Free Statistics

of Irreproducible Research!

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 computationThu, 06 Dec 2012 17:48:38 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/06/t13548342584gfrz8j69ve713z.htm/, Retrieved Fri, 19 Apr 2024 23:13:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197253, Retrieved Fri, 19 Apr 2024 23:13:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
-   PD  [Multiple Regression] [ws10] [2012-12-06 14:02:01] [0883bf8f4217d775edf6393676d58a73]
- RMP     [Recursive Partitioning (Regression Trees)] [ws10] [2012-12-06 22:21:12] [0883bf8f4217d775edf6393676d58a73]
- R P         [Recursive Partitioning (Regression Trees)] [ws10] [2012-12-06 22:48:38] [0ce3a3cc7b36ec2616d0d876d7c7ef2d] [Current]
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Dataseries X:
2	7	41	38	13	12	14	12
2	5	39	32	16	11	18	11
2	5	30	35	19	15	11	14
1	5	31	33	15	6	12	12
2	8	34	37	14	13	16	21
2	6	35	29	13	10	18	12
2	5	39	31	19	12	14	22
2	6	34	36	15	14	14	11
2	5	36	35	14	12	15	10
2	4	37	38	15	6	15	13
1	6	38	31	16	10	17	10
2	5	36	34	16	12	19	8
1	5	38	35	16	12	10	15
2	6	39	38	16	11	16	14
2	7	33	37	17	15	18	10
1	6	32	33	15	12	14	14
1	7	36	32	15	10	14	14
2	6	38	38	20	12	17	11
1	8	39	38	18	11	14	10
2	7	32	32	16	12	16	13
1	5	32	33	16	11	18	7
2	5	31	31	16	12	11	14
2	7	39	38	19	13	14	12
2	7	37	39	16	11	12	14
1	5	39	32	17	9	17	11
2	4	41	32	17	13	9	9
1	10	36	35	16	10	16	11
2	6	33	37	15	14	14	15
2	5	33	33	16	12	15	14
1	5	34	33	14	10	11	13
2	5	31	28	15	12	16	9
1	5	27	32	12	8	13	15
2	6	37	31	14	10	17	10
2	5	34	37	16	12	15	11
1	5	34	30	14	12	14	13
1	5	32	33	7	7	16	8
1	5	29	31	10	6	9	20
1	5	36	33	14	12	15	12
2	5	29	31	16	10	17	10
1	5	35	33	16	10	13	10
1	5	37	32	16	10	15	9
2	7	34	33	14	12	16	14
1	5	38	32	20	15	16	8
1	6	35	33	14	10	12	14
2	7	38	28	14	10	12	11
2	7	37	35	11	12	11	13
2	5	38	39	14	13	15	9
2	5	33	34	15	11	15	11
2	4	36	38	16	11	17	15
1	5	38	32	14	12	13	11
2	4	32	38	16	14	16	10
1	5	32	30	14	10	14	14
1	5	32	33	12	12	11	18
2	7	34	38	16	13	12	14
1	5	32	32	9	5	12	11
2	5	37	32	14	6	15	12
2	6	39	34	16	12	16	13
2	4	29	34	16	12	15	9
1	6	37	36	15	11	12	10
2	6	35	34	16	10	12	15
1	5	30	28	12	7	8	20
1	7	38	34	16	12	13	12
2	6	34	35	16	14	11	12
2	8	31	35	14	11	14	14
2	7	34	31	16	12	15	13
1	5	35	37	17	13	10	11
2	6	36	35	18	14	11	17
1	6	30	27	18	11	12	12
2	5	39	40	12	12	15	13
1	5	35	37	16	12	15	14
1	5	38	36	10	8	14	13
2	5	31	38	14	11	16	15
2	4	34	39	18	14	15	13
1	6	38	41	18	14	15	10
1	6	34	27	16	12	13	11
2	6	39	30	17	9	12	19
2	6	37	37	16	13	17	13
2	7	34	31	16	11	13	17
1	5	28	31	13	12	15	13
1	7	37	27	16	12	13	9
1	6	33	36	16	12	15	11
1	5	37	38	20	12	16	10
2	5	35	37	16	12	15	9
1	4	37	33	15	12	16	12
2	8	32	34	15	11	15	12
2	8	33	31	16	10	14	13
1	5	38	39	14	9	15	13
2	5	33	34	16	12	14	12
2	6	29	32	16	12	13	15
2	4	33	33	15	12	7	22
2	5	31	36	12	9	17	13
2	5	36	32	17	15	13	15
2	5	35	41	16	12	15	13
2	5	32	28	15	12	14	15
2	6	29	30	13	12	13	10
2	6	39	36	16	10	16	11
2	5	37	35	16	13	12	16
2	6	35	31	16	9	14	11
1	5	37	34	16	12	17	11
1	7	32	36	14	10	15	10
2	5	38	36	16	14	17	10
1	6	37	35	16	11	12	16
2	6	36	37	20	15	16	12
1	6	32	28	15	11	11	11
2	4	33	39	16	11	15	16
1	5	40	32	13	12	9	19
2	5	38	35	17	12	16	11
1	7	41	39	16	12	15	16
1	6	36	35	16	11	10	15
2	9	43	42	12	7	10	24
2	6	30	34	16	12	15	14
2	6	31	33	16	14	11	15
2	5	32	41	17	11	13	11
1	6	32	33	13	11	14	15
2	5	37	34	12	10	18	12
1	8	37	32	18	13	16	10
2	7	33	40	14	13	14	14
2	5	34	40	14	8	14	13
2	7	33	35	13	11	14	9
2	6	38	36	16	12	14	15
2	6	33	37	13	11	12	15
2	9	31	27	16	13	14	14
2	7	38	39	13	12	15	11
2	6	37	38	16	14	15	8
2	5	33	31	15	13	15	11
2	5	31	33	16	15	13	11
1	6	39	32	15	10	17	8
2	6	44	39	17	11	17	10
2	7	33	36	15	9	19	11
2	5	35	33	12	11	15	13
1	5	32	33	16	10	13	11
1	5	28	32	10	11	9	20
2	6	40	37	16	8	15	10
1	4	27	30	12	11	15	15
1	5	37	38	14	12	15	12
2	7	32	29	15	12	16	14
1	5	28	22	13	9	11	23
1	7	34	35	15	11	14	14
2	7	30	35	11	10	11	16
2	6	35	34	12	8	15	11
1	5	31	35	8	9	13	12
2	8	32	34	16	8	15	10
1	5	30	34	15	9	16	14
2	5	30	35	17	15	14	12
1	5	31	23	16	11	15	12
2	6	40	31	10	8	16	11
2	4	32	27	18	13	16	12
1	5	36	36	13	12	11	13
1	5	32	31	16	12	12	11
1	7	35	32	13	9	9	19
2	6	38	39	10	7	16	12
2	7	42	37	15	13	13	17
1	10	34	38	16	9	16	9
2	6	35	39	16	6	12	12
2	8	35	34	14	8	9	19
2	4	33	31	10	8	13	18
2	5	36	32	17	15	13	15
2	6	32	37	13	6	14	14
2	7	33	36	15	9	19	11
2	7	34	32	16	11	13	9
2	6	32	35	12	8	12	18
2	6	34	36	13	8	13	16




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 6 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197253&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197253&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197253&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Goodness of Fit
