R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.
> x <- array(list(5,8,3,3,0,6,7,9,4,8,1,5,6,7,3,7,12,6,0,0,5,8,6,5,6,3,6,3,2,4,1,5,5,7,7,4,3,5,3,0,3,3,7,6,8,0,6,2,3,4,5,3,5,5,10,9,2,5,6,4,4,3,6,7,8,3,4,4,5,6,10,5,6,1,7,10,4,7,10,3,4,8,3,6,3,7,3,6,3,5,7,6,15,3,0,2,0,5,4,3,5,3,5,4,2,8,3,3,0,6,9,5,2,6,7,5,7,2,0,2,0,3,10,10,2,3,1,5,8,5,6,1,11,2,3,2,8,2,6,8,9,2,9,0,8,3,8,5,7,6,6,4,5,3,4,1,6,1,3,1,2,6,12,6,8,5,5,10,9,11,6,7,5,4,2,9,4,3,7,4,5,1,6,10,7,5,8,3,6,0,0,10,1,1,5,3,5,4,5,11,7,0,7,4,1,7,3,6,4,2,8,1,6,3,6,3,2,9,2,6,3,2,3,3,0,3,2,4,8,3,8,7,0,5,5,5,9,3,6,2,6,2,3,6,9,9,7,4,8,8,0,3,7,3,0,5,5,1,0,5,14,3,5,0,2,1,8,0,4,2,2,0,6,3,3,0,5,1,9,3,3,2,3,3,0,0,10,3,4,0,2,0,3,1,10,3,7,1,0,0,6,0,8,4,0,2,4,0,10,0,5,0),dim=c(2,156),dimnames=list(c('WS','WS(2)'),1:156))
> y <- array(NA,dim=c(2,156),dimnames=list(c('WS','WS(2)'),1:156))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = '0.0'
> par5 = 'paired'
> par4 = 'two.sided'
> par3 = '0.95'
> par2 = '2'
> par1 = '1'
> ylab = ''
> xlab = ''
> main = ''
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication:
> #Technical description:
> par1 <- as.numeric(par1) #column number of first sample
> par2 <- as.numeric(par2) #column number of second sample
> par3 <- as.numeric(par3) #confidence (= 1 - alpha)
> if (par5 == 'unpaired') paired <- FALSE else paired <- TRUE
> par6 <- as.numeric(par6) #H0
> z <- t(y)
> if (par1 == par2) stop('Please, select two different column numbers')
> if (par1 < 1) stop('Please, select a column number greater than zero for the first sample')
> if (par2 < 1) stop('Please, select a column number greater than zero for the second sample')
> if (par1 > length(z[1,])) stop('The column number for the first sample should be smaller')
> if (par2 > length(z[1,])) stop('The column number for the second sample should be smaller')
> if (par3 <= 0) stop('The confidence level should be larger than zero')
> if (par3 >= 1) stop('The confidence level should be smaller than zero')
> (r.t <- t.test(z[,par1],z[,par2],var.equal=TRUE,alternative=par4,paired=paired,mu=par6,conf.level=par3))
Paired t-test
data: z[, par1] and z[, par2]
t = 3.1055, df = 155, p-value = 0.002259
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
0.3685661 1.6570749
sample estimates:
mean of the differences
1.012821
> (v.t <- var.test(z[,par1],z[,par2],conf.level=par3))
F test to compare two variances
data: z[, par1] and z[, par2]
F = 1.2794, num df = 155, denom df = 155, p-value = 0.1262
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
0.932717 1.754846
sample estimates:
ratio of variances
1.279365
> (r.w <- t.test(z[,par1],z[,par2],var.equal=FALSE,alternative=par4,paired=paired,mu=par6,conf.level=par3))
Paired t-test
data: z[, par1] and z[, par2]
t = 3.1055, df = 155, p-value = 0.002259
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
0.3685661 1.6570749
sample estimates:
mean of the differences
1.012821
> (w.t <- wilcox.test(z[,par1],z[,par2],alternative=par4,paired=paired,mu=par6,conf.level=par3))
Wilcoxon signed rank test with continuity correction
data: z[, par1] and z[, par2]
V = 6369.5, p-value = 0.004892
alternative hypothesis: true location shift is not equal to 0
> (ks.t <- ks.test(z[,par1],z[,par2],alternative=par4))
Two-sample Kolmogorov-Smirnov test
data: z[, par1] and z[, par2]
D = 0.1667, p-value = 0.02625
alternative hypothesis: two-sided
Warning message:
In ks.test(z[, par1], z[, par2], alternative = par4) :
cannot compute correct p-values with ties
> m1 <- mean(z[,par1],na.rm=T)
> m2 <- mean(z[,par2],na.rm=T)
> mdiff <- m1 - m2
> newsam1 <- z[!is.na(z[,par1]),par1]
> newsam2 <- z[,par2]+mdiff
> newsam2 <- newsam2[!is.na(newsam2)]
> (ks1.t <- ks.test(newsam1,newsam2,alternative=par4))
Two-sample Kolmogorov-Smirnov test
data: newsam1 and newsam2
D = 0.1538, p-value = 0.04983
alternative hypothesis: two-sided
Warning message:
In ks.test(newsam1, newsam2, alternative = par4) :
cannot compute correct p-values with ties
> mydf <- data.frame(cbind(z[,par1],z[,par2]))
> colnames(mydf) <- c('Variable 1','Variable 2')
> postscript(file="/var/www/html/rcomp/tmp/11azp1293205660.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> boxplot(mydf, notch=TRUE, ylab='value',main=main)
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/21azp1293205660.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(z[,par1],main='Normal QQplot - Variable 1')
> qqline(z[,par1])
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/31azp1293205660.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(z[,par2],main='Normal QQplot - Variable 2')
> qqline(z[,par2])
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,paste('Two Sample t-test (',par5,')',sep=''),2,TRUE)
> a<-table.row.end(a)
> if(!paired){
+ a<-table.row.start(a)
+ a<-table.element(a,'Mean of Sample 1',header=TRUE)
+ a<-table.element(a,r.t$estimate[[1]])
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Mean of Sample 2',header=TRUE)
