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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_regression_trees1.wasp
Title produced by softwareRecursive Partitioning (Regression Trees)
Date of computationSun, 12 Dec 2010 20:07:21 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/12/t1292184340ykgkveojywlmh0u.htm/, Retrieved Tue, 07 May 2024 17:11:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108653, Retrieved Tue, 07 May 2024 17:11:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

Tree of Dependent Computations

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)] [WS10 RP] [2010-12-12 20:07:21] [8b27277f7b82c0354d659d066108e38e] [Current]
-   PD      [Recursive Partitioning (Regression Trees)] [WS10 RP] [2010-12-12 20:20:40] [65eb19f81eab2b6e672eafaed2a27190]
-   PD      [Recursive Partitioning (Regression Trees)] [WS10 Recursive Pa...] [2010-12-13 09:33:29] [65eb19f81eab2b6e672eafaed2a27190]
-   P         [Recursive Partitioning (Regression Trees)] [WS10 RP Equal 2 cat.] [2010-12-13 10:47:37] [65eb19f81eab2b6e672eafaed2a27190]
-   P         [Recursive Partitioning (Regression Trees)] [WS10 RP equal 2 cat.] [2010-12-13 10:47:37] [65eb19f81eab2b6e672eafaed2a27190]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6	73	62	66
4	58	54	54
5	68	41	82
4	62	49	61
4	65	49	65
6	81	72	77
6	73	78	66
4	64	58	66
4	68	58	66
6	51	23	48
4	68	39	57
6	61	63	80
5	69	46	60
4	73	58	70
6	61	39	85
3	62	44	59
5	63	49	72
6	69	57	70
4	47	76	74
6	66	63	70
2	58	18	51
7	63	40	70
5	69	59	71
2	59	62	72
4	59	70	50
4	63	65	69
6	65	56	73
6	65	45	66
5	71	57	73
6	60	50	58
6	81	40	78
4	67	58	83
6	66	49	76
6	62	49	77
6	63	27	79
2	73	51	71
4	55	75	79
5	59	65	60
3	64	47	73
7	63	49	70
5	64	65	42
3	73	61	74
8	54	46	68
8	76	69	83
5	74	55	62
6	63	78	79
3	73	58	61
5	67	34	86
4	68	67	64
5	66	45	75
5	62	68	59
6	71	49	82
5	63	19	61
6	75	72	69
6	77	59	60
4	62	46	59
8	74	56	81
6	67	45	65
4	56	53	60
6	60	67	60
5	58	73	45
5	65	46	75
6	49	70	84
6	61	38	77
6	66	54	64
6	64	46	54
6	65	46	72
6	46	45	56
7	65	47	67
4	81	25	81
4	72	63	73
3	65	46	67
6	74	69	72
5	59	43	69
5	69	49	71
3	58	39	77
5	71	65	63
4	79	54	49
3	68	50	74
7	66	42	76
4	62	45	65
4	69	50	65
5	63	55	69
6	62	38	71
2	61	40	68
2	65	51	49
6	64	49	86
4	56	39	63
5	56	57	77
6	48	30	52
7	74	51	73
8	69	48	63
6	62	56	54
6	73	66	56
3	64	72	54
7	57	28	61
3	57	52	70
6	60	53	68
4	61	70	63
4	72	63	76
6	57	46	69
6	51	45	71
6	63	68	39
4	54	54	54
7	72	60	64
5	62	50	70
7	68	66	76
4	62	56	71
6	63	54	73
6	77	72	81
6	57	34	50
5	57	39	42
5	61	66	66
6	65	27	77
7	63	63	62
4	66	65	66
4	68	63	69
8	72	49	72
6	68	42	67
3	59	51	59
4	56	50	66
5	62	64	68
5	72	68	72
6	68	66	73
8	67	59	69
2	54	32	57
4	69	62	55
7	61	52	72
5	55	34	68
6	75	63	83
6	55	48	74
4	49	53	72
5	54	39	66
6	66	51	61
6	73	60	86
6	63	70	81
6	61	40	79
5	74	61	73
5	81	35	59
6	62	39	64
4	64	31	75
6	62	36	68
3	85	51	84
6	74	55	68
8	51	67	68
4	66	40	69

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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=108653&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=108653&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108653&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Goodness of Fit
CorrelationNA
R-squaredNA
RMSE1.3897

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & NA \tabularnewline
R-squared & NA \tabularnewline
RMSE & 1.3897 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108653&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]NA[/C][/ROW]
[ROW][C]R-squared[/C][C]NA[/C][/ROW]
[ROW][C]RMSE[/C][C]1.3897[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108653&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108653&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Goodness of Fit
CorrelationNA
R-squaredNA
RMSE1.3897






Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
165.143835616438360.856164383561643
245.14383561643836-1.14383561643836
355.14383561643836-0.143835616438357
445.14383561643836-1.14383561643836
545.14383561643836-1.14383561643836
665.143835616438360.856164383561643
765.143835616438360.856164383561643
845.14383561643836-1.14383561643836
945.14383561643836-1.14383561643836
1065.143835616438360.856164383561643
1145.14383561643836-1.14383561643836
1265.143835616438360.856164383561643
1355.14383561643836-0.143835616438357
1445.14383561643836-1.14383561643836
1565.143835616438360.856164383561643
1635.14383561643836-2.14383561643836
1755.14383561643836-0.143835616438357
1865.143835616438360.856164383561643
1945.14383561643836-1.14383561643836
2065.143835616438360.856164383561643
2125.14383561643836-3.14383561643836
2275.143835616438361.85616438356164
2355.14383561643836-0.143835616438357
2425.14383561643836-3.14383561643836
2545.14383561643836-1.14383561643836
2645.14383561643836-1.14383561643836
2765.143835616438360.856164383561643
2865.143835616438360.856164383561643
2955.14383561643836-0.143835616438357
3065.143835616438360.856164383561643
3165.143835616438360.856164383561643
3245.14383561643836-1.14383561643836
3365.143835616438360.856164383561643
3465.143835616438360.856164383561643
3565.143835616438360.856164383561643
3625.14383561643836-3.14383561643836
3745.14383561643836-1.14383561643836
3855.14383561643836-0.143835616438357
3935.14383561643836-2.14383561643836
4075.143835616438361.85616438356164
4155.14383561643836-0.143835616438357
4235.14383561643836-2.14383561643836
4385.143835616438362.85616438356164
4485.143835616438362.85616438356164
4555.14383561643836-0.143835616438357
4665.143835616438360.856164383561643
4735.14383561643836-2.14383561643836
4855.14383561643836-0.143835616438357
4945.14383561643836-1.14383561643836
5055.14383561643836-0.143835616438357
5155.14383561643836-0.143835616438357
5265.143835616438360.856164383561643
5355.14383561643836-0.143835616438357
5465.143835616438360.856164383561643
5565.143835616438360.856164383561643
5645.14383561643836-1.14383561643836
5785.143835616438362.85616438356164
5865.143835616438360.856164383561643