Correlation0.5325
R-squared0.2835
RMSE1.9725

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.5325 \tabularnewline
R-squared & 0.2835 \tabularnewline
RMSE & 1.9725 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197253&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.5325[/C][/ROW]
[ROW][C]R-squared[/C][C]0.2835[/C][/ROW]
[ROW][C]RMSE[/C][C]1.9725[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197253&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197253&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
Correlation0.5325
R-squared0.2835
RMSE1.9725







Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
11414.8039215686275-0.803921568627452
21814.80392156862753.19607843137255
31113.5238095238095-2.52380952380952
41214.8039215686275-2.80392156862745
51610.88888888888895.11111111111111
61814.80392156862753.19607843137255
71410.88888888888893.11111111111111
81414.8039215686275-0.803921568627452
91514.80392156862750.196078431372548
101514.80392156862750.196078431372548
111714.80392156862752.19607843137255
121914.80392156862754.19607843137255
131013.5238095238095-3.52380952380952
141613.52380952380952.47619047619048
151814.80392156862753.19607843137255
161413.52380952380950.476190476190476
171413.52380952380950.476190476190476
181714.80392156862752.19607843137255
191414.8039215686275-0.803921568627452
201614.80392156862751.19607843137255
211814.80392156862753.19607843137255
221113.5238095238095-2.52380952380952
231414.8039215686275-0.803921568627452
241213.5238095238095-1.52380952380952
251714.80392156862752.19607843137255
26914.8039215686275-5.80392156862745
271614.80392156862751.19607843137255
281413.52380952380950.476190476190476
291513.52380952380951.47619047619048
301114.8039215686275-3.80392156862745
311614.80392156862751.19607843137255
321313.5238095238095-0.523809523809524
331714.80392156862752.19607843137255
341514.80392156862750.196078431372548
351414.8039215686275-0.803921568627452
361614.80392156862751.19607843137255
37910.8888888888889-1.88888888888889
381514.80392156862750.196078431372548
391714.80392156862752.19607843137255
401314.8039215686275-1.80392156862745
411514.80392156862750.196078431372548
421613.52380952380952.47619047619048
431614.80392156862751.19607843137255
441213.5238095238095-1.52380952380952
451214.8039215686275-2.80392156862745
461114.8039215686275-3.80392156862745
471514.80392156862750.196078431372548
481514.80392156862750.196078431372548
491713.52380952380953.47619047619048
501314.8039215686275-1.80392156862745
511614.80392156862751.19607843137255
521413.52380952380950.476190476190476
531110.88888888888890.111111111111111
541213.5238095238095-1.52380952380952
551214.8039215686275-2.80392156862745
561514.80392156862750.196078431372548
571614.80392156862751.19607843137255
581514.80392156862750.196078431372548
591214.8039215686275-2.80392156862745
601213.5238095238095-1.52380952380952
61810.8888888888889-2.88888888888889
621314.8039215686275-1.80392156862745
631114.8039215686275-3.80392156862745
641413.52380952380950.476190476190476
651514.80392156862750.196078431372548
661014.8039215686275-4.80392156862745
671110.88888888888890.111111111111111
681214.8039215686275-2.80392156862745
691514.80392156862750.196078431372548
701513.52380952380951.47619047619048
711414.8039215686275-0.803921568627452
721613.52380952380952.47619047619048
731514.80392156862750.196078431372548
741514.80392156862750.196078431372548
751314.8039215686275-1.80392156862745
761210.88888888888891.11111111111111
771714.80392156862752.19607843137255
781310.88888888888892.11111111111111
791514.80392156862750.196078431372548
801314.8039215686275-1.80392156862745
811514.80392156862750.196078431372548
821614.80392156862751.19607843137255
831514.80392156862750.196078431372548
841614.80392156862751.19607843137255
851514.80392156862750.196078431372548
861414.8039215686275-0.803921568627452
871514.80392156862750.196078431372548
881414.8039215686275-0.803921568627452
891313.5238095238095-0.523809523809524
90710.8888888888889-3.88888888888889
911714.80392156862752.19607843137255
921313.5238095238095-0.523809523809524
931514.80392156862750.196078431372548
941413.52380952380950.476190476190476
951314.8039215686275-1.80392156862745
961614.80392156862751.19607843137255
971213.5238095238095-1.52380952380952
981414.8039215686275-0.803921568627452
