.7727272727273	-2.77272727272727
32	29	23.7777777777778	5.22222222222222
33	25	21.7727272727273	3.22727272727273
34	19	23.7777777777778	-4.77777777777778
35	27	21.7727272727273	5.22727272727273
36	25	21.7727272727273	3.22727272727273
37	23	21.7727272727273	1.22727272727273
38	24	21.7727272727273	2.22727272727273
39	23	23.7777777777778	-0.777777777777779
40	25	21.7727272727273	3.22727272727273
41	26	21.7727272727273	4.22727272727273
42	23	23.7777777777778	-0.777777777777779
43	22	23.7777777777778	-1.77777777777778
44	32	23.7777777777778	8.22222222222222
45	22	23.7777777777778	-1.77777777777778
46	18	23.7777777777778	-5.77777777777778
47	19	21.7727272727273	-2.77272727272727
48	23	21.7727272727273	1.22727272727273
49	24	21.7727272727273	2.22727272727273
50	19	21.7727272727273	-2.77272727272727
51	16	21.7727272727273	-5.77272727272727
52	23	23.7777777777778	-0.777777777777779
53	17	23.7777777777778	-6.77777777777778
54	17	21.7727272727273	-4.77272727272727
55	28	23.7777777777778	4.22222222222222
56	24	21.7727272727273	2.22727272727273
57	21	17.2857142857143	3.71428571428572
58	14	17.2857142857143	-3.28571428571428
59	21	23.7777777777778	-2.77777777777778
60	20	21.7727272727273	-1.77272727272727
61	25	21.7727272727273	3.22727272727273
62	20	23.7777777777778	-3.77777777777778
63	17	23.7777777777778	-6.77777777777778
64	26	23.7777777777778	2.22222222222222
65	17	21.7727272727273	-4.77272727272727
66	17	23.7777777777778	-6.77777777777778
67	24	21.7727272727273	2.22727272727273
68	30	23.7777777777778	6.22222222222222
69	25	23.7777777777778	1.22222222222222
70	15	21.7727272727273	-6.77272727272727
71	25	23.7777777777778	1.22222222222222
72	18	23.7777777777778	-5.77777777777778
73	20	23.7777777777778	-3.77777777777778
74	32	23.7777777777778	8.22222222222222
75	14	17.2857142857143	-3.28571428571428
76	20	21.7727272727273	-1.77272727272727
77	25	23.7777777777778	1.22222222222222
78	25	21.7727272727273	3.22727272727273
79	25	21.7727272727273	3.22727272727273
80	35	23.7777777777778	11.2222222222222
81	29	23.7777777777778	5.22222222222222
82	25	23.7777777777778	1.22222222222222
83	21	21.7727272727273	-0.772727272727273
84	21	21.7727272727273	-0.772727272727273
85	24	23.7777777777778	0.222222222222221
86	26	21.7727272727273	4.22727272727273
87	24	21.7727272727273	2.22727272727273
88	20	23.7777777777778	-3.77777777777778
89	24	21.7727272727273	2.22727272727273
90	18	17.2857142857143	0.714285714285715
91	17	17.2857142857143	-0.285714285714285
92	22	23.7777777777778	-1.77777777777778
93	22	23.7777777777778	-1.77777777777778
94	22	17.2857142857143	4.71428571428572
95	24	23.7777777777778	0.222222222222221
96	32	23.7777777777778	8.22222222222222
97	19	21.7727272727273	-2.77272727272727
98	21	21.7727272727273	-0.772727272727273
99	23	21.7727272727273	1.22727272727273
100	26	23.7777777777778	2.22222222222222
101	18	23.7777777777778	-5.77777777777778
102	19	23.7777777777778	-4.77777777777778
103	22	21.7727272727273	0.227272727272727
104	27	21.7727272727273	5.22727272727273
105	21	21.7727272727273	-0.772727272727273
106	20	21.7727272727273	-1.77272727272727
107	21	23.7777777777778	-2.77777777777778
108	20	21.7727272727273	-1.77272727272727
109	29	23.7777777777778	5.22222222222222
110	30	21.7727272727273	8.22727272727273
111	23	21.7727272727273	1.22727272727273
112	29	21.7727272727273	7.22727272727273
113	19	23.7777777777778	-4.77777777777778
114	26	23.7777777777778	2.22222222222222
115	22	21.7727272727273	0.227272727272727
116	26	23.7777777777778	2.22222222222222
117	27	23.7777777777778	3.22222222222222
118	19	23.7777777777778	-4.77777777777778
119	24	23.7777777777778	0.222222222222221
120	26	21.7727272727273	4.22727272727273
121	22	21.7727272727273	0.227272727272727
122	23	23.7777777777778	-0.777777777777779
123	25	23.7777777777778	1.22222222222222
124	19	23.7777777777778	-4.77777777777778
125	20	23.7777777777778	-3.77777777777778
126	25	23.7777777777778	1.22222222222222
127	14	17.2857142857143	-3.28571428571428
128	20	17.2857142857143	2.71428571428572
129	27	23.7777777777778	3.22222222222222
130	21	21.7727272727273	-0.772727272727273
131	21	23.7777777777778	-2.77777777777778
132	14	17.2857142857143	-3.28571428571428
133	21	23.7777777777778	-2.77777777777778
134	23	21.7727272727273	1.22727272727273
135	18	23.7777777777778	-5.77777777777778
136	20	21.7727272727273	-1.77272727272727
137	19	21.7727272727273	-2.77272727272727
138	15	21.7727272727273	-6.77272727272727
139	23	21.7727272727273	1.22727272727273
140	26	23.7777777777778	2.22222222222222
141	21	21.7727272727273	-0.772727272727273
142	13	17.2857142857143	-4.28571428571428
143	24	21.7727272727273	2.22727272727273
144	17	21.7727272727273	-4.77272727272727
145	21	21.7727272727273	-0.772727272727273
146	28	23.7777777777778	4.22222222222222
147	22	23.7777777777778	-1.77777777777778
148	25	17.2857142857143	7.71428571428572
149	18	21.7727272727273	-3.77272727272727
150	27	23.7777777777778	3.22222222222222
151	25	23.7777777777778	1.22222222222222
152	21	21.7727272727273	-0.772727272727273

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 = 4 ; par2 = none ; par3 = 3 ; par4 = yes ;

Parameters (R input):

par1 = 4 ; par2 = none ; par3 = 3 ; par4 = yes ;

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