Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_linear_regression.wasp
Title produced by softwareLinear Regression Graphical Model Validation
Date of computationTue, 26 Feb 2008 03:22:06 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Feb/26/t12040214435my4uqfrs09mgrk.htm/, Retrieved Thu, 28 Mar 2024 09:10:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=9091, Retrieved Thu, 28 Mar 2024 09:10:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact2295
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Linear Regression Graphical Model Validation] [Colombia Coffee -...] [2008-02-26 10:22:06] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   PD    [Linear Regression Graphical Model Validation] [Linear Regression...] [2008-12-22 14:50:39] [33f4701c7363e8b81858dafbf0350eed]
-    D      [Linear Regression Graphical Model Validation] [Linear Regression...] [2008-12-22 20:24:18] [b187fac1a1b0cb3920f54366df47fea3]
-           [Linear Regression Graphical Model Validation] [linear regression...] [2008-12-22 20:49:59] [b641c14ac36cb6fee377f3b099dcac19]
-  M D    [Linear Regression Graphical Model Validation] [WS6: Toturial ass...] [2010-11-05 10:55:30] [1fd136673b2a4fecb5c545b9b4a05d64]
-   P       [Linear Regression Graphical Model Validation] [ws6.3 tutorial] [2010-11-15 08:23:24] [e4076051fbfb461c886b1e223cd7862f]
-    D      [Linear Regression Graphical Model Validation] [Workshop 6_Tutorial] [2011-11-15 11:03:26] [f722e8e78b9e5c5ebaa2263f273aa636]
- RM        [Linear Regression Graphical Model Validation] [linear regression] [2011-11-15 14:55:12] [d31984dff2665bea309b726bae3d5241]
- RM        [Linear Regression Graphical Model Validation] [] [2011-11-15 22:01:41] [74be16979710d4c4e7c6647856088456]
-  M D    [Linear Regression Graphical Model Validation] [Scatterplot Tutorial] [2010-11-05 11:55:49] [aeb27d5c05332f2e597ad139ee63fbe4]
-    D      [Linear Regression Graphical Model Validation] [Simple Linear Reg...] [2010-11-12 11:48:01] [aeb27d5c05332f2e597ad139ee63fbe4]
-    D        [Linear Regression Graphical Model Validation] [Simple Linear Reg...] [2010-12-17 13:47:08] [aeb27d5c05332f2e597ad139ee63fbe4]
- RMPD    [Multiple Regression] [WS6: Toturial ass...] [2010-11-05 12:08:30] [1fd136673b2a4fecb5c545b9b4a05d64]
-   P       [Multiple Regression] [ws6.4 tutorial] [2010-11-15 08:32:05] [e4076051fbfb461c886b1e223cd7862f]
-   P       [Multiple Regression] [Ws 6 Tutorial Ass...] [2011-11-13 21:56:59] [74be16979710d4c4e7c6647856088456]
- R P         [Multiple Regression] [Ws 6 Tutorial Ass...] [2011-11-13 22:00:46] [74be16979710d4c4e7c6647856088456]
- RM        [Multiple Regression] [regression] [2011-11-15 15:06:25] [d31984dff2665bea309b726bae3d5241]
- RM        [Multiple Regression] [] [2011-11-15 22:07:29] [74be16979710d4c4e7c6647856088456]
- RM D    [Linear Regression Graphical Model Validation] [Regression Model 1] [2010-11-05 17:43:27] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
-   P       [Linear Regression Graphical Model Validation] [Vraag 3: Lineair ...] [2010-11-11 10:18:38] [39c51da0be01189e8a44eb69e891b7a1]