991714.80392156862752.19607843137255
1001514.80392156862750.196078431372548
1011714.80392156862752.19607843137255
1021213.5238095238095-1.52380952380952
1031614.80392156862751.19607843137255
1041114.8039215686275-3.80392156862745
1051513.52380952380951.47619047619048
106910.8888888888889-1.88888888888889
1071614.80392156862751.19607843137255
1081513.52380952380951.47619047619048
1091013.5238095238095-3.52380952380952
1101010.8888888888889-0.888888888888889
1111513.52380952380951.47619047619048
1121113.5238095238095-2.52380952380952
1131314.8039215686275-1.80392156862745
1141413.52380952380950.476190476190476
1151814.80392156862753.19607843137255
1161614.80392156862751.19607843137255
1171413.52380952380950.476190476190476
1181414.8039215686275-0.803921568627452
1191414.8039215686275-0.803921568627452
1201413.52380952380950.476190476190476
1211213.5238095238095-1.52380952380952
1221413.52380952380950.476190476190476
1231514.80392156862750.196078431372548
1241514.80392156862750.196078431372548
1251514.80392156862750.196078431372548
1261314.8039215686275-1.80392156862745
1271714.80392156862752.19607843137255
1281714.80392156862752.19607843137255
1291914.80392156862754.19607843137255
1301514.80392156862750.196078431372548
1311314.8039215686275-1.80392156862745
132910.8888888888889-1.88888888888889
1331514.80392156862750.196078431372548
1341513.52380952380951.47619047619048
1351514.80392156862750.196078431372548
1361613.52380952380952.47619047619048
1371110.88888888888890.111111111111111
1381413.52380952380950.476190476190476
1391113.5238095238095-2.52380952380952
1401514.80392156862750.196078431372548
1411314.8039215686275-1.80392156862745
1421514.80392156862750.196078431372548
1431613.52380952380952.47619047619048
1441414.8039215686275-0.803921568627452
1451514.80392156862750.196078431372548
1461614.80392156862751.19607843137255
1471614.80392156862751.19607843137255
1481114.8039215686275-3.80392156862745
1491214.8039215686275-2.80392156862745
150910.8888888888889-1.88888888888889
1511614.80392156862751.19607843137255
1521310.88888888888892.11111111111111
1531614.80392156862751.19607843137255
1541214.8039215686275-2.80392156862745
155910.8888888888889-1.88888888888889
1561310.88888888888892.11111111111111
1571313.5238095238095-0.523809523809524
1581413.52380952380950.476190476190476
1591914.80392156862754.19607843137255
1601314.8039215686275-1.80392156862745
1611210.88888888888891.11111111111111
1621313.5238095238095-0.523809523809524

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
2 & 18 & 14.8039215686275 & 3.19607843137255 \tabularnewline
3 & 11 & 13.5238095238095 & -2.52380952380952 \tabularnewline
4 & 12 & 14.8039215686275 & -2.80392156862745 \tabularnewline
5 & 16 & 10.8888888888889 & 5.11111111111111 \tabularnewline
6 & 18 & 14.8039215686275 & 3.19607843137255 \tabularnewline
7 & 14 & 10.8888888888889 & 3.11111111111111 \tabularnewline
8 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
9 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
10 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
11 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
12 & 19 & 14.8039215686275 & 4.19607843137255 \tabularnewline
13 & 10 & 13.5238095238095 & -3.52380952380952 \tabularnewline
14 & 16 & 13.5238095238095 & 2.47619047619048 \tabularnewline
15 & 18 & 14.8039215686275 & 3.19607843137255 \tabularnewline
16 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
17 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
18 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
19 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
20 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
21 & 18 & 14.8039215686275 & 3.19607843137255 \tabularnewline
22 & 11 & 13.5238095238095 & -2.52380952380952 \tabularnewline
23 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
24 & 12 & 13.5238095238095 & -1.52380952380952 \tabularnewline
25 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
26 & 9 & 14.8039215686275 & -5.80392156862745 \tabularnewline
27 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
28 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
29 & 15 & 13.5238095238095 & 1.47619047619048 \tabularnewline
30 & 11 & 14.8039215686275 & -3.80392156862745 \tabularnewline
31 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
32 & 13 & 13.5238095238095 & -0.523809523809524 \tabularnewline
33 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
34 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
