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Author

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R Software Module

rwasp_regression_trees1.wasp

Title produced by software

Recursive Partitioning (Regression Trees)

Date of computation

Tue, 14 Dec 2010 19:33:19 +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/t1292355065zlv8gly3h14e4lo.htm/, Retrieved Fri, 03 May 2024 01:36:57 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110094, Retrieved Fri, 03 May 2024 01:36:57 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

128

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)] [] [2010-12-14 19:33:19] [23ca1b0f6f6de1e008a90be3f55e3db8] [Current]
-   P       [Recursive Partitioning (Regression Trees)] [WS10 - Review] [2010-12-16 18:17:52] [4a7069087cf9e0eda253aeed7d8c30d6] 
-             [Recursive Partitioning (Regression Trees)] [WS10 - Review] [2010-12-16 18:20:13] [4a7069087cf9e0eda253aeed7d8c30d6] 
-   P       [Recursive Partitioning (Regression Trees)] [] [2010-12-22 14:43:53] [1908ef7bb1a3d37a854f5aaad1a1c348] 
-   PD        [Recursive Partitioning (Regression Trees)] [] [2010-12-22 15:43:23] [1908ef7bb1a3d37a854f5aaad1a1c348] 
-   PD          [Recursive Partitioning (Regression Trees)] [] [2010-12-22 15:57:00] [1908ef7bb1a3d37a854f5aaad1a1c348] 
-   P         [Recursive Partitioning (Regression Trees)] [] [2010-12-22 16:34:00] [1908ef7bb1a3d37a854f5aaad1a1c348] 

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Dataseries X:

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6	4	15	10	4	4	1
11	9	9	19	7	7	1
9	9	12	15	4	4	1
14	6	16	12	5	4	1
12	8	16	14	5	6	1
18	11	15	13	4	4	1
15	10	16	11	4	5	1
12	13	13	18	5	5	1
15	10	18	12	5	4	1
13	6	17	15	3	4	1
10	8	14	15	7	7	1
13	5	13	9	4	5	1
17	9	15	11	6	5	1
15	11	15	16	5	4	1
13	11	13	17	7	7	1
17	9	13	11	5	5	1
21	7	16	13	5	5	1
12	6	14	9	4	4	1
15	6	18	11	4	4	1
16	10	16	12	7	7	1
11	4	17	13	5	8	1
9	9	15	13	2	2	1
14	10	11	13	4	3	1
14	13	11	14	5	7	1
12	8	15	9	4	5	1
15	10	15	9	4	4	1
11	5	12	15	4	4	1
11	8	17	10	4	4	1
13	9	14	15	5	6	1
12	7	17	13	4	6	1
24	20	10	24	4	4	1
11	8	15	13	4	4	1
12	7	7	22	2	4	1
13	6	9	9	5	5	1
11	10	14	12	5	7	1
14	11	11	16	7	8	1
16	12	15	10	7	7	1
12	7	16	13	4	4	1
21	12	17	11	4	4	1
6	6	15	13	4	2	1
14	9	15	10	2	4	1
16	5	16	11	5	4	1
18	11	16	9	4	4	1
13	10	12	14	2	4	1
11	7	15	11	4	5	1
16	8	17	10	4	5	1
11	9	19	11	5	5	1
11	8	15	12	1	1	1
20	13	14	14	4	5	1
10	7	16	21	5	7	1
12	7	15	13	5	7	1
14	9	12	12	7	7	1
12	9	18	12	4	4	1
12	8	13	11	4	4	1
12	7	14	14	4	4	1
13	10	15	12	2	2	1
12	7	11	12	5	4	1
9	7	15	11	4	4	1
14	10	14	15	4	4	1
12	8	16	11	4	4	1
18	5	14	22	5	7	1
17	8	18	10	3	4	1
15	9	14	11	5	5	1
8	11	13	15	4	4	1
12	8	14	11	4	4	1
10	4	17	10	5	5	1
18	16	12	14	4	7	1
15	9	16	14	6	7	1
16	10	15	11	7	8	1
17	11	16	10	5	5	1
7	8	14	12	4	4	1
12	8	17	10	5	7	1
15	6	14	12	4	1	1
13	8	16	15	4	4	1
16	14	12	11	3	4	1
18	12	13	17	2	7	1
11	11	19	8	1	1	1
13	8	11	17	4	4	1
11	8	15	13	4	2	1
13	7	12	16	4	4	1
14	9	14	13	1	1	1
18	12	11	15	4	3	1
15	6	15	14	4	4	1
9	4	12	18	5	5	1
11	6	14	14	4	4	1
17	7	13	10	6	6	1
5	4	9	20	4	4	2
20	10	12	16	4	5	2
12	6	15	10	7	7	2
11	5	17	8	7	7	2
12	8	14	14	4	4	2
13	8	11	23	5	4	2
9	11	13	9	4	2	2
9	5	10	11	3	5	2
12	7	12	10	5	7	2
12	7	15	12	5	4	2
11	8	13	10	4	4	2
17	7	13	12	7	4	2
12	7	12	14	4	4	2
8	5	9	20	4	1	2
15	4	16	8	1	1	2
9	8	17	10	5	5	2
13	6	13	11	4	4	2
9	6	10	15	4	4	2
15	9	13	12	5	5	2
14	6	16	9	4	4	2
9	6	15	13	4	5	2
8	9	16	8	4	4	2
11	8	11	11	6	3	2
16	7	15	12	6	6	2
18	10	17	11	2	2	2
12	5	14	15	1	1	2
14	8	18	7	4	3	2
16	9	14	14	4	4	2
24	20	14	10	2	2	2
11	8	12	11	4	4	2
9	6	11	13	4	4	2
17	8	14	14	3	3	2
11	10	16	14	4	3	2
11	8	17	11	4	3	2
10	6	14	13	4	4	2
12	8	14	13	4	4	2
10	8	12	12	4	4	2
10	8	12	12	5	4	2
13	8	11	18	3	4	2
14	9	15	13	7	7	2
8	7	14	14	4	4	2
11	12	10	15	4	4	2
10	8	13	11	4	4	2
7	4	15	10	4	4	2
9	6	15	12	5	6	2
11	10	16	10	4	4	2
7	5	8	20	4	4	2
15	8	9	19	5	4	2
11	8	15	11	5	8	2
13	9	11	13	4	1	2
12	6	15	9	4	4	2
11	5	16	10	7	7	2
8	4	16	12	4	3	2
12	9	15	14	2	2	2
9	5	13	11	3	5	2
12	9	15	8	5	4	2

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110094&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110094&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110094&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Goodness of Fit
Correlation	0.4808
R-squared	0.2311
RMSE	2.0705

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.4808 \tabularnewline
R-squared & 0.2311 \tabularnewline
RMSE & 2.0705 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110094&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.4808[/C][/ROW]
[ROW][C]R-squared[/C][C]0.2311[/C][/ROW]
[ROW][C]RMSE[/C][C]2.0705[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110094&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110094&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	0.4808
R-squared	0.2311
RMSE	2.0705

