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)
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> x <- array(list(52792117.596,44942851.780,9817684.280,51114646.772,27004830.074,2777207.566,13875207.231,37995371.498,40847986.206,13156891.138,57657199.379,19252361.685,33135196.435,17637213.595,7039635.987,77208823.856,8579609.420,22878477.938,32920447.802,13209990.380,27438431.426,27546948.302,54556562.144,44498674.354,16958873.113,71726744.785,57160689.248,10497804.428,30942147.512,37013819.338,28153012.700,36119785.686,9845637.610,19012326.326,41872234.131,33038681.382,1429002.988,36442251.000,19142553.224,10306108.416,32552845.124,27342318.448,9927903.168,19962132.886,10076578.476,34556371.040,14816666.092,19990601.747,23729529.338,12057368.840,11805589.848,3890720.530,53180992.296,18186921.663,32914142.490,32411086.961,27707941.848,23247527.828,3033894.172,7283147.700,28571004.280,38622407.926),dim=c(2,47),dimnames=list(c('3nas','sbcc'),1:47))
> y <- array(NA,dim=c(2,47),dimnames=list(c('3nas','sbcc'),1:47))
> 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 = -0.4192, df = 92, p-value = 0.676
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-8928308 5815992
sample estimates:
mean of x mean of y
28050336 29606494
> (v.t <- var.test(z[,par1],z[,par2],conf.level=par3))
F test to compare two variances
data: z[, par1] and z[, par2]
F = 0.7956, num df = 46, denom df = 46, p-value = 0.4412
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
0.4431701 1.4284192
sample estimates:
ratio of variances
0.7956335
> (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 = -0.4192, df = 90.824, p-value = 0.676
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-8929580 5817265
sample estimates:
mean of x mean of y
28050336 29606494
> (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 = 1054, p-value = 0.7053
alternative hypothesis: true location shift is not equal to 0
Warning message:
In wilcox.test.default(z[, par1], z[, par2], alternative = par4, :
cannot compute exact p-value with ties
> (ks.t <- ks.test(z[,par1],z[,par2],alternative=par4))
Two-sample Kolmogorov-Smirnov test
data: z[, par1] and z[, par2]
D = 0.1489, p-value = 0.6744
alternative hypothesis: two-sided
Warning message:
In ks.test(z[, par1], z[, par2], alternative = par4) :
cannot compute exact p-value 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 = 0.1489, p-value = 0.6744
alternative hypothesis: two-sided
Warning message:
In ks.test(newsam1, newsam2, alternative = par4) :
cannot compute exact p-value with ties
> mydf <- data.frame(cbind(z[,par1],z[,par2]))
> colnames(mydf) <- c('Variable 1','Variable 2')
> postscript(file="/var/fisher/rcomp/tmp/1uq3k1383343928.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/2psl71383343928.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/39lox1383343928.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/40mme1383343928.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$conf.int[2],']',sep=''))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/5woee1383343928.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,paste('Wicoxon rank sum test with continuity correction (',par5,')',sep=''),2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'W',header=TRUE)
> a<-table.element(a,w.t$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/fisher/rcomp/tmp/6h1u11383343928.tab")
>
> try(system("convert tmp/1uq3k1383343928.ps tmp/1uq3k1383343928.png",intern=TRUE))
character(0)
> try(system("convert tmp/2psl71383343928.ps tmp/2psl71383343928.png",intern=TRUE))
character(0)
> try(system("convert tmp/39lox1383343928.ps tmp/39lox1383343928.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
1.723 0.508 2.214