35 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
36 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
37 & 9 & 10.8888888888889 & -1.88888888888889 \tabularnewline
38 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
39 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
40 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
41 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
42 & 16 & 13.5238095238095 & 2.47619047619048 \tabularnewline
43 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
44 & 12 & 13.5238095238095 & -1.52380952380952 \tabularnewline
45 & 12 & 14.8039215686275 & -2.80392156862745 \tabularnewline
46 & 11 & 14.8039215686275 & -3.80392156862745 \tabularnewline
47 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
48 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
49 & 17 & 13.5238095238095 & 3.47619047619048 \tabularnewline
50 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
51 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
52 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
53 & 11 & 10.8888888888889 & 0.111111111111111 \tabularnewline
54 & 12 & 13.5238095238095 & -1.52380952380952 \tabularnewline
55 & 12 & 14.8039215686275 & -2.80392156862745 \tabularnewline
56 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
57 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
58 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
59 & 12 & 14.8039215686275 & -2.80392156862745 \tabularnewline
60 & 12 & 13.5238095238095 & -1.52380952380952 \tabularnewline
61 & 8 & 10.8888888888889 & -2.88888888888889 \tabularnewline
62 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
63 & 11 & 14.8039215686275 & -3.80392156862745 \tabularnewline
64 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
65 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
66 & 10 & 14.8039215686275 & -4.80392156862745 \tabularnewline
67 & 11 & 10.8888888888889 & 0.111111111111111 \tabularnewline
68 & 12 & 14.8039215686275 & -2.80392156862745 \tabularnewline
69 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
70 & 15 & 13.5238095238095 & 1.47619047619048 \tabularnewline
71 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
72 & 16 & 13.5238095238095 & 2.47619047619048 \tabularnewline
73 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
74 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
75 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
76 & 12 & 10.8888888888889 & 1.11111111111111 \tabularnewline
77 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
78 & 13 & 10.8888888888889 & 2.11111111111111 \tabularnewline
79 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
80 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
81 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
82 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
83 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
84 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
85 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
86 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
87 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
88 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
89 & 13 & 13.5238095238095 & -0.523809523809524 \tabularnewline
90 & 7 & 10.8888888888889 & -3.88888888888889 \tabularnewline
91 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
92 & 13 & 13.5238095238095 & -0.523809523809524 \tabularnewline
93 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
94 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
95 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
96 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
97 & 12 & 13.5238095238095 & -1.52380952380952 \tabularnewline
98 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
99 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
100 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
101 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
102 & 12 & 13.5238095238095 & -1.52380952380952 \tabularnewline
103 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
104 & 11 & 14.8039215686275 & -3.80392156862745 \tabularnewline
105 & 15 & 13.5238095238095 & 1.47619047619048 \tabularnewline
106 & 9 & 10.8888888888889 & -1.88888888888889 \tabularnewline
107 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
108 & 15 & 13.5238095238095 & 1.47619047619048 \tabularnewline
109 & 10 & 13.5238095238095 & -3.52380952380952 \tabularnewline