5945.14383561643836-1.14383561643836
6065.143835616438360.856164383561643
6155.14383561643836-0.143835616438357
6255.14383561643836-0.143835616438357
6365.143835616438360.856164383561643
6465.143835616438360.856164383561643
6565.143835616438360.856164383561643
6665.143835616438360.856164383561643
6765.143835616438360.856164383561643
6865.143835616438360.856164383561643
6975.143835616438361.85616438356164
7045.14383561643836-1.14383561643836
7145.14383561643836-1.14383561643836
7235.14383561643836-2.14383561643836
7365.143835616438360.856164383561643
7455.14383561643836-0.143835616438357
7555.14383561643836-0.143835616438357
7635.14383561643836-2.14383561643836
7755.14383561643836-0.143835616438357
7845.14383561643836-1.14383561643836
7935.14383561643836-2.14383561643836
8075.143835616438361.85616438356164
8145.14383561643836-1.14383561643836
8245.14383561643836-1.14383561643836
8355.14383561643836-0.143835616438357
8465.143835616438360.856164383561643
8525.14383561643836-3.14383561643836
8625.14383561643836-3.14383561643836
8765.143835616438360.856164383561643
8845.14383561643836-1.14383561643836
8955.14383561643836-0.143835616438357
9065.143835616438360.856164383561643
9175.143835616438361.85616438356164
9285.143835616438362.85616438356164
9365.143835616438360.856164383561643
9465.143835616438360.856164383561643
9535.14383561643836-2.14383561643836
9675.143835616438361.85616438356164
9735.14383561643836-2.14383561643836
9865.143835616438360.856164383561643
9945.14383561643836-1.14383561643836
10045.14383561643836-1.14383561643836
10165.143835616438360.856164383561643
10265.143835616438360.856164383561643
10365.143835616438360.856164383561643
10445.14383561643836-1.14383561643836
10575.143835616438361.85616438356164
10655.14383561643836-0.143835616438357
10775.143835616438361.85616438356164
10845.14383561643836-1.14383561643836
10965.143835616438360.856164383561643
11065.143835616438360.856164383561643
11165.143835616438360.856164383561643
11255.14383561643836-0.143835616438357
11355.14383561643836-0.143835616438357
11465.143835616438360.856164383561643
11575.143835616438361.85616438356164
11645.14383561643836-1.14383561643836
11745.14383561643836-1.14383561643836
11885.143835616438362.85616438356164
11965.143835616438360.856164383561643
12035.14383561643836-2.14383561643836
12145.14383561643836-1.14383561643836
12255.14383561643836-0.143835616438357
12355.14383561643836-0.143835616438357
12465.143835616438360.856164383561643
12585.143835616438362.85616438356164
12625.14383561643836-3.14383561643836
12745.14383561643836-1.14383561643836
12875.143835616438361.85616438356164
12955.14383561643836-0.143835616438357
13065.143835616438360.856164383561643
13165.143835616438360.856164383561643
13245.14383561643836-1.14383561643836
13355.14383561643836-0.143835616438357
13465.143835616438360.856164383561643
13565.143835616438360.856164383561643
13665.143835616438360.856164383561643
13765.143835616438360.856164383561643
13855.14383561643836-0.143835616438357
13955.14383561643836-0.143835616438357
14065.143835616438360.856164383561643
14145.14383561643836-1.14383561643836
14265.143835616438360.856164383561643
14335.14383561643836-2.14383561643836
14465.143835616438360.856164383561643
14585.143835616438362.85616438356164
14645.14383561643836-1.14383561643836

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
2 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
3 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
4 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
5 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
6 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
7 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
8 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
9 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
10 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
11 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
12 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
13 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
14 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
15 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
16 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
17 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
18 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
19 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
20 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
21 & 2 & 5.14383561643836 & -3.14383561643836 \tabularnewline
22 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
23 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
24 & 2 & 5.14383561643836 & -3.14383561643836 \tabularnewline
25 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
26 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
27 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
28 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
29 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
30 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
31 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
32 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
33 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
34 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
35 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
36 & 2 & 5.14383561643836 & -3.14383561643836 \tabularnewline
37 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
38 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
39 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
40 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
41 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
42 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
43 & 8 & 5.14383561643836 & 2.85616438356164 \tabularnewline
44 & 8 & 5.14383561643836 & 2.85616438356164 \tabularnewline
45 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
46 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
47 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
