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Author

*The author of this computation has been verified*

R Software Module

rwasp_regression_trees1.wasp

Title produced by software

Recursive Partitioning (Regression Trees)

Date of computation

Thu, 22 Dec 2011 05:43:02 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/22/t132455062159sy01rm5qcoglh.htm/, Retrieved Fri, 03 May 2024 08:55:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159282, Retrieved Fri, 03 May 2024 08:55:44 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

102

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 20:13:50] [b98453cac15ba1066b407e146608df68]
-   P   [Recursive Partitioning (Regression Trees)] [WS 10 RP met cate...] [2011-12-15 21:05:06] [3dd791303389e75e672968b227170a72]
-   PD      [Recursive Partitioning (Regression Trees)] [Paper Regression ...] [2011-12-22 10:43:02] [ef8d8c90df4ff8d053d0205bd6ba250c] [Current]

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Dataseries X:

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Histogram

Boxplots

4	30	115	79	1
NA	28	109	58	1
1	38	146	60	0
NA	30	116	108	NA
NA	22	68	49	NA
NA	26	101	0	NA
3	25	96	121	1
NA	18	67	1	NA
NA	11	44	20	NA
3	26	100	43	1
4	25	93	69	0
4	38	140	78	0
NA	44	166	86	NA
3	30	99	44	0
NA	40	139	104	NA
NA	34	130	63	NA
2	47	181	158	0
4	30	116	102	1
4	31	116	77	0
NA	23	88	82	1
NA	36	139	115	NA
4	36	135	101	1
5	30	108	80	0
NA	25	89	50	1
NA	39	156	83	NA
4	34	129	123	0
4	31	118	73	0
5	31	118	81	1
4	33	125	105	0
4	25	95	47	0
NA	33	126	105	NA
2	35	135	94	1
3	42	154	44	1
NA	43	165	114	NA
NA	30	113	38	NA
4	33	127	107	1
NA	13	52	30	NA
NA	32	121	71	NA
2	36	136	84	0
4	0	0	0	0
NA	28	108	59	NA
2	14	46	33	1
4	17	54	42	1
4	32	124	96	0
NA	30	115	106	NA
4	35	128	56	1
3	20	80	57	0
4	28	97	59	1
5	28	104	39	0
NA	39	59	34	NA
4	34	125	76	0
NA	26	82	20	NA
5	39	149	91	1
NA	39	149	115	NA
NA	33	122	85	NA
NA	28	118	76	0
NA	4	12	8	0
2	39	144	79	0
NA	18	67	21	NA
NA	14	52	30	NA
3	29	108	76	0
4	44	166	101	0
3	21	80	94	0
4	16	60	27	1
NA	28	107	92	NA
4	35	127	123	0
NA	28	107	75	NA
NA	38	146	128	NA
NA	23	84	105	1
NA	36	141	55	NA
NA	32	123	56	NA
4	29	111	41	0
NA	25	98	72	0
5	27	105	67	1
NA	36	135	75	0
4	28	107	114	1
NA	23	85	118	NA
NA	40	155	77	NA
2	23	88	22	0
NA	40	155	66	NA
4	28	104	69	1
4	34	132	105	1
NA	33	127	116	NA
4	28	108	88	1
NA	34	129	73	0
NA	30	116	99	NA
4	33	122	62	0
NA	22	85	53	NA
4	38	147	118	0
NA	26	99	30	NA
4	35	87	100	0
NA	8	28	49	NA
2	24	90	24	0
2	29	109	67	1
4	20	78	46	0
3	29	111	57	0
NA	45	158	75	NA
4	37	141	135	0
NA	33	122	68	NA
2	33	124	124	1
3	25	93	33	0
2	32	124	98	0
4	29	112	58	0
4	28	108	68	0
