R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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.

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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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- array(list(110
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+ ,dim=c(3
+ ,160)
+ ,dimnames=list(c('Hours.UK'
+ ,'Hours.BS'
+ ,'Hours.BB')
+ ,1:160))
>  y <- array(NA,dim=c(3,160),dimnames=list(c('Hours.UK','Hours.BS','Hours.BB'),1:160))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par6 = '0.0'
> par5 = 'unpaired'
> par4 = 'two.sided'
> par3 = '0.95'
> par2 = '2'
> par1 = '1'
> main = 'Two Samples'
> par6 <- '0.0'
> par5 <- 'unpaired'
> par4 <- 'two.sided'
> par3 <- '0.95'
> par2 <- '2'
> par1 <- '1'
> #'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))

	Two Sample t-test

data:  z[, par1] and z[, par2]
t = 4.3693, df = 284, p-value = 1.749e-05
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
  5.379723 14.200436
sample estimates:
mean of x mean of y 
 38.42500  28.63492 

> (v.t <- var.test(z[,par1],z[,par2],conf.level=par3))

	F test to compare two variances

data:  z[, par1] and z[, par2]
F = 0.8343, num df = 159, denom df = 125, p-value = 0.2803
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
 0.596180 1.159738
sample estimates:
ratio of variances 
         0.8343062 

> (r.w <- t.test(z[,par1],z[,par2],var.equal=FALSE,alternative=par4,paired=paired,mu=par6,conf.level=par3))

	Welch Two Sample t-test

data:  z[, par1] and z[, par2]
t = 4.3225, df = 256.251, p-value = 2.21e-05
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
  5.329867 14.250291
sample estimates:
mean of x mean of y 
 38.42500  28.63492 

> (w.t <- wilcox.test(z[,par1],z[,par2],alternative=par4,paired=paired,mu=par6,conf.level=par3))

	Wilcoxon rank sum test with continuity correction

data:  z[, par1] and z[, par2]
W = 13097.5, p-value = 1.386e-05
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 = 0.2843, p-value = 2.246e-05
alternative hypothesis: two-sided

Warning message:
In ks.test(z[, par1], z[, par2], alternative = par4) :
  p-value will be approximate in the presence of 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 = 0.1386, p-value = 0.1333
alternative hypothesis: two-sided

Warning message:
In ks.test(newsam1, newsam2, alternative = par4) :
  p-value will be approximate in the presence of ties
> mydf <- data.frame(cbind(z[,par1],z[,par2]))
> colnames(mydf) <- c('Variable 1','Variable 2')
> postscript(file="/var/fisher/rcomp/tmp/1fr731387133508.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/fisher/rcomp/tmp/22zqh1387133508.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/fisher/rcomp/tmp/3e9xq1387133508.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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$conf.int[2],']',sep=''))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/4c9na1387133508.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,paste('Welch Two Sample t-test (',par5,')',sep=''),2,TRUE)
> a<-table.row.end(a)
> if(!paired){
+ a<-table.row.start(a)
+ a<-table.element(a,'Mean of Sample 1',header=TRUE)
+ a<-table.element(a,r.w$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/fisher/rcomp/tmp/5k4it1387133508.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 <i>Distributions</i> 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 <i>Distributional Shape</i> 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/fisher/rcomp/tmp/6lpwj1387133508.tab") 
> 
> try(system("convert tmp/1fr731387133508.ps tmp/1fr731387133508.png",intern=TRUE))
character(0)
> try(system("convert tmp/22zqh1387133508.ps tmp/22zqh1387133508.png",intern=TRUE))
character(0)
> try(system("convert tmp/3e9xq1387133508.ps tmp/3e9xq1387133508.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.298   1.056   4.336