110 & 10 & 10.8888888888889 & -0.888888888888889 \tabularnewline
111 & 15 & 13.5238095238095 & 1.47619047619048 \tabularnewline
112 & 11 & 13.5238095238095 & -2.52380952380952 \tabularnewline
113 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
114 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
115 & 18 & 14.8039215686275 & 3.19607843137255 \tabularnewline
116 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
117 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
118 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
119 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
120 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
121 & 12 & 13.5238095238095 & -1.52380952380952 \tabularnewline
122 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
123 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
124 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
125 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
126 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
127 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
128 & 17 & 14.8039215686275 & 2.19607843137255 \tabularnewline
129 & 19 & 14.8039215686275 & 4.19607843137255 \tabularnewline
130 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
131 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
132 & 9 & 10.8888888888889 & -1.88888888888889 \tabularnewline
133 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
134 & 15 & 13.5238095238095 & 1.47619047619048 \tabularnewline
135 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
136 & 16 & 13.5238095238095 & 2.47619047619048 \tabularnewline
137 & 11 & 10.8888888888889 & 0.111111111111111 \tabularnewline
138 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
139 & 11 & 13.5238095238095 & -2.52380952380952 \tabularnewline
140 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
141 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
142 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
143 & 16 & 13.5238095238095 & 2.47619047619048 \tabularnewline
144 & 14 & 14.8039215686275 & -0.803921568627452 \tabularnewline
145 & 15 & 14.8039215686275 & 0.196078431372548 \tabularnewline
146 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
147 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
148 & 11 & 14.8039215686275 & -3.80392156862745 \tabularnewline
149 & 12 & 14.8039215686275 & -2.80392156862745 \tabularnewline
150 & 9 & 10.8888888888889 & -1.88888888888889 \tabularnewline
151 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
152 & 13 & 10.8888888888889 & 2.11111111111111 \tabularnewline
153 & 16 & 14.8039215686275 & 1.19607843137255 \tabularnewline
154 & 12 & 14.8039215686275 & -2.80392156862745 \tabularnewline
155 & 9 & 10.8888888888889 & -1.88888888888889 \tabularnewline
156 & 13 & 10.8888888888889 & 2.11111111111111 \tabularnewline
157 & 13 & 13.5238095238095 & -0.523809523809524 \tabularnewline
158 & 14 & 13.5238095238095 & 0.476190476190476 \tabularnewline
159 & 19 & 14.8039215686275 & 4.19607843137255 \tabularnewline
160 & 13 & 14.8039215686275 & -1.80392156862745 \tabularnewline
161 & 12 & 10.8888888888889 & 1.11111111111111 \tabularnewline
162 & 13 & 13.5238095238095 & -0.523809523809524 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197253&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]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]14.8039215686275[/C][C]3.19607843137255[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.5238095238095[/C][C]-2.52380952380952[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.8039215686275[/C][C]-2.80392156862745[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]10.8888888888889[/C][C]5.11111111111111[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.8039215686275[/C][C]3.19607843137255[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.8888888888889[/C][C]3.11111111111111[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]14.8039215686275[/C][C]4.19607843137255[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.5238095238095[/C][C]-3.52380952380952[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.5238095238095[/C][C]2.47619047619048[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]14.8039215686275[/C][C]3.19607843137255[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]14.8039215686275[/C][C]3.19607843137255[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.5238095238095[/C][C]-2.52380952380952[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