NA	28	99	81	NA
4	31	117	131	0
3	52	199	110	1
4	21	78	37	0
NA	24	91	130	1
2	41	158	93	1
5	33	126	118	0
NA	32	122	39	1
NA	19	71	13	NA
NA	20	75	74	NA
4	31	115	81	0
NA	31	119	109	NA
NA	32	124	151	NA
4	18	72	51	0
2	23	91	28	1
4	17	45	40	0
4	20	78	56	0
2	12	39	27	0
NA	17	68	37	NA
4	30	119	83	0
NA	31	117	54	NA
NA	10	39	27	NA
3	13	50	28	1
5	22	88	59	0
4	42	155	133	0
2	1	0	12	0
NA	9	36	0	NA
4	32	123	106	0
NA	11	32	23	NA
4	25	99	44	1
4	36	136	71	0
4	31	117	116	1
NA	0	0	4	0
NA	24	88	62	0
2	13	39	12	1
NA	8	25	18	1
4	13	52	14	0
4	19	75	60	0
NA	18	71	7	NA
4	33	124	98	0
NA	40	151	64	NA
NA	22	71	29	NA
3	38	145	32	1
2	24	87	25	1
NA	8	27	16	NA
NA	35	131	48	NA
4	43	162	100	0
3	43	165	46	NA
4	14	54	45	0
5	41	159	129	1
NA	38	147	130	NA
4	45	170	136	0
NA	31	119	59	1
NA	13	49	25	NA
NA	28	104	32	NA
4	31	120	63	0
NA	40	150	95	NA
NA	30	112	14	0
4	16	59	36	1
4	37	136	113	1
4	30	107	47	1
2	35	130	92	1
NA	32	115	70	NA
NA	27	107	19	NA
2	20	75	50	1
3	18	71	41	0
NA	31	120	91	0
1	31	116	111	1
3	21	79	41	0
3	39	150	120	1
NA	41	156	135	NA
NA	13	51	27	NA
NA	32	118	87	NA
3	18	71	25	0
4	39	144	131	1
2	14	47	45	1
4	7	28	29	0
3	17	68	58	1
NA	0	0	4	NA
4	30	110	47	0
4	37	147	109	0
NA	0	0	7	NA
NA	5	15	12	NA
NA	1	4	0	NA
NA	16	64	37	NA
2	32	111	37	0
NA	24	85	46	NA
4	17	68	15	1
NA	11	40	42	NA
4	24	80	7	1
4	22	88	54	0
4	12	48	54	1
4	19	76	14	0
3	13	51	16	0
NA	17	67	33	NA
NA	15	59	32	0
NA	16	61	21	NA
NA	24	76	15	NA
2	15	60	38	1
5	17	68	22	1
NA	18	71	28	NA
NA	20	76	10	NA
NA	16	62	31	NA
4	16	61	32	0
4	18	67	32	0
NA	22	88	43	NA
NA	8	30	27	NA
2	17	64	37	1
NA	18	68	20	NA
3	16	64	32	1
3	23	91	0	1
4	22	88	5	1
NA	13	52	26	NA
3	13	49	10	0
NA	16	62	27	0
NA	16	61	11	NA
2	20	76	29	0
5	22	88	25	0
4	17	66	55	1
NA	18	71	23	NA
NA	17	68	5	0
NA	12	48	43	1
NA	7	25	23	NA
4	17	68	34	0
NA	14	41	36	NA
5	23	90	35	0
4	17	66	0	1
4	14	54	37	0
NA	15	59	28	NA
NA	17	60	16	NA
4	21	77	26	0
2	18	68	38	0
2	18	72	23	0
NA	17	67	22	NA
4	17	64	30	0
NA	16	63	16	NA
NA	15	59	18	0
NA	21	84	28	0
NA	16	64	32	NA
2	14	56	21	1
NA	15	54	23	NA
NA	17	67	29	NA
4	15	58	50	1
2	15	59	12	0
NA	10	40	21	NA
NA	6	22	18	NA
4	22	83	27	0
4	21	81	41	0
NA	1	2	13	NA
4	18	72	12	1
4	17	61	21	1
4	4	15	8	1
5	10	32	26	0
NA	16	62	27	0
NA	16	58	13	NA
NA	9	36	16	NA
NA	16	59	2	NA
NA	17	68	42	NA
NA	7	21	5	NA
4	15	55	37	NA
NA	14	54	17	NA
NA	14	55	38	NA
4	18	72	37	1
2	12	41	29	1
2	16	61	32	1
NA	21	67	35	1
NA	19	76	17	NA
NA	16	64	20	NA
NA	1	3	7	NA
NA	16	63	46	NA
NA	10	40	24	NA
NA	19	69	40	NA
NA	12	48	3	NA
NA	2	8	10	0
NA	14	52	37	NA
4	17	66	17	1
NA	19	76	28	NA
NA	14	43	19	NA
NA	11	39	29	NA
NA	4	14	8	NA
2	16	61	10	0
NA	20	71	15	NA
NA	12	44	15	NA
NA	15	60	28	NA
NA	16	64	17	0

