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Type 'q()' to quit R. > x <- array(list(0,1,0,1,0,1,0,1,1,1,1,0,0,0,1,1,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,1),dim=c(2,35),dimnames=list(c('A','B '),1:35)) > y <- array(NA,dim=c(2,35),dimnames=list(c('A','B '),1:35)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par6 = '0' > par5 = 'paired' > par4 = 'two.sided' > par3 = '0.95' > par2 = '2' > par1 = '1' > main = 'Two Samples' > #'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 = -0.6269, df = 34, p-value = 0.5349 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -0.2423708 0.1280851 sample estimates: mean of the differences -0.05714286 > (v.t <- var.test(z[,par1],z[,par2],conf.level=par3)) F test to compare two variances data: z[, par1] and z[, par2] F = 0.9935, num df = 34, denom df = 34, p-value = 0.9849 alternative hypothesis: true ratio of variances is not equal to 1 95 percent confidence interval: 0.501466 1.968171 sample estimates: ratio of variances 0.993464 > (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 = -0.6269, df = 34, p-value = 0.5349 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -0.2423708 0.1280851 sample estimates: mean of the differences -0.05714286 > (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 = 22, p-value = 0.5653 alternative hypothesis: true location shift is not equal to 0 Warning messages: 1: In wilcox.test.default(z[, par1], z[, par2], alternative = par4, : cannot compute exact p-value with ties 2: In wilcox.test.default(z[, par1], z[, par2], alternative = par4, : cannot compute exact p-value with zeroes > (ks.t <- ks.test(z[,par1],z[,par2],alternative=par4)) Two-sample Kolmogorov-Smirnov test data: z[, par1] and z[, par2] D = 0.0571, p-value = 1 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 = 0.4857, p-value = 0.0005188 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/rcomp/tmp/1o23g1319721472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > boxplot(mydf, notch=TRUE, ylab='value',main=main) Warning message: In bxp(list(stats = c(0, 0, 0, 1, 1, 0, 0, 1, 1, 1), n = c(35, 35 : some notches went outside hinges ('box'): maybe set notch=FALSE > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/23ldo1319721472.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/rcomp/tmp/3rskf1319721472.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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/rcomp/tmp/46ru11319721472.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$conf.int[2],']',sep='')) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/5v1pl1319721472.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,paste('Wicoxon rank sum test with continuity correction (',par5,')',sep=''),2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'W',header=TRUE) > a<-table.element(a,w.t$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/rcomp/tmp/6yhqs1319721472.tab") > > try(system("convert tmp/1o23g1319721472.ps tmp/1o23g1319721472.png",intern=TRUE)) character(0) > try(system("convert tmp/23ldo1319721472.ps tmp/23ldo1319721472.png",intern=TRUE)) character(0) > try(system("convert tmp/3rskf1319721472.ps tmp/3rskf1319721472.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.360 0.130 1.474