48 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
49 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
50 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
51 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
52 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
53 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
54 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
55 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
56 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
57 & 8 & 5.14383561643836 & 2.85616438356164 \tabularnewline
58 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
59 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
60 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
61 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
62 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
63 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
64 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
65 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
66 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
67 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
68 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
69 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
70 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
71 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
72 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
73 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
74 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
75 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
76 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
77 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
78 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
79 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
80 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
81 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
82 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
83 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
84 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
85 & 2 & 5.14383561643836 & -3.14383561643836 \tabularnewline
86 & 2 & 5.14383561643836 & -3.14383561643836 \tabularnewline
87 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
88 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
89 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
90 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
91 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
92 & 8 & 5.14383561643836 & 2.85616438356164 \tabularnewline
93 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
94 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
95 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
96 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
97 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
98 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
99 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
100 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
101 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
102 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
103 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
104 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
105 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
106 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
107 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
108 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
109 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
110 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
111 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
112 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
113 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
114 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
115 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
116 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
117 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
118 & 8 & 5.14383561643836 & 2.85616438356164 \tabularnewline
119 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
120 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
121 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
122 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
123 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
124 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
125 & 8 & 5.14383561643836 & 2.85616438356164 \tabularnewline
126 & 2 & 5.14383561643836 & -3.14383561643836 \tabularnewline
127 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
128 & 7 & 5.14383561643836 & 1.85616438356164 \tabularnewline
129 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
130 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
131 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
132 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
133 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
134 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
135 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
136 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
137 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
138 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
139 & 5 & 5.14383561643836 & -0.143835616438357 \tabularnewline
140 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
141 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
142 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
143 & 3 & 5.14383561643836 & -2.14383561643836 \tabularnewline
144 & 6 & 5.14383561643836 & 0.856164383561643 \tabularnewline
145 & 8 & 5.14383561643836 & 2.85616438356164 \tabularnewline
