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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 computationThu, 25 Nov 2010 11:12:40 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/25/t1290683544ez8rm0w16c5q1j1.htm/, Retrieved Tue, 16 Apr 2024 10:42:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=100790, Retrieved Tue, 16 Apr 2024 10:42:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

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]
-  M D    [Linear Regression Graphical Model Validation] [] [2010-11-25 11:12:40] [288f03f47c5783dcaccb816dacc66894] [Current]
-    D      [Linear Regression Graphical Model Validation] [] [2010-11-26 14:52:17] [b85d3508e7cb050fe9be80ea93d51170]
-    D      [Linear Regression Graphical Model Validation] [] [2010-11-26 14:52:17] [b85d3508e7cb050fe9be80ea93d51170]
-   P       [Linear Regression Graphical Model Validation] [] [2010-12-13 20:07:13] [e71d94d32f847f62b540eebe6fadd003]
-   P       [Linear Regression Graphical Model Validation] [] [2010-12-13 20:07:13] [43e84bd88d5f94b739fa54f225367516]
-   P       [Linear Regression Graphical Model Validation] [] [2010-12-13 20:07:13] [43e84bd88d5f94b739fa54f225367516]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
61.712
62.084
61.406
60.724
58.904
58.722
59.704
60.674
59.813
60.568
61.401
61.427
61.080
61.999
63.888
66.284
67.309
66.685
65.404
65.045
63.867
64.156
62.224
63.193
64.256
66.153
68.072
68.245
68.741
67.795
67.315
67.245
66.448
69.112
71.787
74.366
76.337
77.618
77.090
76.925
78.384
80.462
82.765
85.033
83.608
81.813
81.467
80.708
80.631
79.133
77.396
75.491
74.267
72.882
71.286
70.737
67.425
67.530
67.157
67.215
66.268
66.053
54.905
54.459
51.159
44.725
40.184
44.094
46.904
47.141
45.052
42.758
41.388
41.154
40.019
39.928
38.598
36.584
32.566
30.140
27.713
25.380
23.823
21.376
18.696
16.304
14.203
11.807
7.551
4.215
3.346
3.010
2.849
2.485
1.744
1.221
803
553
314
204
125
55
53
27
10
6
Dataseries Y:
Download CSV
Histogram 
58.951
59.634
58.389
57.702
56.593
55.998
57.363
58.022
57.598
57.842
58.875
59.103
58.484
58.636
61.342
63.470
64.281
63.721
62.657
62.549
61.882
62.325
61.907
63.136
63.982
65.800
67.596
68.654
67.548
67.398
66.999
66.284
65.561
67.694
69.976
72.908
75.128
75.522
75.242
75.179
75.572
78.340
80.107
82.972
81.638
80.018
80.631
79.211
79.999
77.789
76.205
75.352
74.393
72.771
70.682
69.991
67.525
67.779
66.864
67.971
67.071
66.980
57.144
56.648
53.706
47.108
43.292
48.489
52.642
53.249
50.722
49.805
49.303
49.985
49.512
51.282
50.734
50.365
46.191
44.617
42.012
41.027
39.478
36.824
34.761
31.295
28.951
25.872
17.297
10.739
9.087
8.658
8.731
8.358
6.518
5.021
3.440
2.523
1.725
1.210
777
498
312
179
92
106

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100790&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100790&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 time6 seconds
R Server'George Udny Yule' @ 72.249.76.132






Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term72.059059224307910.76616419185976.693104242158221.13433129556029e-09
slope-0.02897417764875850.0920603929373-0.3147301105752610.753597138259184

\begin{tabular}{lllllllll}
\hline
Simple Linear Regression \tabularnewline
Statistics & Estimate & S.D. & T-STAT (H0: coeff=0) & P-value (two-sided) \tabularnewline
constant term & 72.0590592243079 & 10.7661641918597 & 6.69310424215822 & 1.13433129556029e-09 \tabularnewline
slope & -0.0289741776487585 & 0.0920603929373 & -0.314730110575261 & 0.753597138259184 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100790&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]72.0590592243079[/C][C]10.7661641918597[/C][C]6.69310424215822[/C][C]1.13433129556029e-09[/C][/ROW]
[ROW][C]slope[/C][C]-0.0289741776487585[/C][C]0.0920603929373[/C][C]-0.314730110575261[/C][C]0.753597138259184[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100790&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 term72.059059224307910.76616419185976.693104242158221.13433129556029e-09
slope-0.02897417764875850.0920603929373-0.3147301105752610.753597138259184


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):
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')