- RM        [Linear Regression Graphical Model Validation] [WS 6 - 11] [2011-11-15 14:55:02] [74be16979710d4c4e7c6647856088456]
- RM D    [Linear Regression Graphical Model Validation] [Regressiemodel 1] [2010-11-06 16:54:19] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
-   PD      [Linear Regression Graphical Model Validation] [Regressiemodel 1] [2010-11-20 19:37:29] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
-   PD      [Linear Regression Graphical Model Validation] [Regressiemodel 1] [2010-11-20 19:54:37] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- RMPD      [Univariate Data Series] [Bestedingen] [2010-12-10 12:35:43] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- RMPD      [Mean Plot] [Mean plot Schiphol] [2010-12-10 12:51:13] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
-    D      [Linear Regression Graphical Model Validation] [Regressiemodel 1] [2010-12-10 12:24:47] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- RMPD      [Spectral Analysis] [Spectral Analysis...] [2010-12-10 14:16:07] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- R           [Spectral Analysis] [Paper - Spectral ...] [2011-12-20 14:36:26] [69d59b79aaf660457acc70a0ef0bfdab]
- RMPD      [(Partial) Autocorrelation Function] [Autocorrelatiefun...] [2010-12-10 14:34:45] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- R P         [(Partial) Autocorrelation Function] [Paper - autocorre...] [2011-12-20 15:27:59] [69d59b79aaf660457acc70a0ef0bfdab]
- RMPD      [Multiple Regression] [Schiphol: MR - Mo...] [2010-12-10 14:47:34] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- R  D      [Linear Regression Graphical Model Validation] [] [2011-11-15 17:48:12] [06c08141d7d783218a8164fd2ea166f2]
-             [Linear Regression Graphical Model Validation] [] [2011-12-18 15:51:24] [06c08141d7d783218a8164fd2ea166f2]
- R P       [Linear Regression Graphical Model Validation] [] [2011-11-15 21:43:38] [ec2187f7727da5d5d939740b21b8b68a]
- R PD        [Linear Regression Graphical Model Validation] [] [2011-12-19 15:58:44] [ec2187f7727da5d5d939740b21b8b68a]
- R         [Linear Regression Graphical Model Validation] [Paper - Hypothese...] [2011-12-19 16:27:20] [69d59b79aaf660457acc70a0ef0bfdab]
F RMPD    [Chi-Squared and McNemar Tests] [WS6 - Chi kwadraa...] [2010-11-07 14:08:40] [8ef49741e164ec6343c90c7935194465]
- R         [Chi-Squared and McNemar Tests] [Workshop 6, Chi-S...] [2010-11-09 11:02:54] [8ffb4cfa64b4677df0d2c448735a40bb]
-   P         [Chi-Squared and McNemar Tests] [Workshop 6, Chi-S...] [2010-11-09 16:29:28] [8ffb4cfa64b4677df0d2c448735a40bb]
-   P           [Chi-Squared and McNemar Tests] [Workshop 6, Chi-S...] [2010-11-09 16:32:35] [8ffb4cfa64b4677df0d2c448735a40bb]
-   P           [Chi-Squared and McNemar Tests] [Workshop 6, Chi-S...] [2010-11-09 16:41:58] [8ffb4cfa64b4677df0d2c448735a40bb]
F             [Chi-Squared and McNemar Tests] [WS6 Hap-Con] [2010-11-11 17:20:45] [afe9379cca749d06b3d6872e02cc47ed]
-               [Chi-Squared and McNemar Tests] [] [2010-11-15 17:01:17] [b64b273f7a25c5bb07ff2f026b8ce952]