146 & 4 & 5.14383561643836 & -1.14383561643836 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108653&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]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]2[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]3[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]4[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]5[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]6[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]7[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]8[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]9[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]10[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]11[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]12[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]14[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]15[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]16[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]18[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]19[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]20[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]21[/C][C]2[/C][C]5.14383561643836[/C][C]-3.14383561643836[/C][/ROW]
[ROW][C]22[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]23[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]24[/C][C]2[/C][C]5.14383561643836[/C][C]-3.14383561643836[/C][/ROW]
[ROW][C]25[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]27[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]28[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]29[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]30[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]31[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]32[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]33[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]34[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]35[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]36[/C][C]2[/C][C]5.14383561643836[/C][C]-3.14383561643836[/C][/ROW]
[ROW][C]37[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]38[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]39[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]40[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]41[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]42[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]5.14383561643836[/C][C]2.85616438356164[/C][/ROW]
[ROW][C]44[/C][C]8[/C][C]5.14383561643836[/C][C]2.85616438356164[/C][/ROW]
[ROW][C]45[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]46[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]47[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]48[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]49[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]50[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]54[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]55[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]56[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]57[/C][C]8[/C][C]5.14383561643836[/C][C]2.85616438356164[/C][/ROW]
[ROW][C]58[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]59[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]60[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]61[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]62[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]63[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]65[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]66[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]67[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]68[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]69[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]70[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]71[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]72[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]73[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]74[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]75[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]76[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]77[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]78[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]79[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]80[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]81[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]82[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]83[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]84[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]85[/C][C]2[/C][C]5.14383561643836[/C][C]-3.14383561643836[/C][/ROW]
[ROW][C]86[/C][C]2[/C][C]5.14383561643836[/C][C]-3.14383561643836[/C][/ROW]
[ROW][C]87[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]88[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]89[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]90[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]91[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]92[/C][C]8[/C][C]5.14383561643836[/C][C]2.85616438356164[/C][/ROW]
[ROW][C]93[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]94[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]96[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]97[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]98[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]99[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]100[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]101[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]102[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]103[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]104[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]105[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]106[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]107[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]108[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]109[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]110[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]111[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]112[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]113[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]114[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]115[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]116[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]117[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]118[/C][C]8[/C][C]5.14383561643836[/C][C]2.85616438356164[/C][/ROW]