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	15	14.6545454545455	0.345454545454546
2	9	11.9375	-2.9375
3	12	11.9375	0.0625
4	16	14.6545454545455	1.34545454545455
5	16	14.6545454545455	1.34545454545455
6	15	14.6545454545455	0.345454545454546
7	16	14.6545454545455	1.34545454545455
8	13	11.9375	1.0625
9	18	14.6545454545455	3.34545454545455
10	17	11.9375	5.0625
11	14	11.9375	2.0625
12	13	14.6545454545455	-1.65454545454545
13	15	14.6545454545455	0.345454545454546
14	15	11.9375	3.0625
15	13	11.9375	1.0625
16	13	14.6545454545455	-1.65454545454545
17	16	14.6545454545455	1.34545454545455
18	14	14.6545454545455	-0.654545454545454
19	18	14.6545454545455	3.34545454545455
20	16	14.6545454545455	1.34545454545455
21	17	14.6545454545455	2.34545454545455
22	15	14.6545454545455	0.345454545454546
23	11	14.6545454545455	-3.65454545454545
24	11	14.6545454545455	-3.65454545454545
25	15	14.6545454545455	0.345454545454546
26	15	14.6545454545455	0.345454545454546
27	12	11.9375	0.0625
28	17	14.6545454545455	2.34545454545455
29	14	11.9375	2.0625
30	17	14.6545454545455	2.34545454545455
31	10	11.9375	-1.9375
32	15	14.6545454545455	0.345454545454546
33	7	11.9375	-4.9375
34	9	14.6545454545455	-5.65454545454545
35	14	14.6545454545455	-0.654545454545454
36	11	11.9375	-0.9375
37	15	14.6545454545455	0.345454545454546
38	16	14.6545454545455	1.34545454545455
39	17	14.6545454545455	2.34545454545455
40	15	14.6545454545455	0.345454545454546
41	15	14.6545454545455	0.345454545454546
42	16	14.6545454545455	1.34545454545455
43	16	14.6545454545455	1.34545454545455
44	12	14.6545454545455	-2.65454545454545
45	15	14.6545454545455	0.345454545454546
46	17	14.6545454545455	2.34545454545455
47	19	14.6545454545455	4.34545454545455
48	15	14.6545454545455	0.345454545454546
49	14	14.6545454545455	-0.654545454545454
50	16	11.9375	4.0625
51	15	14.6545454545455	0.345454545454546
52	12	14.6545454545455	-2.65454545454545
53	18	14.6545454545455	3.34545454545455
54	13	14.6545454545455	-1.65454545454545
55	14	14.6545454545455	-0.654545454545454
56	15	14.6545454545455	0.345454545454546
57	11	14.6545454545455	-3.65454545454545
58	15	14.6545454545455	0.345454545454546
59	14	11.9375	2.0625
60	16	14.6545454545455	1.34545454545455
61	14	11.9375	2.0625
62	18	14.6545454545455	3.34545454545455
63	14	14.6545454545455	-0.654545454545454
64	13	11.9375	1.0625
65	14	14.6545454545455	-0.654545454545454
66	17	14.6545454545455	2.34545454545455
67	12	14.6545454545455	-2.65454545454545
68	16	14.6545454545455	1.34545454545455
69	15	14.6545454545455	0.345454545454546
70	16	14.6545454545455	1.34545454545455
71	14	14.6545454545455	-0.654545454545454