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'AstonUniversity' @ aston.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 & 3 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159282&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159282&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159282&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'AstonUniversity' @ aston.wessa.net

Goodness of Fit
Correlation	NA
R-squared	NA
RMSE	0.9501

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & NA \tabularnewline
R-squared & NA \tabularnewline
RMSE & 0.9501 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159282&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]0.9501[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159282&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159282&T=1

As an alternative you can also use a QR Code:

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

Goodness of Fit
Correlation	NA
R-squared	NA
RMSE	0.9501

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	4	3.48299319727891	0.517006802721089
2	1	3.48299319727891	-2.48299319727891
3	3	3.48299319727891	-0.482993197278911
4	3	3.48299319727891	-0.482993197278911
5	4	3.48299319727891	0.517006802721089
6	4	3.48299319727891	0.517006802721089
7	3	3.48299319727891	-0.482993197278911
8	2	3.48299319727891	-1.48299319727891
9	4	3.48299319727891	0.517006802721089
10	4	3.48299319727891	0.517006802721089
11	4	3.48299319727891	0.517006802721089
12	5	3.48299319727891	1.51700680272109
13	4	3.48299319727891	0.517006802721089
14	4	3.48299319727891	0.517006802721089
15	5	3.48299319727891	1.51700680272109
16	4	3.48299319727891	0.517006802721089
17	4	3.48299319727891	0.517006802721089
18	2	3.48299319727891	-1.48299319727891
19	3	3.48299319727891	-0.482993197278911
20	4	3.48299319727891	0.517006802721089
21	2	3.48299319727891	-1.48299319727891
22	4	3.48299319727891	0.517006802721089
23	2	3.48299319727891	-1.48299319727891
24	4	3.48299319727891	0.517006802721089
25	4	3.48299319727891	0.517006802721089
26	4	3.48299319727891	0.517006802721089
27	3	3.48299319727891	-0.482993197278911
28	4	3.48299319727891	0.517006802721089
29	5	3.48299319727891	1.51700680272109
30	4	3.48299319727891	0.517006802721089
31	5	3.48299319727891	1.51700680272109
32	2	3.48299319727891	-1.48299319727891
33	3	3.48299319727891	-0.482993197278911
34	4	3.48299319727891	0.517006802721089
35	3	3.48299319727891	-0.482993197278911
36	4	3.48299319727891	0.517006802721089
37	4	3.48299319727891	0.517006802721089
38	4	3.48299319727891	0.517006802721089
39	5	3.48299319727891	1.51700680272109
40	4	3.48299319727891	0.517006802721089
41	2	3.48299319727891	-1.48299319727891
42	4	3.48299319727891	0.517006802721089
43	4	3.48299319727891	0.517006802721089
44	4	3.48299319727891	0.517006802721089
45	4	3.48299319727891	0.517006802721089
46	4	3.48299319727891	0.517006802721089
47	4	3.48299319727891	0.517006802721089
48	2	3.48299319727891	-1.48299319727891
49	2	3.48299319727891	-1.48299319727891
50	4	3.48299319727891	0.517006802721089
51	3	3.48299319727891	-0.482993197278911
52	4	3.48299319727891	0.517006802721089
53	2	3.48299319727891	-1.48299319727891
54	3	3.48299319727891	-0.482993197278911
55	2	3.48299319727891	-1.48299319727891
56	4	3.48299319727891	0.517006802721089
57	4	3.48299319727891	0.517006802721089
58	4	3.48299319727891	0.517006802721089
59	3	3.48299319727891	-0.482993197278911
60	4	3.48299319727891	0.517006802721089
61	2	3.48299319727891	-1.48299319727891