[ROW][C]119[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]120[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]121[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]122[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]123[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]124[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]125[/C][C]8[/C][C]5.14383561643836[/C][C]2.85616438356164[/C][/ROW]
[ROW][C]126[/C][C]2[/C][C]5.14383561643836[/C][C]-3.14383561643836[/C][/ROW]
[ROW][C]127[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]128[/C][C]7[/C][C]5.14383561643836[/C][C]1.85616438356164[/C][/ROW]
[ROW][C]129[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]130[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]131[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]132[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]133[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]134[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]135[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]136[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]137[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]138[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]139[/C][C]5[/C][C]5.14383561643836[/C][C]-0.143835616438357[/C][/ROW]
[ROW][C]140[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]141[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]143[/C][C]3[/C][C]5.14383561643836[/C][C]-2.14383561643836[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]5.14383561643836[/C][C]0.856164383561643[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]5.14383561643836[/C][C]2.85616438356164[/C][/ROW]
[ROW][C]146[/C][C]4[/C][C]5.14383561643836[/C][C]-1.14383561643836[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108653&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108653&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
165.143835616438360.856164383561643
245.14383561643836-1.14383561643836
355.14383561643836-0.143835616438357
445.14383561643836-1.14383561643836
545.14383561643836-1.14383561643836
665.143835616438360.856164383561643
765.143835616438360.856164383561643
845.14383561643836-1.14383561643836
945.14383561643836-1.14383561643836
1065.143835616438360.856164383561643
1145.14383561643836-1.14383561643836
1265.143835616438360.856164383561643
1355.14383561643836-0.143835616438357
1445.14383561643836-1.14383561643836
1565.143835616438360.856164383561643
1635.14383561643836-2.14383561643836
1755.14383561643836-0.143835616438357
1865.143835616438360.856164383561643
1945.14383561643836-1.14383561643836
2065.143835616438360.856164383561643
2125.14383561643836-3.14383561643836
2275.143835616438361.85616438356164
2355.14383561643836-0.143835616438357
2425.14383561643836-3.14383561643836
2545.14383561643836-1.14383561643836
2645.14383561643836-1.14383561643836
2765.143835616438360.856164383561643
2865.143835616438360.856164383561643
2955.14383561643836-0.143835616438357
3065.143835616438360.856164383561643
3165.143835616438360.856164383561643
3245.14383561643836-1.14383561643836
3365.143835616438360.856164383561643
3465.143835616438360.856164383561643
3565.143835616438360.856164383561643
3625.14383561643836-3.14383561643836
3745.14383561643836-1.14383561643836
3855.14383561643836-0.143835616438357
3935.14383561643836-2.14383561643836
4075.143835616438361.85616438356164
4155.14383561643836-0.143835616438357
4235.14383561643836-2.14383561643836
4385.143835616438362.85616438356164
4485.143835616438362.85616438356164
4555.14383561643836-0.143835616438357
4665.143835616438360.856164383561643
4735.14383561643836-2.14383561643836
4855.14383561643836-0.143835616438357
4945.14383561643836-1.14383561643836
5055.14383561643836-0.143835616438357
5155.14383561643836-0.143835616438357
5265.143835616438360.856164383561643
5355.14383561643836-0.143835616438357
5465.143835616438360.856164383561643
5565.143835616438360.856164383561643
5645.14383561643836-1.14383561643836
5785.143835616438362.85616438356164
5865.143835616438360.856164383561643
5945.14383561643836-1.14383561643836
6065.143835616438360.856164383561643
6155.14383561643836-0.143835616438357
6255.14383561643836-0.143835616438357
6365.143835616438360.856164383561643
6465.143835616438360.856164383561643
6565.143835616438360.856164383561643
6665.143835616438360.856164383561643
6765.143835616438360.856164383561643
6865.143835616438360.856164383561643
6975.143835616438361.85616438356164
7045.14383561643836-1.14383561643836
7145.14383561643836-1.14383561643836
7235.14383561643836-2.14383561643836
7365.143835616438360.856164383561643
7455.14383561643836-0.143835616438357
7555.14383561643836-0.143835616438357
7635.14383561643836-2.14383561643836
7755.14383561643836-0.143835616438357
7845.14383561643836-1.14383561643836
7935.14383561643836-2.14383561643836
8075.143835616438361.85616438356164
8145.14383561643836-1.14383561643836
8245.14383561643836-1.14383561643836
8355.14383561643836-0.143835616438357
8465.143835616438360.856164383561643
8525.14383561643836-3.14383561643836
8625.14383561643836-3.14383561643836
8765.143835616438360.856164383561643
8845.14383561643836-1.14383561643836
8955.14383561643836-0.143835616438357
9065.143835616438360.856164383561643
9175.143835616438361.85616438356164
9285.143835616438362.85616438356164
9365.143835616438360.856164383561643
9465.143835616438360.856164383561643
9535.14383561643836-2.14383561643836
9675.143835616438361.85616438356164
9735.14383561643836-2.14383561643836
9865.143835616438360.856164383561643
9945.14383561643836-1.14383561643836