72	17	14.6545454545455	2.34545454545455
73	14	14.6545454545455	-0.654545454545454
74	16	11.9375	4.0625
75	12	14.6545454545455	-2.65454545454545
76	13	11.9375	1.0625
77	19	14.6545454545455	4.34545454545455
78	11	11.9375	-0.9375
79	15	14.6545454545455	0.345454545454546
80	12	11.9375	0.0625
81	14	14.6545454545455	-0.654545454545454
82	11	11.9375	-0.9375
83	15	14.6545454545455	0.345454545454546
84	12	11.9375	0.0625
85	14	14.6545454545455	-0.654545454545454
86	13	14.6545454545455	-1.65454545454545
87	9	11.9375	-2.9375
88	12	11.9375	0.0625
89	15	14.6545454545455	0.345454545454546
90	17	14.6545454545455	2.34545454545455
91	14	14.6545454545455	-0.654545454545454
92	11	11.9375	-0.9375
93	13	14.6545454545455	-1.65454545454545
94	10	14.6545454545455	-4.65454545454545
95	12	14.6545454545455	-2.65454545454545
96	15	14.6545454545455	0.345454545454546
97	13	14.6545454545455	-1.65454545454545
98	13	14.6545454545455	-1.65454545454545
99	12	14.6545454545455	-2.65454545454545
100	9	11.9375	-2.9375
101	16	14.6545454545455	1.34545454545455
102	17	14.6545454545455	2.34545454545455
103	13	14.6545454545455	-1.65454545454545
104	10	11.9375	-1.9375
105	13	14.6545454545455	-1.65454545454545
106	16	14.6545454545455	1.34545454545455
107	15	14.6545454545455	0.345454545454546
108	16	14.6545454545455	1.34545454545455
109	11	14.6545454545455	-3.65454545454545
110	15	14.6545454545455	0.345454545454546
111	17	14.6545454545455	2.34545454545455
112	14	11.9375	2.0625
113	18	14.6545454545455	3.34545454545455
114	14	14.6545454545455	-0.654545454545454
115	14	14.6545454545455	-0.654545454545454
116	12	14.6545454545455	-2.65454545454545
117	11	14.6545454545455	-3.65454545454545
118	14	14.6545454545455	-0.654545454545454
119	16	14.6545454545455	1.34545454545455
120	17	14.6545454545455	2.34545454545455
121	14	14.6545454545455	-0.654545454545454
122	14	14.6545454545455	-0.654545454545454
123	12	14.6545454545455	-2.65454545454545
124	12	14.6545454545455	-2.65454545454545
125	11	11.9375	-0.9375
126	15	14.6545454545455	0.345454545454546
127	14	14.6545454545455	-0.654545454545454
128	10	11.9375	-1.9375
129	13	14.6545454545455	-1.65454545454545
130	15	14.6545454545455	0.345454545454546
131	15	14.6545454545455	0.345454545454546
132	16	14.6545454545455	1.34545454545455
133	8	11.9375	-3.9375
134	9	11.9375	-2.9375
135	15	14.6545454545455	0.345454545454546
136	11	14.6545454545455	-3.65454545454545
137	15	14.6545454545455	0.345454545454546
138	16	14.6545454545455	1.34545454545455
139	16	14.6545454545455	1.34545454545455
140	15	14.6545454545455	0.345454545454546
141	13	14.6545454545455	-1.65454545454545
142	15	14.6545454545455	0.345454545454546