62	5	3.48299319727891	1.51700680272109
63	4	3.48299319727891	0.517006802721089
64	4	3.48299319727891	0.517006802721089
65	2	3.48299319727891	-1.48299319727891
66	4	3.48299319727891	0.517006802721089
67	4	3.48299319727891	0.517006802721089
68	2	3.48299319727891	-1.48299319727891
69	4	3.48299319727891	0.517006802721089
70	3	3.48299319727891	-0.482993197278911
71	5	3.48299319727891	1.51700680272109
72	4	3.48299319727891	0.517006802721089
73	2	3.48299319727891	-1.48299319727891
74	4	3.48299319727891	0.517006802721089
75	4	3.48299319727891	0.517006802721089
76	4	3.48299319727891	0.517006802721089
77	4	3.48299319727891	0.517006802721089
78	2	3.48299319727891	-1.48299319727891
79	4	3.48299319727891	0.517006802721089
80	4	3.48299319727891	0.517006802721089
81	4	3.48299319727891	0.517006802721089
82	3	3.48299319727891	-0.482993197278911
83	2	3.48299319727891	-1.48299319727891
84	4	3.48299319727891	0.517006802721089
85	3	3.48299319727891	-0.482993197278911
86	4	3.48299319727891	0.517006802721089
87	5	3.48299319727891	1.51700680272109
88	4	3.48299319727891	0.517006802721089
89	4	3.48299319727891	0.517006802721089
90	4	3.48299319727891	0.517006802721089
91	4	3.48299319727891	0.517006802721089
92	4	3.48299319727891	0.517006802721089
93	2	3.48299319727891	-1.48299319727891
94	2	3.48299319727891	-1.48299319727891
95	3	3.48299319727891	-0.482993197278911
96	1	3.48299319727891	-2.48299319727891
97	3	3.48299319727891	-0.482993197278911
98	3	3.48299319727891	-0.482993197278911
99	3	3.48299319727891	-0.482993197278911
100	4	3.48299319727891	0.517006802721089
101	2	3.48299319727891	-1.48299319727891
102	4	3.48299319727891	0.517006802721089
103	3	3.48299319727891	-0.482993197278911
104	4	3.48299319727891	0.517006802721089
105	4	3.48299319727891	0.517006802721089
106	2	3.48299319727891	-1.48299319727891
107	4	3.48299319727891	0.517006802721089
108	4	3.48299319727891	0.517006802721089
109	4	3.48299319727891	0.517006802721089
110	4	3.48299319727891	0.517006802721089
111	4	3.48299319727891	0.517006802721089
112	3	3.48299319727891	-0.482993197278911
113	2	3.48299319727891	-1.48299319727891
114	5	3.48299319727891	1.51700680272109
115	4	3.48299319727891	0.517006802721089
116	4	3.48299319727891	0.517006802721089
117	2	3.48299319727891	-1.48299319727891
118	3	3.48299319727891	-0.482993197278911
119	3	3.48299319727891	-0.482993197278911
120	4	3.48299319727891	0.517006802721089
121	3	3.48299319727891	-0.482993197278911
122	2	3.48299319727891	-1.48299319727891
123	5	3.48299319727891	1.51700680272109
124	4	3.48299319727891	0.517006802721089
125	4	3.48299319727891	0.517006802721089
126	5	3.48299319727891	1.51700680272109
127	4	3.48299319727891	0.517006802721089
128	4	3.48299319727891	0.517006802721089
129	4	3.48299319727891	0.517006802721089
130	2	3.48299319727891	-1.48299319727891
131	2	3.48299319727891	-1.48299319727891
132	4	3.48299319727891	0.517006802721089
133	2	3.48299319727891	-1.48299319727891
134	4	3.48299319727891	0.517006802721089
135	2	3.48299319727891	-1.48299319727891
136	4	3.48299319727891	0.517006802721089
137	4	3.48299319727891	0.517006802721089
138	4	3.48299319727891	0.517006802721089
139	4	3.48299319727891	0.517006802721089
140	4	3.48299319727891	0.517006802721089
141	5	3.48299319727891	1.51700680272109
142	4	3.48299319727891	0.517006802721089
143	4	3.48299319727891	0.517006802721089
144	2	3.48299319727891	-1.48299319727891
145	2	3.48299319727891	-1.48299319727891
146	4	3.48299319727891	0.517006802721089
147	2	3.48299319727891	-1.48299319727891