10045.14383561643836-1.14383561643836
10165.143835616438360.856164383561643
10265.143835616438360.856164383561643
10365.143835616438360.856164383561643
10445.14383561643836-1.14383561643836
10575.143835616438361.85616438356164
10655.14383561643836-0.143835616438357
10775.143835616438361.85616438356164
10845.14383561643836-1.14383561643836
10965.143835616438360.856164383561643
11065.143835616438360.856164383561643
11165.143835616438360.856164383561643
11255.14383561643836-0.143835616438357
11355.14383561643836-0.143835616438357
11465.143835616438360.856164383561643
11575.143835616438361.85616438356164
11645.14383561643836-1.14383561643836
11745.14383561643836-1.14383561643836
11885.143835616438362.85616438356164
11965.143835616438360.856164383561643
12035.14383561643836-2.14383561643836
12145.14383561643836-1.14383561643836
12255.14383561643836-0.143835616438357
12355.14383561643836-0.143835616438357
12465.143835616438360.856164383561643
12585.143835616438362.85616438356164
12625.14383561643836-3.14383561643836
12745.14383561643836-1.14383561643836
12875.143835616438361.85616438356164
12955.14383561643836-0.143835616438357
13065.143835616438360.856164383561643
13165.143835616438360.856164383561643
13245.14383561643836-1.14383561643836
13355.14383561643836-0.143835616438357
13465.143835616438360.856164383561643
13565.143835616438360.856164383561643
13665.143835616438360.856164383561643
13765.143835616438360.856164383561643
13855.14383561643836-0.143835616438357
13955.14383561643836-0.143835616438357
14065.143835616438360.856164383561643
14145.14383561643836-1.14383561643836
14265.143835616438360.856164383561643
14335.14383561643836-2.14383561643836
14465.143835616438360.856164383561643
14585.143835616438362.85616438356164
14645.14383561643836-1.14383561643836


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;
Parameters (R input):
par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;
R code (references can be found in the software module):
library(party)
library(Hmisc)
par1 <- as.numeric(par1)
par3 <- as.numeric(par3)
x <- data.frame(t(y))
is.data.frame(x)
x <- x[!is.na(x[,par1]),]
k <- length(x[1,])
n <- length(x[,1])
colnames(x)[par1]
x[,par1]
if (par2 == 'kmeans') {
cl <- kmeans(x[,par1], par3)
print(cl)
clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
clm <- clm[sort.list(clm[,1]),]
for (i in 1:par3) {
cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
}
cl$cluster <- as.factor(cl$cluster)
print(cl$cluster)
x[,par1] <- cl$cluster
}
if (par2 == 'quantiles') {
x[,par1] <- cut2(x[,par1],g=par3)
}
if (par2 == 'hclust') {
hc <- hclust(dist(x[,par1])^2, 'cen')
print(hc)
memb <- cutree(hc, k = par3)
dum <- c(mean(x[memb==1,par1]))
for (i in 2:par3) {
dum <- c(dum, mean(x[memb==i,par1]))
}
hcm <- matrix(cbind(dum,1:par3),ncol=2)
hcm <- hcm[sort.list(hcm[,1]),]
for (i in 1:par3) {
memb[memb==hcm[i,2]] <- paste('C',i,sep='')
}
memb <- as.factor(memb)
print(memb)
x[,par1] <- memb
}
if (par2=='equal') {
ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
x[,par1] <- as.factor(ed)
}
table(x[,par1])
colnames(x)
colnames(x)[par1]
x[,par1]
if (par2 == 'none') {
m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
}
load(file='createtable')
if (par2 != 'none') {
m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
if (par4=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Prediction (training)',par3+1,TRUE)
a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Actual',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
a<-table.row.end(a)
for (i in 1:10) {
ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
if (i==1) {
m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
m.ct.i.actu <- x[ind==1,par1]
m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
m.ct.x.actu <- x[ind==2,par1]
} else {
m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
}
}
print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
numer <- numer + m.ct.i.tab[i,i]
}
print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
numer <- numer + m.ct.x.tab[i,i]
}
print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'Overall',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.i.cp,4))
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.x.cp,4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
}
}
m
bitmap(file='test1.png')
plot(m)
dev.off()
bitmap(file='test1a.png')
plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
dev.off()
if (par2 == 'none') {
forec <- predict(m)
result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
colnames(result) <- c('Actuals','Forecasts','Residuals')
print(result)
}
if (par2 != 'none') {
print(cbind(as.factor(x[,par1]),predict(m)))
myt <- table(as.factor(x[,par1]),predict(m))
print(myt)
}
bitmap(file='test2.png')
if(par2=='none') {
op <- par(mfrow=c(2,2))
plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
par(op)
}
if(par2!='none') {
plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
}
dev.off()
if (par2 == 'none') {
detcoef <- cor(result$Forecasts,result$Actuals)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goodness of Fit',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.element(a,round(detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'R-squared',1,TRUE)
a<-table.element(a,round(detcoef*detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'RMSE',1,TRUE)
a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#',header=TRUE)
a<-table.element(a,'Actuals',header=TRUE)
a<-table.element(a,'Forecasts',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(result$Actuals)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,result$Actuals[i])
a<-table.element(a,result$Forecasts[i])
a<-table.element(a,result$Residuals[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if (par2 != 'none') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
for (i in 1:par3) {
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (j in 1:par3) {
a<-table.element(a,myt[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}