- R  D          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [ws 6 - 1.3] [2011-11-14 20:51:16] [4b648d52023f19d55c572f0eddd72b1f]
- R PD          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [ws 6 - 1.2] [2011-11-14 20:52:27] [4b648d52023f19d55c572f0eddd72b1f]
- R PD          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [ws 6 - 1.1] [2011-11-14 20:53:08] [4b648d52023f19d55c572f0eddd72b1f]
- R PD          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [ws 6 - 1.4] [2011-11-14 20:54:13] [4b648d52023f19d55c572f0eddd72b1f]
- R PD          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [ws 6 - 1.5] [2011-11-14 20:55:43] [4b648d52023f19d55c572f0eddd72b1f]

[Truncated]
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Dataseries X:
87.28
87.28
87.09
86.92
87.59
90.72
90.69
90.3
89.55
88.94
88.41
87.82
87.07
86.82
86.4
86.02
85.66
85.32
85
84.67
83.94
82.83
81.95
81.19
80.48
78.86
69.47
68.77
70.06
73.95
75.8
77.79
81.57
83.07
84.34
85.1
85.25
84.26
83.63
86.44
85.3
84.1
83.36
82.48
81.58
80.47
79.34
82.13
81.69
80.7
79.88
79.16
78.38
77.42
76.47
75.46
74.48
78.27
80.7
79.91
78.75
77.78
81.14
81.08
80.03
78.91
78.01
76.9
75.97
81.93
80.27
78.67
77.42
76.16
74.7
76.39
76.04
74.65
73.29
71.79
74.39
74.91
74.54
73.08
72.75
71.32
70.38
70.35
70.01
69.36
67.77
69.26
69.8
68.38
67.62
68.39
66.95
65.21
66.64
63.45
60.66
62.34
60.32
58.64
60.46
58.59
61.87
61.85
67.44
77.06
91.74
93.15
94.15
93.11
91.51
89.96
88.16
86.98
88.03
86.24
84.65
83.23
81.7
80.25
78.8
77.51
76.2
75.04
74
75.49
77.14
76.15
76.27
78.19
76.49
77.31
76.65
74.99
73.51
72.07
70.59
71.96
76.29
74.86
74.93
71.9
71.01
77.47
75.78
76.6
76.07
74.57
73.02
72.65
73.16
71.53
69.78
67.98
69.96
72.16
70.47
68.86
67.37
65.87
72.16
71.34
69.93
68.44
67.16
66.01
67.25
70.91
69.75
68.59
67.48
66.31
64.81
66.58
65.97
64.7
64.7
60.94
59.08
58.42
57.77
57.11
53.31
49.96
49.4
48.84
48.3
47.74
47.24
46.76
46.29
48.9
49.23
48.53
48.03
54.34
53.79
53.24
52.96
52.17
51.7
58.55
78.2
77.03
76.19
77.15
75.87
95.47
109.67
112.28
112.01
107.93
105.96
105.06
102.98
102.2
105.23
101.85
99.89
96.23
94.76
91.51
91.63
91.54
85.23
87.83
87.38
84.44
85.19
84.03
86.73
102.52
104.45
106.98
107.02
99.26
94.45
113.44
157.33
147.38
171.89
171.95
132.71
126.02
121.18
115.45
110.48
117.85
117.63
124.65
109.59
111.27
99.78
98.21
99.2
97.97
89.55
87.91
93.34
94.42
93.2
90.29
91.46
89.98
88.35
88.41
82.44
79.89
75.69
75.66
84.5
96.73
87.48
82.39
83.48
79.31
78.16
72.77
72.45
68.46
67.62
68.76
70.07
68.55
65.3
58.96
59.17
62.37
66.28
55.62
55.23
55.85
56.75
50.89
53.88
52.95
55.08
53.61
58.78
61.85
55.91
53.32
46.41
44.57
50
50
53.36
46.23
50.45
49.07
45.85
48.45
49.96
46.53
50.51
47.58
48.05
46.84
47.67
49.16
55.54
55.82
58.22
56.19
57.77
63.19
54.76
55.74
62.54
61.39
69.6
79.23
80
93.68
107.63
100.18
97.3
90.45
80.64
80.58
75.82
85.59
89.35
89.42
104.73
95.32
89.27
90.44
86.97
79.98
81.22
87.35
83.64
82.22
94.4
102.18
Dataseries Y:
255
280.2
299.9
339.2
374.2
393.5
389.2
381.7
375.2
369
357.4
352.1
346.5
342.9
340.3
328.3
322.9
314.3
308.9
294