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
2 & 1 & 3.48299319727891 & -2.48299319727891 \tabularnewline
3 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
4 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
5 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
6 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
7 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
8 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
9 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
10 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
11 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
12 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
13 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
14 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
15 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
16 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
17 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
18 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
19 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
20 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
21 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
22 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
23 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
24 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
25 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
26 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
27 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
28 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
29 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
30 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
31 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
32 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
33 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
34 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
35 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
36 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
37 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
38 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
39 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
40 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
41 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
42 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
43 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
44 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
45 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
46 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
47 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
48 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
49 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
50 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
51 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
52 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
53 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
54 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
55 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
56 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
57 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
58 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
59 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
60 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
61 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
62 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
63 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
64 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
65 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
66 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
67 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
68 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
69 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
70 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
71 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
72 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
73 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
74 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
75 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
76 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
77 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
78 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
79 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
80 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
81 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
82 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
83 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
84 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
85 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
86 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
87 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
88 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
89 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
90 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
91 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
92 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
93 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
94 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
95 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
96 & 1 & 3.48299319727891 & -2.48299319727891 \tabularnewline
97 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
98 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
99 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
100 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
101 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
102 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
103 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
104 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
105 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
106 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
107 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
108 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
109 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
110 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
111 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
112 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
113 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
114 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
115 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
116 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
117 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
118 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
119 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
120 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
121 & 3 & 3.48299319727891 & -0.482993197278911 \tabularnewline
122 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
123 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
124 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
125 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
126 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
127 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
128 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
129 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
130 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
131 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
132 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
133 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
134 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
135 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
136 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
137 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
138 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
139 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
140 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
141 & 5 & 3.48299319727891 & 1.51700680272109 \tabularnewline
142 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
143 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
144 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
145 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
146 & 4 & 3.48299319727891 & 0.517006802721089 \tabularnewline
147 & 2 & 3.48299319727891 & -1.48299319727891 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159282&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]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]3.48299319727891[/C][C]-2.48299319727891[/C][/ROW]
[ROW][C]3[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]4[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]5[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]6[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]7[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]8[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]9[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]10[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]11[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]13[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]14[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]16[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]17[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]18[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]21[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]22[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]23[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]24[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]25[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]27[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]28[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]29[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]31[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]32[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]33[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]34[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]35[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]36[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]37[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]38[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]39[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]40[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]41[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]42[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]43[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]44[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]45[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]46[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]47[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]48[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]49[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]50[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]51[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]52[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]53[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]54[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]55[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]56[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]57[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]58[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]59[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]60[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]61[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]62[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]63[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]64[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]65[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]66[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]68[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]70[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]72[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]73[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]74[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]75[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]76[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]77[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]78[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]79[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]80[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]81[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]82[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]83[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]84[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]85[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]86[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]87[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]88[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]89[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]90[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]91[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]92[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]93[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]94[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]3.48299319727891[/C][C]-2.48299319727891[/C][/ROW]
[ROW][C]97[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]98[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]99[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]100[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]101[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]102[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]103[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]104[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]105[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]106[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]107[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]108[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]109[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]110[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]111[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]112[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]113[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]114[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]115[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]116[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]117[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]118[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]119[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]120[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]121[/C][C]3[/C][C]3.48299319727891[/C][C]-0.482993197278911[/C][/ROW]
[ROW][C]122[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]123[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]124[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]125[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]126[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]127[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]128[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]130[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]131[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]132[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]133[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]134[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]135[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]136[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]137[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]138[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]139[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]140[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]141[/C][C]5[/C][C]3.48299319727891[/C][C]1.51700680272109[/C][/ROW]
[ROW][C]142[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]143[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]144[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]145[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[ROW][C]146[/C][C]4[/C][C]3.48299319727891[/C][C]0.517006802721089[/C][/ROW]
[ROW][C]147[/C][C]2[/C][C]3.48299319727891[/C][C]-1.48299319727891[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159282&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159282&T=2