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
2 & 9 & 11.9375 & -2.9375 \tabularnewline
3 & 12 & 11.9375 & 0.0625 \tabularnewline
4 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
5 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
6 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
7 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
8 & 13 & 11.9375 & 1.0625 \tabularnewline
9 & 18 & 14.6545454545455 & 3.34545454545455 \tabularnewline
10 & 17 & 11.9375 & 5.0625 \tabularnewline
11 & 14 & 11.9375 & 2.0625 \tabularnewline
12 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
13 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
14 & 15 & 11.9375 & 3.0625 \tabularnewline
15 & 13 & 11.9375 & 1.0625 \tabularnewline
16 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
17 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
18 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
19 & 18 & 14.6545454545455 & 3.34545454545455 \tabularnewline
20 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
21 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
22 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
23 & 11 & 14.6545454545455 & -3.65454545454545 \tabularnewline
24 & 11 & 14.6545454545455 & -3.65454545454545 \tabularnewline
25 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
26 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
27 & 12 & 11.9375 & 0.0625 \tabularnewline
28 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
29 & 14 & 11.9375 & 2.0625 \tabularnewline
30 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
31 & 10 & 11.9375 & -1.9375 \tabularnewline
32 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
33 & 7 & 11.9375 & -4.9375 \tabularnewline
34 & 9 & 14.6545454545455 & -5.65454545454545 \tabularnewline
35 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
36 & 11 & 11.9375 & -0.9375 \tabularnewline
37 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
38 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
39 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
40 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
41 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
42 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
43 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
44 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
45 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
46 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
47 & 19 & 14.6545454545455 & 4.34545454545455 \tabularnewline
48 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
49 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
50 & 16 & 11.9375 & 4.0625 \tabularnewline
51 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
52 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
53 & 18 & 14.6545454545455 & 3.34545454545455 \tabularnewline
54 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
55 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
56 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
57 & 11 & 14.6545454545455 & -3.65454545454545 \tabularnewline
58 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
59 & 14 & 11.9375 & 2.0625 \tabularnewline
60 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
61 & 14 & 11.9375 & 2.0625 \tabularnewline
62 & 18 & 14.6545454545455 & 3.34545454545455 \tabularnewline
63 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
64 & 13 & 11.9375 & 1.0625 \tabularnewline
65 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
66 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
67 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
68 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
69 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
70 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
71 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
72 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
73 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
74 & 16 & 11.9375 & 4.0625 \tabularnewline
75 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
76 & 13 & 11.9375 & 1.0625 \tabularnewline
77 & 19 & 14.6545454545455 & 4.34545454545455 \tabularnewline
78 & 11 & 11.9375 & -0.9375 \tabularnewline
79 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
80 & 12 & 11.9375 & 0.0625 \tabularnewline
81 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
82 & 11 & 11.9375 & -0.9375 \tabularnewline
83 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
84 & 12 & 11.9375 & 0.0625 \tabularnewline
85 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
86 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
87 & 9 & 11.9375 & -2.9375 \tabularnewline
88 & 12 & 11.9375 & 0.0625 \tabularnewline
89 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
90 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
91 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
92 & 11 & 11.9375 & -0.9375 \tabularnewline
93 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
94 & 10 & 14.6545454545455 & -4.65454545454545 \tabularnewline
