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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_linear_regression.wasp
Title produced by softwareLinear Regression Graphical Model Validation
Date of computationSun, 02 Dec 2012 07:55:42 -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/02/t1354453059rhxzix6qkyz7ene.htm/, Retrieved Thu, 31 Oct 2024 22:45:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195476, Retrieved Thu, 31 Oct 2024 22:45:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact193

Tree of Dependent Computations

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] [74be16979710d4c4e7c6647856088456]
- RM D    [Linear Regression Graphical Model Validation] [simple regression...] [2012-12-02 12:55:42] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D      [Linear Regression Graphical Model Validation] [lineair regressio...] [2012-12-02 13:14:50] [74be16979710d4c4e7c6647856088456]
-    D        [Linear Regression Graphical Model Validation] [simple lineair re...] [2012-12-02 14:14:16] [74be16979710d4c4e7c6647856088456]
-    D        [Linear Regression Graphical Model Validation] [] [2014-12-03 14:41:24] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
210907
120982
176508
179321
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385534
33170
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165446
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106408
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269651
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341570
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233328
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206161
311473
235800
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151101
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324598
131069
204271
165543
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250047
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195838
173260
254488
104389
136084
199476
92499
224330
135781
74408
81240
14688
181633
271856
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17547
133368
95227
152601
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59194
139942
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72880
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77272
49289
135131
108446
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77648
181528
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124064
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104011
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103425
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62215
69304
53117
19764
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84105
77945
89113
91005
40248
64187
50857
56613
62792
72535
Dataseries Y:
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Histogram 
56
56
54
89
40
25
92
18
63
44
33
84
88
55
60
66
154
53
119
41
61
58
75
33
40
92
100
112
73
40
45
60
62
75
31
77
34
46
99
17
66
30
76
146
67
56
107
58
34
61
119
42
66
89
44
66
24
259
17
64
41
68
168
43
132
105
71
112
94
82
70
57
53
103
121
62
52
52
32
62
45
46
63
75
88
46
53
37
90
63
78
25
45
46
41
144
82
91
71
63
53
62
63
32
39
62
117
34
92
93
54
144
14
61
109
38
73
75
50
61
55
77
75
72
50
32
53
42
71
10
35
65
25
66
41
86
16
42
19
19
45
65
35
95
49
37
64
38
34
32
65
52
62
65
83
95
29
18
33
247
139
29
118
110
67
42
65
94
64
81
95
67
63
83
45
30
70
32
83
31
67
66
10
70
103
5
20
5
36
34
48
40
43
31
42
46
33
18
55
35
59
19
66
60
36
25
47
54
53
40
40
39
14
45
36
28
44
30
22
17
31
55
54
21
14
81
35
43
46
30
23
38
54
20
53
45
39
20
24
31
35
151
52
30
31
29
57
40
44
25
77
35
11
63
44
19
13
42
38
29
20
27
20
19
37
26
42
49
30
49
67
28
19
49
27
30
22
12
31
20
20
39
29
16
27
21
19
35
14

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 7 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195476&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195476&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195476&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term14.20395991800352.724097354416375.214189535104433.53823967680356e-07
slope0.0002945078291702541.69514004761485e-0517.37365768596180

\begin{tabular}{lllllllll}
\hline
Simple Linear Regression \tabularnewline
Statistics & Estimate & S.D. & T-STAT (H0: coeff=0) & P-value (two-sided) \tabularnewline
constant term & 14.2039599180035 & 2.72409735441637 & 5.21418953510443 & 3.53823967680356e-07 \tabularnewline
slope & 0.000294507829170254 & 1.69514004761485e-05 & 17.3736576859618 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195476&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]14.2039599180035[/C][C]2.72409735441637[/C][C]5.21418953510443[/C][C]3.53823967680356e-07[/C][/ROW]
[ROW][C]slope[/C][C]0.000294507829170254[/C][C]1.69514004761485e-05[/C][C]17.3736576859618[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195476&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195476&T=1

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


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

Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term14.20395991800352.724097354416375.214189535104433.53823967680356e-07
slope0.0002945078291702541.69514004761485e-0517.37365768596180


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Input Parameters & R Code

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')