.5238095238095[/C][C]-1.52380952380952[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]14.8039215686275[/C][C]-5.80392156862745[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.5238095238095[/C][C]1.47619047619048[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.8039215686275[/C][C]-3.80392156862745[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.5238095238095[/C][C]-0.523809523809524[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.8888888888889[/C][C]-1.88888888888889[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.5238095238095[/C][C]2.47619047619048[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.5238095238095[/C][C]-1.52380952380952[/C][/ROW]
[ROW][C]45[/C][C]12[/C][C]14.8039215686275[/C][C]-2.80392156862745[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]14.8039215686275[/C][C]-3.80392156862745[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.5238095238095[/C][C]3.47619047619048[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]10.8888888888889[/C][C]0.111111111111111[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.5238095238095[/C][C]-1.52380952380952[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.8039215686275[/C][C]-2.80392156862745[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]14.8039215686275[/C][C]-2.80392156862745[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.5238095238095[/C][C]-1.52380952380952[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.8888888888889[/C][C]-2.88888888888889[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.8039215686275[/C][C]-3.80392156862745[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]14.8039215686275[/C][C]-4.80392156862745[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]10.8888888888889[/C][C]0.111111111111111[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.8039215686275[/C][C]-2.80392156862745[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.5238095238095[/C][C]1.47619047619048[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]13.5238095238095[/C][C]2.47619047619048[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]10.8888888888889[/C][C]1.11111111111111[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]10.8888888888889[/C][C]2.11111111111111[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]84[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]85[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]87[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]88[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]89[/C][C]13[/C][C]13.5238095238095[/C][C]-0.523809523809524[/C][/ROW]
[ROW][C]90[/C][C]7[/C][C]10.8888888888889[/C][C]-3.88888888888889[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]13.5238095238095[/C][C]-0.523809523809524[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]94[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]95[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]97[/C][C]12[/C][C]13.5238095238095[/C][C]-1.52380952380952[/C][/ROW]
[ROW][C]98[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]99[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]100[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]101[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]13.5238095238095[/C][C]-1.52380952380952[/C][/ROW]
[ROW][C]103[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]14.8039215686275[/C][C]-3.80392156862745[/C][/ROW]
[ROW][C]105[/C][C]15[/C][C]13.5238095238095[/C][C]1.47619047619048[/C][/ROW]
[ROW][C]106[/C][C]9[/C][C]10.8888888888889[/C][C]-1.88888888888889[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]13.5238095238095[/C][C]1.47619047619048[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]13.5238095238095[/C][C]-3.52380952380952[/C][/ROW]
[ROW][C]110[/C][C]10[/C][C]10.8888888888889[/C][C]-0.888888888888889[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]13.5238095238095[/C][C]1.47619047619048[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]13.5238095238095[/C][C]-2.52380952380952[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]114[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]14.8039215686275[/C][C]3.19607843137255[/C][/ROW]
[ROW][C]116[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]120[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]121[/C][C]12[/C][C]13.5238095238095[/C][C]-1.52380952380952[/C][/ROW]
[ROW][C]122[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]126[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]128[/C][C]17[/C][C]14.8039215686275[/C][C]2.19607843137255[/C][/ROW]