95 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
96 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
97 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
98 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
99 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
100 & 9 & 11.9375 & -2.9375 \tabularnewline
101 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
102 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
103 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
104 & 10 & 11.9375 & -1.9375 \tabularnewline
105 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
106 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
107 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
108 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
109 & 11 & 14.6545454545455 & -3.65454545454545 \tabularnewline
110 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
111 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
112 & 14 & 11.9375 & 2.0625 \tabularnewline
113 & 18 & 14.6545454545455 & 3.34545454545455 \tabularnewline
114 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
115 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
116 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
117 & 11 & 14.6545454545455 & -3.65454545454545 \tabularnewline
118 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
119 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
120 & 17 & 14.6545454545455 & 2.34545454545455 \tabularnewline
121 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
122 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
123 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
124 & 12 & 14.6545454545455 & -2.65454545454545 \tabularnewline
125 & 11 & 11.9375 & -0.9375 \tabularnewline
126 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
127 & 14 & 14.6545454545455 & -0.654545454545454 \tabularnewline
128 & 10 & 11.9375 & -1.9375 \tabularnewline
129 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
130 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
131 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
132 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
133 & 8 & 11.9375 & -3.9375 \tabularnewline
134 & 9 & 11.9375 & -2.9375 \tabularnewline
135 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
136 & 11 & 14.6545454545455 & -3.65454545454545 \tabularnewline
137 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
138 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
139 & 16 & 14.6545454545455 & 1.34545454545455 \tabularnewline
140 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
141 & 13 & 14.6545454545455 & -1.65454545454545 \tabularnewline
142 & 15 & 14.6545454545455 & 0.345454545454546 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110094&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]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]2[/C][C]9[/C][C]11.9375[/C][C]-2.9375[/C][/ROW]
[ROW][C]3[/C][C]12[/C][C]11.9375[/C][C]0.0625[/C][/ROW]
[ROW][C]4[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]6[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]7[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]8[/C][C]13[/C][C]11.9375[/C][C]1.0625[/C][/ROW]
[ROW][C]9[/C][C]18[/C][C]14.6545454545455[/C][C]3.34545454545455[/C][/ROW]
[ROW][C]10[/C][C]17[/C][C]11.9375[/C][C]5.0625[/C][/ROW]
[ROW][C]11[/C][C]14[/C][C]11.9375[/C][C]2.0625[/C][/ROW]
[ROW][C]12[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]14[/C][C]15[/C][C]11.9375[/C][C]3.0625[/C][/ROW]
[ROW][C]15[/C][C]13[/C][C]11.9375[/C][C]1.0625[/C][/ROW]
[ROW][C]16[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]17[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]18[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]14.6545454545455[/C][C]3.34545454545455[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]21[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]22[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]23[/C][C]11[/C][C]14.6545454545455[/C][C]-3.65454545454545[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]14.6545454545455[/C][C]-3.65454545454545[/C][/ROW]
[ROW][C]25[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]26[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]27[/C][C]12[/C][C]11.9375[/C][C]0.0625[/C][/ROW]
[ROW][C]28[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]11.9375[/C][C]2.0625[/C][/ROW]
[ROW][C]30[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]31[/C][C]10[/C][C]11.9375[/C][C]-1.9375[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]33[/C][C]7[/C][C]11.9375[/C][C]-4.9375[/C][/ROW]
[ROW][C]34[/C][C]9[/C][C]14.6545454545455[/C][C]-5.65454545454545[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]36[/C][C]11[/C][C]11.9375[/C][C]-0.9375[/C][/ROW]
[ROW][C]37[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]38[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]40[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]46[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]47[/C][C]19[/C][C]14.6545454545455[/C][C]4.34545454545455[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]49[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]50[/C][C]16[/C][C]11.9375[/C][C]4.0625[/C][/ROW]