As an alternative you can also use a QR Code:

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

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	4	3.48299319727891	0.517006802721089
2	1	3.48299319727891	-2.48299319727891
3	3	3.48299319727891	-0.482993197278911
4	3	3.48299319727891	-0.482993197278911
5	4	3.48299319727891	0.517006802721089
6	4	3.48299319727891	0.517006802721089
7	3	3.48299319727891	-0.482993197278911
8	2	3.48299319727891	-1.48299319727891
9	4	3.48299319727891	0.517006802721089
10	4	3.48299319727891	0.517006802721089
11	4	3.48299319727891	0.517006802721089
12	5	3.48299319727891	1.51700680272109
13	4	3.48299319727891	0.517006802721089
14	4	3.48299319727891	0.517006802721089
15	5	3.48299319727891	1.51700680272109
16	4	3.48299319727891	0.517006802721089
17	4	3.48299319727891	0.517006802721089
18	2	3.48299319727891	-1.48299319727891
19	3	3.48299319727891	-0.482993197278911
20	4	3.48299319727891	0.517006802721089
21	2	3.48299319727891	-1.48299319727891
22	4	3.48299319727891	0.517006802721089
23	2	3.48299319727891	-1.48299319727891
24	4	3.48299319727891	0.517006802721089
25	4	3.48299319727891	0.517006802721089
26	4	3.48299319727891	0.517006802721089
27	3	3.48299319727891	-0.482993197278911
28	4	3.48299319727891	0.517006802721089
29	5	3.48299319727891	1.51700680272109
30	4	3.48299319727891	0.517006802721089
31	5	3.48299319727891	1.51700680272109
32	2	3.48299319727891	-1.48299319727891
33	3	3.48299319727891	-0.482993197278911
34	4	3.48299319727891	0.517006802721089
35	3	3.48299319727891	-0.482993197278911
36	4	3.48299319727891	0.517006802721089
37	4	3.48299319727891	0.517006802721089
38	4	3.48299319727891	0.517006802721089
39	5	3.48299319727891	1.51700680272109
40	4	3.48299319727891	0.517006802721089
41	2	3.48299319727891	-1.48299319727891
42	4	3.48299319727891	0.517006802721089
43	4	3.48299319727891	0.517006802721089
44	4	3.48299319727891	0.517006802721089
45	4	3.48299319727891	0.517006802721089
46	4	3.48299319727891	0.517006802721089
47	4	3.48299319727891	0.517006802721089
48	2	3.48299319727891	-1.48299319727891
49	2	3.48299319727891	-1.48299319727891
50	4	3.48299319727891	0.517006802721089
51	3	3.48299319727891	-0.482993197278911
52	4	3.48299319727891	0.517006802721089
53	2	3.48299319727891	-1.48299319727891
54	3	3.48299319727891	-0.482993197278911
55	2	3.48299319727891	-1.48299319727891
56	4	3.48299319727891	0.517006802721089
57	4	3.48299319727891	0.517006802721089
58	4	3.48299319727891	0.517006802721089
59	3	3.48299319727891	-0.482993197278911
60	4	3.48299319727891	0.517006802721089
61	2	3.48299319727891	-1.48299319727891
62	5	3.48299319727891	1.51700680272109
63	4	3.48299319727891	0.517006802721089
64	4	3.48299319727891	0.517006802721089
65	2	3.48299319727891	-1.48299319727891
66	4	3.48299319727891	0.517006802721089
67	4	3.48299319727891	0.517006802721089
68	2	3.48299319727891	-1.48299319727891
69	4	3.48299319727891	0.517006802721089
70	3	3.48299319727891	-0.482993197278911
71	5	3.48299319727891	1.51700680272109
72	4	3.48299319727891	0.517006802721089
73	2	3.48299319727891	-1.48299319727891
74	4	3.48299319727891	0.517006802721089
75	4	3.48299319727891	0.517006802721089
76	4	3.48299319727891	0.517006802721089