[ROW][C]129[/C][C]19[/C][C]14.8039215686275[/C][C]4.19607843137255[/C][/ROW]
[ROW][C]130[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]131[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]132[/C][C]9[/C][C]10.8888888888889[/C][C]-1.88888888888889[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]13.5238095238095[/C][C]1.47619047619048[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]136[/C][C]16[/C][C]13.5238095238095[/C][C]2.47619047619048[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]10.8888888888889[/C][C]0.111111111111111[/C][/ROW]
[ROW][C]138[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.5238095238095[/C][C]-2.52380952380952[/C][/ROW]
[ROW][C]140[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]141[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]143[/C][C]16[/C][C]13.5238095238095[/C][C]2.47619047619048[/C][/ROW]
[ROW][C]144[/C][C]14[/C][C]14.8039215686275[/C][C]-0.803921568627452[/C][/ROW]
[ROW][C]145[/C][C]15[/C][C]14.8039215686275[/C][C]0.196078431372548[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]147[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.8039215686275[/C][C]-3.80392156862745[/C][/ROW]
[ROW][C]149[/C][C]12[/C][C]14.8039215686275[/C][C]-2.80392156862745[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]10.8888888888889[/C][C]-1.88888888888889[/C][/ROW]
[ROW][C]151[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]152[/C][C]13[/C][C]10.8888888888889[/C][C]2.11111111111111[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]14.8039215686275[/C][C]1.19607843137255[/C][/ROW]
[ROW][C]154[/C][C]12[/C][C]14.8039215686275[/C][C]-2.80392156862745[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]10.8888888888889[/C][C]-1.88888888888889[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]10.8888888888889[/C][C]2.11111111111111[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]13.5238095238095[/C][C]-0.523809523809524[/C][/ROW]
[ROW][C]158[/C][C]14[/C][C]13.5238095238095[/C][C]0.476190476190476[/C][/ROW]
[ROW][C]159[/C][C]19[/C][C]14.8039215686275[/C][C]4.19607843137255[/C][/ROW]
[ROW][C]160[/C][C]13[/C][C]14.8039215686275[/C][C]-1.80392156862745[/C][/ROW]
[ROW][C]161[/C][C]12[/C][C]10.8888888888889[/C][C]1.11111111111111[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]13.5238095238095[/C][C]-0.523809523809524[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197253&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197253&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
#ActualsForecastsResiduals
11414.8039215686275-0.803921568627452
21814.80392156862753.19607843137255
31113.5238095238095-2.52380952380952
41214.8039215686275-2.80392156862745
51610.88888888888895.11111111111111
61814.80392156862753.19607843137255
71410.88888888888893.11111111111111
81414.8039215686275-0.803921568627452
91514.80392156862750.196078431372548
101514.80392156862750.196078431372548
111714.80392156862752.19607843137255
121914.80392156862754.19607843137255
131013.5238095238095-3.52380952380952
141613.52380952380952.47619047619048
151814.80392156862753.19607843137255
161413.52380952380950.476190476190476
171413.52380952380950.476190476190476
181714.80392156862752.19607843137255
191414.8039215686275-0.803921568627452
201614.80392156862751.19607843137255
211814.80392156862753.19607843137255
221113.5238095238095-2.52380952380952
231414.8039215686275-0.803921568627452
241213.5238095238095-1.52380952380952
251714.80392156862752.19607843137255
26914.8039215686275-5.80392156862745
271614.80392156862751.19607843137255
281413.52380952380950.476190476190476
291513.52380952380951.47619047619048
301114.8039215686275-3.80392156862745
311614.80392156862751.19607843137255
321313.5238095238095-0.523809523809524
331714.80392156862752.19607843137255
341514.80392156862750.196078431372548
351414.8039215686275-0.803921568627452
361614.80392156862751.19607843137255
37910.8888888888889-1.88888888888889
381514.80392156862750.196078431372548
391714.80392156862752.19607843137255
401314.8039215686275-1.80392156862745
411514.80392156862750.196078431372548
421613.52380952380952.47619047619048
431614.80392156862751.19607843137255
441213.5238095238095-1.52380952380952
451214.8039215686275-2.80392156862745
461114.8039215686275-3.80392156862745
471514.80392156862750.196078431372548
481514.80392156862750.196078431372548
491713.52380952380953.47619047619048