[ROW][C]51[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]52[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]14.6545454545455[/C][C]3.34545454545455[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]55[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]57[/C][C]11[/C][C]14.6545454545455[/C][C]-3.65454545454545[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]59[/C][C]14[/C][C]11.9375[/C][C]2.0625[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]61[/C][C]14[/C][C]11.9375[/C][C]2.0625[/C][/ROW]
[ROW][C]62[/C][C]18[/C][C]14.6545454545455[/C][C]3.34545454545455[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]64[/C][C]13[/C][C]11.9375[/C][C]1.0625[/C][/ROW]
[ROW][C]65[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]67[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]68[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]72[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]74[/C][C]16[/C][C]11.9375[/C][C]4.0625[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]11.9375[/C][C]1.0625[/C][/ROW]
[ROW][C]77[/C][C]19[/C][C]14.6545454545455[/C][C]4.34545454545455[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.9375[/C][C]-0.9375[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.9375[/C][C]0.0625[/C][/ROW]
[ROW][C]81[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]82[/C][C]11[/C][C]11.9375[/C][C]-0.9375[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]11.9375[/C][C]0.0625[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]87[/C][C]9[/C][C]11.9375[/C][C]-2.9375[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.9375[/C][C]0.0625[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]91[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]92[/C][C]11[/C][C]11.9375[/C][C]-0.9375[/C][/ROW]
[ROW][C]93[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]94[/C][C]10[/C][C]14.6545454545455[/C][C]-4.65454545454545[/C][/ROW]
[ROW][C]95[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]96[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]97[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]98[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]99[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]11.9375[/C][C]-2.9375[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]102[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]103[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]104[/C][C]10[/C][C]11.9375[/C][C]-1.9375[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]109[/C][C]11[/C][C]14.6545454545455[/C][C]-3.65454545454545[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]111[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]112[/C][C]14[/C][C]11.9375[/C][C]2.0625[/C][/ROW]
[ROW][C]113[/C][C]18[/C][C]14.6545454545455[/C][C]3.34545454545455[/C][/ROW]
[ROW][C]114[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]115[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]116[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]117[/C][C]11[/C][C]14.6545454545455[/C][C]-3.65454545454545[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]120[/C][C]17[/C][C]14.6545454545455[/C][C]2.34545454545455[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]122[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]123[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]124[/C][C]12[/C][C]14.6545454545455[/C][C]-2.65454545454545[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]11.9375[/C][C]-0.9375[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]127[/C][C]14[/C][C]14.6545454545455[/C][C]-0.654545454545454[/C][/ROW]
[ROW][C]128[/C][C]10[/C][C]11.9375[/C][C]-1.9375[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]130[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]131[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]133[/C][C]8[/C][C]11.9375[/C][C]-3.9375[/C][/ROW]
[ROW][C]134[/C][C]9[/C][C]11.9375[/C][C]-2.9375[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]14.6545454545455[/C][C]-3.65454545454545[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]139[/C][C]16[/C][C]14.6545454545455[/C][C]1.34545454545455[/C][/ROW]
[ROW][C]140[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[ROW][C]141[/C][C]13[/C][C]14.6545454545455[/C][C]-1.65454545454545[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]14.6545454545455[/C][C]0.345454545454546[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110094&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110094&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	14.6545454545455	0.345454545454546
2	9	11.9375	-2.9375
3	12	11.9375	0.0625
4	16	14.6545454545455	1.34545454545455
5	16	14.6545454545455	1.34545454545455
6	15	14.6545454545455	0.345454545454546
7	16	14.6545454545455	1.34545454545455
8	13	11.9375	1.0625
9	18	14.6545454545455	3.34545454545455
10	17	11.9375	5.0625
11	14	11.9375	2.0625
12	13	14.6545454545455	-1.65454545454545
13	15	14.6545454545455	0.345454545454546