77	4	3.48299319727891	0.517006802721089
78	2	3.48299319727891	-1.48299319727891
79	4	3.48299319727891	0.517006802721089
80	4	3.48299319727891	0.517006802721089
81	4	3.48299319727891	0.517006802721089
82	3	3.48299319727891	-0.482993197278911
83	2	3.48299319727891	-1.48299319727891
84	4	3.48299319727891	0.517006802721089
85	3	3.48299319727891	-0.482993197278911
86	4	3.48299319727891	0.517006802721089
87	5	3.48299319727891	1.51700680272109
88	4	3.48299319727891	0.517006802721089
89	4	3.48299319727891	0.517006802721089
90	4	3.48299319727891	0.517006802721089
91	4	3.48299319727891	0.517006802721089
92	4	3.48299319727891	0.517006802721089
93	2	3.48299319727891	-1.48299319727891
94	2	3.48299319727891	-1.48299319727891
95	3	3.48299319727891	-0.482993197278911
96	1	3.48299319727891	-2.48299319727891
97	3	3.48299319727891	-0.482993197278911
98	3	3.48299319727891	-0.482993197278911
99	3	3.48299319727891	-0.482993197278911
100	4	3.48299319727891	0.517006802721089
101	2	3.48299319727891	-1.48299319727891
102	4	3.48299319727891	0.517006802721089
103	3	3.48299319727891	-0.482993197278911
104	4	3.48299319727891	0.517006802721089
105	4	3.48299319727891	0.517006802721089
106	2	3.48299319727891	-1.48299319727891
107	4	3.48299319727891	0.517006802721089
108	4	3.48299319727891	0.517006802721089
109	4	3.48299319727891	0.517006802721089
110	4	3.48299319727891	0.517006802721089
111	4	3.48299319727891	0.517006802721089
112	3	3.48299319727891	-0.482993197278911
113	2	3.48299319727891	-1.48299319727891
114	5	3.48299319727891	1.51700680272109
115	4	3.48299319727891	0.517006802721089
116	4	3.48299319727891	0.517006802721089
117	2	3.48299319727891	-1.48299319727891
118	3	3.48299319727891	-0.482993197278911
119	3	3.48299319727891	-0.482993197278911
120	4	3.48299319727891	0.517006802721089
121	3	3.48299319727891	-0.482993197278911
122	2	3.48299319727891	-1.48299319727891
123	5	3.48299319727891	1.51700680272109
124	4	3.48299319727891	0.517006802721089
125	4	3.48299319727891	0.517006802721089
126	5	3.48299319727891	1.51700680272109
127	4	3.48299319727891	0.517006802721089
128	4	3.48299319727891	0.517006802721089
129	4	3.48299319727891	0.517006802721089
130	2	3.48299319727891	-1.48299319727891
131	2	3.48299319727891	-1.48299319727891
132	4	3.48299319727891	0.517006802721089
133	2	3.48299319727891	-1.48299319727891
134	4	3.48299319727891	0.517006802721089
135	2	3.48299319727891	-1.48299319727891
136	4	3.48299319727891	0.517006802721089
137	4	3.48299319727891	0.517006802721089
138	4	3.48299319727891	0.517006802721089
139	4	3.48299319727891	0.517006802721089
140	4	3.48299319727891	0.517006802721089
141	5	3.48299319727891	1.51700680272109
142	4	3.48299319727891	0.517006802721089
143	4	3.48299319727891	0.517006802721089
144	2	3.48299319727891	-1.48299319727891
145	2	3.48299319727891	-1.48299319727891
146	4	3.48299319727891	0.517006802721089
147	2	3.48299319727891	-1.48299319727891

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = equal ; par3 = 2 ; par4 = no ;

Parameters (R input):

par1 = 1 ; par2 = none ; par3 = ; par4 = no ;

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

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code