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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_linear_regression.wasp

Title produced by software

Linear Regression Graphical Model Validation

Date of computation

Sat, 13 Nov 2010 12:51:28 +0000

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/2010/Nov/13/t12896525850upgt9itbhvxdvy.htm/, Retrieved Sat, 27 Apr 2024 11:58:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=94364, Retrieved Sat, 27 Apr 2024 11:58:05 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

189

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] [ws6vb] [2010-11-13 11:31:05] [c7506ced21a6c0dca45d37c8a93c80e0]
-    D      [Linear Regression Graphical Model Validation] [tt] [2010-11-13 12:51:28] [cfd788255f1b1b5389e58d7f218c70bf] [Current]
-    D        [Linear Regression Graphical Model Validation] [W6tutorial] [2010-11-13 14:33:02] [c7506ced21a6c0dca45d37c8a93c80e0] 
-    D          [Linear Regression Graphical Model Validation] [Workshop 6, Mini ...] [2010-11-14 15:39:04] [3635fb7041b1998c5a1332cf9de22bce] 
-    D            [Linear Regression Graphical Model Validation] [Workshop 6, Simpl...] [2010-11-16 19:47:28] [3635fb7041b1998c5a1332cf9de22bce] 
- R  D              [Linear Regression Graphical Model Validation] [Mini Toturial - H...] [2010-11-17 00:22:02] [b20a509e36241371274681d9edf773da] 
- R  D              [Linear Regression Graphical Model Validation] [] [2011-11-15 15:55:49] [46896e8a404bb9354f2d070359621409] 
- R  D              [Linear Regression Graphical Model Validation] [Mini Tutorial - k...] [2011-11-15 16:56:43] [74be16979710d4c4e7c6647856088456] 
- RMPD              [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [Chi Squared Test ...] [2011-11-15 17:42:51] [d0cddc92c01af61bef0226b9e5ade9b3] 
- R  D            [Linear Regression Graphical Model Validation] [Mini Toturial - H...] [2010-11-17 00:19:55] [b20a509e36241371274681d9edf773da] 
-    D            [Linear Regression Graphical Model Validation] [] [2011-11-15 08:53:32] [ea9976aa04c7322b215e949114660791] 
- R  D            [Linear Regression Graphical Model Validation] [] [2011-11-15 15:35:27] [46896e8a404bb9354f2d070359621409] 
- R  D            [Linear Regression Graphical Model Validation] [Mini Tutorial - t...] [2011-11-15 16:42:35] [74be16979710d4c4e7c6647856088456] 
- R  D            [Linear Regression Graphical Model Validation] [Workshop 6: Mini-...] [2011-11-15 17:30:14] [21b3d52ef28595defb5676e0f3570994] 
- R  D            [Linear Regression Graphical Model Validation] [Workshop 6: Mini-...] [2011-11-15 17:32:29] [21b3d52ef28595defb5676e0f3570994] 
- R  D            [Linear Regression Graphical Model Validation] [] [2011-12-19 16:17:39] [c505444e07acba7694d29053ca5d114e] 
- R  D            [Linear Regression Graphical Model Validation] [] [2011-12-19 16:19:11] [c505444e07acba7694d29053ca5d114e] 
-               [Linear Regression Graphical Model Validation] [Tutorial1] [2010-11-16 20:35:31] [fc9068db680cd880760a7c0fccd81a61] 
F    D          [Linear Regression Graphical Model Validation] [] [2010-11-17 08:28:03] [f9eaed74daea918f73b9f505c5b1f19e] 
-    D          [Linear Regression Graphical Model Validation] [Spaargeld NL vs L...] [2010-12-21 14:30:35] [fc9068db680cd880760a7c0fccd81a61] 
-    D          [Linear Regression Graphical Model Validation] [Spaargeld NL vs L...] [2010-12-21 14:42:24] [fc9068db680cd880760a7c0fccd81a61] 

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Dataseries X:

Download CSV

Histogram

Boxplots

3,4
1,8
4,6
2,3
3,1
5,5
0,7
3,0
2,6
4,3
2,1
1,1
6,1
4,8
3,8

Dataseries Y:

Download CSV

Histogram

26,2
17,8
31,3
23,1
27,5
36,0
14,1
22,3
19,6
31,3
24,0
17,3
43,2
36,4
26,1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 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 & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94364&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]9 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=94364&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94364&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	9 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Simple Linear Regression
Statistics	Estimate	S.D.	T-STAT (H0: coeff=0)	P-value (two-sided)
constant term	10.2779285495247	1.42027781053505	7.2365620819301	6.58556422616918e-06
slope	4.91933072677093	0.392747749440305	12.5254205371803	1.24779999666202e-08

\begin{tabular}{lllllllll}
\hline
Simple Linear Regression \tabularnewline
Statistics & Estimate & S.D. & T-STAT (H0: coeff=0) & P-value (two-sided) \tabularnewline
constant term & 10.2779285495247 & 1.42027781053505 & 7.2365620819301 & 6.58556422616918e-06 \tabularnewline
slope & 4.91933072677093 & 0.392747749440305 & 12.5254205371803 & 1.24779999666202e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94364&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]10.2779285495247[/C][C]1.42027781053505[/C][C]7.2365620819301[/C][C]6.58556422616918e-06[/C][/ROW]
[ROW][C]slope[/C][C]4.91933072677093[/C][C]0.392747749440305[/C][C]12.5254205371803[/C][C]1.24779999666202e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94364&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94364&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
Statistics	Estimate	S.D.	T-STAT (H0: coeff=0)	P-value (two-sided)
constant term	10.2779285495247	1.42027781053505	7.2365620819301	6.58556422616918e-06
slope	4.91933072677093	0.392747749440305	12.5254205371803	1.24779999666202e-08

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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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')

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Figures (Output of Computation)

Input Parameters & R Code