14	15	11.9375	3.0625
15	13	11.9375	1.0625
16	13	14.6545454545455	-1.65454545454545
17	16	14.6545454545455	1.34545454545455
18	14	14.6545454545455	-0.654545454545454
19	18	14.6545454545455	3.34545454545455
20	16	14.6545454545455	1.34545454545455
21	17	14.6545454545455	2.34545454545455
22	15	14.6545454545455	0.345454545454546
23	11	14.6545454545455	-3.65454545454545
24	11	14.6545454545455	-3.65454545454545
25	15	14.6545454545455	0.345454545454546
26	15	14.6545454545455	0.345454545454546
27	12	11.9375	0.0625
28	17	14.6545454545455	2.34545454545455
29	14	11.9375	2.0625
30	17	14.6545454545455	2.34545454545455
31	10	11.9375	-1.9375
32	15	14.6545454545455	0.345454545454546
33	7	11.9375	-4.9375
34	9	14.6545454545455	-5.65454545454545
35	14	14.6545454545455	-0.654545454545454
36	11	11.9375	-0.9375
37	15	14.6545454545455	0.345454545454546
38	16	14.6545454545455	1.34545454545455
39	17	14.6545454545455	2.34545454545455
40	15	14.6545454545455	0.345454545454546
41	15	14.6545454545455	0.345454545454546
42	16	14.6545454545455	1.34545454545455
43	16	14.6545454545455	1.34545454545455
44	12	14.6545454545455	-2.65454545454545
45	15	14.6545454545455	0.345454545454546
46	17	14.6545454545455	2.34545454545455
47	19	14.6545454545455	4.34545454545455
48	15	14.6545454545455	0.345454545454546
49	14	14.6545454545455	-0.654545454545454
50	16	11.9375	4.0625
51	15	14.6545454545455	0.345454545454546
52	12	14.6545454545455	-2.65454545454545
53	18	14.6545454545455	3.34545454545455
54	13	14.6545454545455	-1.65454545454545
55	14	14.6545454545455	-0.654545454545454
56	15	14.6545454545455	0.345454545454546
57	11	14.6545454545455	-3.65454545454545
58	15	14.6545454545455	0.345454545454546
59	14	11.9375	2.0625
60	16	14.6545454545455	1.34545454545455
61	14	11.9375	2.0625
62	18	14.6545454545455	3.34545454545455
63	14	14.6545454545455	-0.654545454545454
64	13	11.9375	1.0625
65	14	14.6545454545455	-0.654545454545454
66	17	14.6545454545455	2.34545454545455
67	12	14.6545454545455	-2.65454545454545
68	16	14.6545454545455	1.34545454545455
69	15	14.6545454545455	0.345454545454546
70	16	14.6545454545455	1.34545454545455
71	14	14.6545454545455	-0.654545454545454
72	17	14.6545454545455	2.34545454545455
73	14	14.6545454545455	-0.654545454545454
74	16	11.9375	4.0625
75	12	14.6545454545455	-2.65454545454545
76	13	11.9375	1.0625
77	19	14.6545454545455	4.34545454545455
78	11	11.9375	-0.9375
79	15	14.6545454545455	0.345454545454546
80	12	11.9375	0.0625
81	14	14.6545454545455	-0.654545454545454
82	11	11.9375	-0.9375
83	15	14.6545454545455	0.345454545454546
84	12	11.9375	0.0625
85	14	14.6545454545455	-0.654545454545454
86	13	14.6545454545455	-1.65454545454545
87	9	11.9375	-2.9375
88	12	11.9375	0.0625
89	15	14.6545454545455	0.345454545454546
90	17	14.6545454545455	2.34545454545455
91	14	14.6545454545455	-0.654545454545454
92	11	11.9375	-0.9375
93	13	14.6545454545455	-1.65454545454545
94	10	14.6545454545455	-4.65454545454545
95	12	14.6545454545455	-2.65454545454545
96	15	14.6545454545455	0.345454545454546
97	13	14.6545454545455	-1.65454545454545
98	13	14.6545454545455	-1.65454545454545
99	12	14.6545454545455	-2.65454545454545
100	9	11.9375	-2.9375
101	16	14.6545454545455	1.34545454545455
102	17	14.6545454545455	2.34545454545455
103	13	14.6545454545455	-1.65454545454545
104	10	11.9375	-1.9375
105	13	14.6545454545455	-1.65454545454545
106	16	14.6545454545455	1.34545454545455
107	15	14.6545454545455	0.345454545454546
108	16	14.6545454545455	1.34545454545455
109	11	14.6545454545455	-3.65454545454545
110	15	14.6545454545455	0.345454545454546
111	17	14.6545454545455	2.34545454545455
112	14	11.9375	2.0625
113	18	14.6545454545455	3.34545454545455
114	14	14.6545454545455	-0.654545454545454
115	14	14.6545454545455	-0.654545454545454
116	12	14.6545454545455	-2.65454545454545
117	11	14.6545454545455	-3.65454545454545
118	14	14.6545454545455	-0.654545454545454
119	16	14.6545454545455	1.34545454545455
120	17	14.6545454545455	2.34545454545455
121	14	14.6545454545455	-0.654545454545454
122	14	14.6545454545455	-0.654545454545454
123	12	14.6545454545455	-2.65454545454545
124	12	14.6545454545455	-2.65454545454545
125	11	11.9375	-0.9375
126	15	14.6545454545455	0.345454545454546
127	14	14.6545454545455	-0.654545454545454
128	10	11.9375	-1.9375
129	13	14.6545454545455	-1.65454545454545
130	15	14.6545454545455	0.345454545454546
131	15	14.6545454545455	0.345454545454546
132	16	14.6545454545455	1.34545454545455
133	8	11.9375	-3.9375
134	9	11.9375	-2.9375
135	15	14.6545454545455	0.345454545454546
136	11	14.6545454545455	-3.65454545454545
137	15	14.6545454545455	0.345454545454546
138	16	14.6545454545455	1.34545454545455
139	16	14.6545454545455	1.34545454545455
140	15	14.6545454545455	0.345454545454546
141	13	14.6545454545455	-1.65454545454545
142	15	14.6545454545455	0.345454545454546

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 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

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

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

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code