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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_linear_regression.wasp
Title produced by softwareLinear Regression Graphical Model Validation
Date of computationMon, 19 Dec 2011 10:58:44 -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/2011/Dec/19/t13243103628zulsbe8z43mvqr.htm/, Retrieved Fri, 09 May 2025 16:30:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=157479, Retrieved Fri, 09 May 2025 16:30:35 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact228

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] [Regressiemodel 1] [2010-11-06 16:54:19] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- 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] [542c32830549043c4555f1bd78aefedb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
90604
97527
111940
100280
100009
95558
98533
92694
97920
110933
110855
111716
96348
105425
114874
104199
101166
99010
101607
97492
106088
113536
112475
115491
97733
102591
114783
100397
97772
96128
91261
90686
97792
108848
109989
109453
93945
98750
119043
104776
103262
106735
101600
99358
105240
114079
121637
111747
99496
104992
124255
108258
106940
104939
105896
107287
110783
122139
125823
120480
103296
117121
129924
118589
118062
113597
117161
112893
119657
136562
140446
138744
120324
118113
130257
125510
117986
118316
122075
117573
122566
135934
138394
137999
118780
117907
142932
132200
125666
127958
127718
124368
135241
144734
142320
141481
120471
123422
145829
134572
132156
140265
137771
134035
144016
151905
155791
148440
129862
134264
151952
143191
137242
136993
134431
132523
133486
140120
137521
112193
94256
99047
109761
102160
104792
104341
112430
113034
114197
127876
135199
123663
112578
117104
139703
114961
134222
128390
134197
135963
135936
146803
143231
131510
Dataseries Y:
Download CSV
Histogram 
33145
30912
35591
35832
38376
37971
39824
39908
38969
39553
37387
35119
36446
36041
38790
38281
41972
40483
42092
42255
40476
41254
37280
35192
37077
34265
38876
37447
41159
40153
42528
42681
40643
40724
34054
32587
33955
31396
35638
36474
39387
38233
40619
40340
38856
39325
34675
32695
32975
31210
35283
34247
37126
36582
39230
38672
37886
38118
33627
31880
32016
31900
35825
35818
39208
38581
40367
40033
38946
40144
34764
33328
32890
31171
34811
36879
40339
39112
40765
40730
39298
39653
34418
32387
33363
31463
36570
38031
42459
41764
43278
43024
41588
42396
37942
35454
35860
34110
39102
39584
43408
42247
44096
44083
41815
42668
37079
35454
35963
34673
37967
40127
43416
42659
44164
43134
41827
42188
34683
32762
32441
30076
34246
36224
38787
37849
40351
39865
37832
37867
32681
30910
31321
29857
34472
29353
38552
38344
41196
40955
38706
39368
34145
31123

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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=157479&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=157479&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157479&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 time3 seconds
R Server'AstonUniversity' @ aston.wessa.net






Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term33723.72331039612273.4790794031414.83353139948380
slope0.03206605759841720.01898965560830211.688606589810840.0934896836726817

\begin{tabular}{lllllllll}
\hline
Simple Linear Regression \tabularnewline
Statistics & Estimate & S.D. & T-STAT (H0: coeff=0) & P-value (two-sided) \tabularnewline
constant term & 33723.7233103961 & 2273.47907940314 & 14.8335313994838 & 0 \tabularnewline
slope & 0.0320660575984172 & 0.0189896556083021 & 1.68860658981084 & 0.0934896836726817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157479&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]33723.7233103961[/C][C]2273.47907940314[/C][C]14.8335313994838[/C][C]0[/C][/ROW]
[ROW][C]slope[/C][C]0.0320660575984172[/C][C]0.0189896556083021[/C][C]1.68860658981084[/C][C]0.0934896836726817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157479&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157479&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 term33723.72331039612273.4790794031414.83353139948380
slope0.03206605759841720.01898965560830211.688606589810840.0934896836726817


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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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):
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')