| | *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: Mon, 20 Dec 2010 18:07:09 +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/Dec/20/t1292868383rtyh8x09drqws4r.htm/, Retrieved Mon, 20 Dec 2010 19:06:23 +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/Dec/20/t1292868383rtyh8x09drqws4r.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 « | 17.98
17.83
19.45
21.04
20.03
20.01
19.64
18.52
19.59
20.09
19.82
21.09
22.64
22.11
20.42
18.58
18.24
16.87
18.64
27.17
33.69
35.92
32.30
27.34
24.96
20.52
19.86
20.82
21.24
20.20
21.42
21.69
21.86
23.23
22.47
19.52
18.82
19.00
18.92
20.24
20.94
22.38
21.76
21.35
21.90
21.69
20.34
19.41
19.08
20.05
20.35
20.27
19.94
19.07
17.87
18.01
17.51
18.15
16.70
14.51
15.00
14.78
14.66
16.38
17.88
19.07
19.65
18.38
17.46
17.71
18.10
17.16
17.99
18.53
18.55
19.87
19.74
18.42
17.30
18.03
18.23
17.44
17.99
19.04
18.88
19.07
21.36
23.57
21.25
20.45
21.32
21.96
23.99
24.90
23.71
25.39
25.17
22.21
20.99
19.72
20.83
19.17
19.63
19.93
19.79
21.26
20.17
18.32
16.71
16.06
15.02
15.44
14.86
13.66
14.08
13.36
14.95
14.39
12.85
11.28
12.47
12.01
14.66
17.34
17.75
17.89
20.07
21.26
23.88
22.64
24.97
26.08
27.18
29.35
29.89
25.74
28.78
31.83
29.77
31.22
33.88
33.08
34.40
28.46
29.58
29.61
27 etc... | | Dataseries Y: | » Textbox « » Textfile « » CSV « | 586,9642
582,1727
586,19396
590,49531
589,70506
590,07518
595,2568
604,1796
605,00987
610,71165
618,31404
614,74292
609,16284
611,73756
620,77222
618,00755
612,3328
604,04309
605,08732
569,6086
595,0899
598,49214
606,67306
608,78857
606,9776
603,86769
606,42144
592,42386
590,6524
592,57978
602,51677
595,5471
605,94461
605,4981
607,95824
612,04311
612,7243
604,3511
597,85685
601,4573
590,17392
592,59948
597,24933
597,11685
599,7328
607,71194
604,82143
608,02913
606,1822
609,73516
602,5858
595,55291
597,41659
594,57492
600,63662
598,85984
598,97301
603,61033
604,24871
608,12389
610,69475
608,90087
607,98959
603,37721
607,81136
610,96411
606,97026
605,89335
611,97502
616,95077
618,69499
621,90975
617,85264
623,04912
615,57
623,58574
623,63317
615,04568
624,57004
625,8824
629,83163
626,42181
628,40528
632,30782
631,60361
635,57585
634,08687
632,61106
632,6136
635,80934
636,67236
633,388
638,09523
641,6666
646,15675
651, etc... | | Output produced by software: |
Simple Linear Regression | Statistics | Estimate | S.D. | T-STAT (H0: coeff=0) | P-value (two-sided) | constant term | 610.349888163618 | 3.78541803077257 | 161.237116535595 | 0 | slope | 1.60320516554971 | 0.090030701766168 | 17.8073161054951 | 0 |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/18dbm1292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/18dbm1292868424.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/28dbm1292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/28dbm1292868424.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/3jms71292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/3jms71292868424.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/4te9s1292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/4te9s1292868424.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/5m5rd1292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/5m5rd1292868424.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/6m5rd1292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/6m5rd1292868424.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/7xe8g1292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/7xe8g1292868424.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/8xe8g1292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/8xe8g1292868424.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/9xe8g1292868424.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/20/t1292868383rtyh8x09drqws4r/9xe8g1292868424.ps (open in new window) |
| | 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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