+ a<-table.element(a,r.t$estimate[[2]])
+ a<-table.row.end(a)
+ } else {
+ a<-table.row.start(a)
+ a<-table.element(a,'Difference: Mean1 - Mean2',header=TRUE)
+ a<-table.element(a,r.t$estimate)
+ a<-table.row.end(a)
+ }
> a<-table.row.start(a)
> a<-table.element(a,'t-stat',header=TRUE)
> a<-table.element(a,r.t$statistic[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'df',header=TRUE)
> a<-table.element(a,r.t$parameter[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,r.t$p.value)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'H0 value',header=TRUE)
> a<-table.element(a,r.t$null.value[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Alternative',header=TRUE)
> a<-table.element(a,r.t$alternative)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'CI Level',header=TRUE)
> a<-table.element(a,attr(r.t$conf.int,'conf.level'))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'CI',header=TRUE)
> a<-table.element(a,paste('[',r.t$conf.int[1],',',r.t$conf.int[2],']',sep=''))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'F-test to compare two variances',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'F-stat',header=TRUE)
> a<-table.element(a,v.t$statistic[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'df',header=TRUE)
> a<-table.element(a,v.t$parameter[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,v.t$p.value)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'H0 value',header=TRUE)
> a<-table.element(a,v.t$null.value[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Alternative',header=TRUE)
> a<-table.element(a,v.t$alternative)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'CI Level',header=TRUE)
> a<-table.element(a,attr(v.t$conf.int,'conf.level'))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'CI',header=TRUE)
> a<-table.element(a,paste('[',v.t$conf.int[1],',',v.t$conf.int[2],']',sep=''))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/44lur1293205660.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,paste('Welch Two Sample t-test (',par5,')',sep=''),2,TRUE)
> a<-table.row.end(a)
> if(!paired){
+ a<-table.row.start(a)
+ a<-table.element(a,'Mean of Sample 1',header=TRUE)
+ a<-table.element(a,r.w$estimate[[1]])
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Mean of Sample 2',header=TRUE)
+ a<-table.element(a,r.w$estimate[[2]])
+ a<-table.row.end(a)
+ } else {
+ a<-table.row.start(a)
+ a<-table.element(a,'Difference: Mean1 - Mean2',header=TRUE)
+ a<-table.element(a,r.w$estimate)
+ a<-table.row.end(a)
+ }
> a<-table.row.start(a)
> a<-table.element(a,'t-stat',header=TRUE)
> a<-table.element(a,r.w$statistic[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'df',header=TRUE)
> a<-table.element(a,r.w$parameter[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,r.w$p.value)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'H0 value',header=TRUE)
> a<-table.element(a,r.w$null.value[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Alternative',header=TRUE)
> a<-table.element(a,r.w$alternative)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'CI Level',header=TRUE)
> a<-table.element(a,attr(r.w$conf.int,'conf.level'))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'CI',header=TRUE)
> a<-table.element(a,paste('[',r.w$conf.int[1],',',r.w$conf.int[2],']',sep=''))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5ida01293205660.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,paste('Wicoxon rank sum test with continuity correction (',par5,')',sep=''),2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'W',header=TRUE)
> a<-table.element(a,w.t$statistic[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,w.t$p.value)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'H0 value',header=TRUE)
> a<-table.element(a,w.t$null.value[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Alternative',header=TRUE)
> a<-table.element(a,w.t$alternative)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Kolmogorov-Smirnov Test to compare Distributions of two Samples',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'KS Statistic',header=TRUE)
> a<-table.element(a,ks.t$statistic[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,ks.t$p.value)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Kolmogorov-Smirnov Test to compare Distributional Shape of two Samples',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'KS Statistic',header=TRUE)
> a<-table.element(a,ks1.t$statistic[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,ks1.t$p.value)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/6e4q91293205660.tab")
> try(system("convert tmp/11azp1293205660.ps tmp/11azp1293205660.png",intern=TRUE))
character(0)
> try(system("convert tmp/21azp1293205660.ps tmp/21azp1293205660.png",intern=TRUE))
character(0)
> try(system("convert tmp/31azp1293205660.ps tmp/31azp1293205660.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
0.665 0.455 1.796