285.6
281.2
280.3
278.8
274.5
270.4
263.4
259.9
258
262.7
284.7
311.3
322.1
327
331.3
333.3
321.4
327
320
314.7
316.7
314.4
321.3
318.2
307.2
301.3
287.5
277.7
274.4
258.8
253.3
251
248.4
249.5
246.1
244.5
243.6
244
240.8
249.8
248
259.4
260.5
260.8
261.3
259.5
256.6
257.9
256.5
254.2
253.3
253.8
255.5
257.1
257.3
253.2
252.8
252
250.7
252.2
250
251
253.4
251.2
255.6
261.1
258.9
259.9
261.2
264.7
267.1
266.4
267.7
268.6
267.5
268.5
268.5
270.5
270.9
270.1
269.3
269.8
270.1
264.9
263.7
264.8
263.7
255.9
276.2
360.1
380.5
373.7
369.8
366.6
359.3
345.8
326.2
324.5
328.1
327.5
324.4
316.5
310.9
301.5
291.7
290.4
287.4
277.7
281.6
288
276
272.9
283
283.3
276.8
284.5
282.7
281.2
287.4
283.1
284
285.5
289.2
292.5
296.4
305.2
303.9
311.5
316.3
316.7
322.5
317.1
309.8
303.8
290.3
293.7
291.7
296.5
289.1
288.5
293.8
297.7
305.4
302.7
302.5
303
294.5
294.1
294.5
297.1
289.4
292.4
287.9
286.6
280.5
272.4
269.2
270.6
267.3
262.5
266.8
268.8
263.1
261.2
266
262.5
265.2
261.3
253.7
249.2
239.1
236.4
235.2
245.2
246.2
247.7
251.4
253.3
254.8
250
249.3
241.5
243.3
248
253
252.9
251.5
251.6
253.5
259.8
334.1
448
445.8
445
448.2
438.2
439.8
423.4
410.8
408.4
406.7
405.9
402.7
405.1
399.6
386.5
381.4
375.2
357.7
359
355
352.7
344.4
343.8
338
339
333.3
334.4
328.3
330.7
330
331.6
351.2
389.4
410.9
442.8
462.8
466.9
461.7
439.2
430.3
416.1
402.5
397.3
403.3
395.9
387.8
378.6
377.1
370.4
362
350.3
348.2
344.6
343.5
342.8
347.6
346.6
349.5
342.1
342
342.8
339.3
348.2
333.7
334.7
354
367.7
363.3
358.4
353.1
343.1
344.6
344.4
333.9
331.7
324.3
321.2
322.4
321.7
320.5
312.8
309.7
315.6
309.7
304.6
302.5
301.5
298.8
291.3
293.6
294.6
285.9
297.6
301.1
293.8
297.7
292.9
292.1
287.2
288.2
283.8
299.9
292.4
293.3
300.8
293.7
293.1
294.4
292.1
291.9
282.5
277.9
287.5
289.2
285.6
293.2
290.8
283.1
275
287.8
287.8
287.4
284
277.8
277.6
304.9
294
300.9
324
332.9
341.6
333.4
348.2
344.7
344.7
329.3
323.5
323.2
317.4
330.1
329.2
334.9
315.8
315.4
319.6
317.3
313.8
315.8
311.3




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=9091&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=9091&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=9091&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term165.5500976116877.7405351817614621.38742266836560
slope1.841683158895680.09701046945821918.98437528630730

\begin{tabular}{lllllllll}
\hline
Simple Linear Regression \tabularnewline
Statistics & Estimate & S.D. & T-STAT (H0: coeff=0) & P-value (two-sided) \tabularnewline
constant term & 165.550097611687 & 7.74053518176146 & 21.3874226683656 & 0 \tabularnewline
slope & 1.84168315889568 & 0.097010469458219 & 18.9843752863073 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=9091&T=1

[TABLE]
[ROW][C]Simple Linear Regression[/C][/ROW]
[ROW][C]Statistics[/C][C]Estimate[/C][C]S.D.[/C][C]T-STAT (H0: coeff=0)[/C][C]P-value (two-sided)[/C][/ROW]
[ROW][C]constant term[/C][C]165.550097611687[/C][C]7.74053518176146[/C][C]21.3874226683656[/C][C]0[/C][/ROW]
[ROW][C]slope[/C][C]1.84168315889568[/C][C]0.097010469458219[/C][C]18.9843752863073[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=9091&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=9091&T=1