501314.8039215686275-1.80392156862745
511614.80392156862751.19607843137255
521413.52380952380950.476190476190476
531110.88888888888890.111111111111111
541213.5238095238095-1.52380952380952
551214.8039215686275-2.80392156862745
561514.80392156862750.196078431372548
571614.80392156862751.19607843137255
581514.80392156862750.196078431372548
591214.8039215686275-2.80392156862745
601213.5238095238095-1.52380952380952
61810.8888888888889-2.88888888888889
621314.8039215686275-1.80392156862745
631114.8039215686275-3.80392156862745
641413.52380952380950.476190476190476
651514.80392156862750.196078431372548
661014.8039215686275-4.80392156862745
671110.88888888888890.111111111111111
681214.8039215686275-2.80392156862745
691514.80392156862750.196078431372548
701513.52380952380951.47619047619048
711414.8039215686275-0.803921568627452
721613.52380952380952.47619047619048
731514.80392156862750.196078431372548
741514.80392156862750.196078431372548
751314.8039215686275-1.80392156862745
761210.88888888888891.11111111111111
771714.80392156862752.19607843137255
781310.88888888888892.11111111111111
791514.80392156862750.196078431372548
801314.8039215686275-1.80392156862745
811514.80392156862750.196078431372548
821614.80392156862751.19607843137255
831514.80392156862750.196078431372548
841614.80392156862751.19607843137255
851514.80392156862750.196078431372548
861414.8039215686275-0.803921568627452
871514.80392156862750.196078431372548
881414.8039215686275-0.803921568627452
891313.5238095238095-0.523809523809524
90710.8888888888889-3.88888888888889
911714.80392156862752.19607843137255
921313.5238095238095-0.523809523809524
931514.80392156862750.196078431372548
941413.52380952380950.476190476190476
951314.8039215686275-1.80392156862745
961614.80392156862751.19607843137255
971213.5238095238095-1.52380952380952
981414.8039215686275-0.803921568627452
991714.80392156862752.19607843137255
1001514.80392156862750.196078431372548
1011714.80392156862752.19607843137255
1021213.5238095238095-1.52380952380952
1031614.80392156862751.19607843137255
1041114.8039215686275-3.80392156862745
1051513.52380952380951.47619047619048
106910.8888888888889-1.88888888888889
1071614.80392156862751.19607843137255
1081513.52380952380951.47619047619048
1091013.5238095238095-3.52380952380952
1101010.8888888888889-0.888888888888889
1111513.52380952380951.47619047619048
1121113.5238095238095-2.52380952380952
1131314.8039215686275-1.80392156862745
1141413.52380952380950.476190476190476
1151814.80392156862753.19607843137255
1161614.80392156862751.19607843137255
1171413.52380952380950.476190476190476
1181414.8039215686275-0.803921568627452
1191414.8039215686275-0.803921568627452
1201413.52380952380950.476190476190476
1211213.5238095238095-1.52380952380952
1221413.52380952380950.476190476190476
1231514.80392156862750.196078431372548
1241514.80392156862750.196078431372548
1251514.80392156862750.196078431372548
1261314.8039215686275-1.80392156862745
1271714.80392156862752.19607843137255
1281714.80392156862752.19607843137255
1291914.80392156862754.19607843137255
1301514.80392156862750.196078431372548
1311314.8039215686275-1.80392156862745
132910.8888888888889-1.88888888888889
1331514.80392156862750.196078431372548
1341513.52380952380951.47619047619048
1351514.80392156862750.196078431372548
1361613.52380952380952.47619047619048
1371110.88888888888890.111111111111111
1381413.52380952380950.476190476190476
1391113.5238095238095-2.52380952380952
1401514.80392156862750.196078431372548
1411314.8039215686275-1.80392156862745
1421514.80392156862750.196078431372548
1431613.52380952380952.47619047619048
1441414.8039215686275-0.803921568627452
1451514.80392156862750.196078431372548
1461614.80392156862751.19607843137255
1471614.80392156862751.19607843137255
1481114.8039215686275-3.80392156862745
1491214.8039215686275-2.80392156862745
150910.8888888888889-1.88888888888889
1511614.80392156862751.19607843137255
1521310.88888888888892.11111111111111
1531614.80392156862751.19607843137255
1541214.8039215686275-2.80392156862745
155910.8888888888889-1.88888888888889
1561310.88888888888892.11111111111111
1571313.5238095238095-0.523809523809524
1581413.52380952380950.476190476190476
1591914.80392156862754.19607843137255
1601314.8039215686275-1.80392156862745
1611210.88888888888891.11111111111111
1621313.5238095238095-0.523809523809524



Parameters (Session):
par1 = 7 ; par2 = none ; par3 = 3 ; par4 = no ;
Parameters (R input):
par1 = 7 ; 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')
}