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*The author of this computation has been verified*
R Software Module: /rwasp_linear_regression.wasp (opens new window with default values)
Title produced by software: Linear Regression Graphical Model Validation
Date of computation: Tue, 16 Nov 2010 20:19:12 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40.htm/, Retrieved Tue, 16 Nov 2010 21:18:24 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1100 1100 1100 1100 1100 1100 1100 1100 1100 1100 1200 1200 1200 1200 1200 1200 1200 1200 1200 1200 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1400 1400 1400 1400 1400 1400 1400 1400 1400 1400 1500 1500 1500 1500 1500 1500 1500 1500 1500 1500 1600 1600 1600 1600 1600 1600 1600 1600 1600 1600 1700 1700 1700 1700 1700 1700 1700 1700 1700 1700 1800 1800 1800 1800 1800 1800 1800 1800 1800 1800 1900 1900 1900 1900 1900 1900 1900 1900 1900 1900 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2100 2100 2100 2100 2100 2100 2100 2100 2100 2100 2200 2200 2200 2200 2200 2200 2200 2200 2200 2200 2300 2300 2300 2300 2300 2300 2300 2300 2300 2300 2400 2400 2400 2400 2400 2400 2400 2400 2400 2400 2500 2500 2500 2500 2500 2500 2500 2500 2500 2500 2600 2600 2600 2600 2600 2600 2600 2600 2600 2600 2700 etc...
 
Dataseries Y:
» Textbox « » Textfile « » CSV «
61.10986116 54.12031648 54.95749446 51.99594378 56.24546553 64.77452146 54.33699821 53.72119053 48.83342072 55.93379725 64.65918024 61.60053636 63.05659263 67.15166067 60.02845855 69.52301201 65.01551552 60.87993666 70.72557348 73.09285805 73.29160052 72.66843666 68.83636849 76.67414394 70.41408315 77.9401298 73.20981757 77.41384989 79.4630442 75.42057899 82.68120243 94.03299383 84.0698862 85.67449188 81.89949935 92.9720738 88.85764153 80.49481348 91.71796544 82.26348598 82.94116291 90.99841989 91.31788491 96.95308859 90.04825345 100.9221214 99.89956639 93.01828481 95.97742386 103.5617168 110.7469177 108.3696381 107.0012411 110.7524482 98.56007743 100.5808127 101.9883776 101.8791562 108.9640668 104.5917605 119.5561823 119.3482511 105.3661433 121.4417904 117.747784 116.6637445 119.6190875 115.2413454 106.7405737 113.7508379 124.9325395 124.9165153 134.0975866 132.0328883 124.4484784 115.0077499 122.6887566 125.0399372 119.2917291 13 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk


Simple Linear Regression
StatisticsEstimateS.D.T-STAT (H0: coeff=0)P-value (two-sided)
constant term-44.47603581591290.66426852711803-66.95490453066460
slope0.0998413036489790.000205980926142623484.7114027434170
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/1sr001289938742.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/1sr001289938742.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/2sr001289938742.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/2sr001289938742.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/3k0il1289938742.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/3k0il1289938742.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/4v9zo1289938742.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/4v9zo1289938742.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/5v9zo1289938742.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/5v9zo1289938742.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/6gajm1289938743.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/6gajm1289938743.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/7gajm1289938743.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/7gajm1289938743.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/8r1io1289938743.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/8r1io1289938743.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/9r1io1289938743.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Nov/16/t1289938701y9we50yzbh93a40/9r1io1289938743.ps (open in new window)


 
Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
 
Parameters (R input):
par1 = 0 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
 
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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This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


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