As an alternative you can also use a QR Code:  

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

Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term165.5500976116877.7405351817614621.38742266836560
slope1.841683158895680.09701046945821918.98437528630730



Parameters (Session):
par1 = 0 ;
Parameters (R input):
par1 = 0 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
library(lattice)
z <- as.data.frame(cbind(x,y))
m <- lm(y~x)
summary(m)
bitmap(file='test1.png')
plot(z,main='Scatterplot, lowess, and regression line')
lines(lowess(z),col='red')
abline(m)
grid()
dev.off()
bitmap(file='test2.png')
m2 <- lm(m$fitted.values ~ x)
summary(m2)
z2 <- as.data.frame(cbind(x,m$fitted.values))
names(z2) <- list('x','Fitted')
plot(z2,main='Scatterplot, lowess, and regression line')
lines(lowess(z2),col='red')
abline(m2)
grid()
dev.off()
bitmap(file='test3.png')
m3 <- lm(m$residuals ~ x)
summary(m3)
z3 <- as.data.frame(cbind(x,m$residuals))
names(z3) <- list('x','Residuals')
plot(z3,main='Scatterplot, lowess, and regression line')
lines(lowess(z3),col='red')
abline(m3)
grid()
dev.off()
bitmap(file='test4.png')
m4 <- lm(m$fitted.values ~ m$residuals)
summary(m4)
z4 <- as.data.frame(cbind(m$residuals,m$fitted.values))
names(z4) <- list('Residuals','Fitted')
plot(z4,main='Scatterplot, lowess, and regression line')
lines(lowess(z4),col='red')
abline(m4)
grid()
dev.off()
bitmap(file='test5.png')
myr <- as.ts(m$residuals)
z5 <- as.data.frame(cbind(lag(myr,1),myr))
names(z5) <- list('Lagged Residuals','Residuals')
plot(z5,main='Lag plot')
m5 <- lm(z5)
summary(m5)
abline(m5)
grid()
dev.off()
bitmap(file='test6.png')
hist(m$residuals,main='Residual Histogram',xlab='Residuals')
dev.off()
bitmap(file='test7.png')
if (par1 > 0)
{
densityplot(~m$residuals,col='black',main=paste('Density Plot bw = ',par1),bw=par1)
} else {
densityplot(~m$residuals,col='black',main='Density Plot')
}
dev.off()
bitmap(file='test8.png')
acf(m$residuals,main='Residual Autocorrelation Function')
dev.off()
bitmap(file='test9.png')
qqnorm(x)
qqline(x)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Simple Linear Regression',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistics',1,TRUE)
a<-table.element(a,'Estimate',1,TRUE)
a<-table.element(a,'S.D.',1,TRUE)
a<-table.element(a,'T-STAT (H0: coeff=0)',1,TRUE)
a<-table.element(a,'P-value (two-sided)',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'constant term',header=TRUE)
a<-table.element(a,m$coefficients[[1]])
sd <- sqrt(vcov(m)[1,1])
a<-table.element(a,sd)
tstat <- m$coefficients[[1]]/sd
a<-table.element(a,tstat)
pval <- 2*(1-pt(abs(tstat),length(x)-2))
a<-table.element(a,pval)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'slope',header=TRUE)
a<-table.element(a,m$coefficients[[2]])
sd <- sqrt(vcov(m)[2,2])
a<-table.element(a,sd)
tstat <- m$coefficients[[2]]/sd
a<-table.element(a,tstat)
pval <- 2*(1-pt(abs(tstat),length(x)-2))
a<-table.element(a,pval)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')