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Type 'q()' to quit R. > x <- array(list(35.323 + ,41.667 + ,35.478 + ,18.109 + ,4.39 + ,18.145 + ,22.173 + ,18.439 + ,28.021 + ,51.202 + ,13.962 + ,33.01 + ,40.174 + ,81.101 + ,16.065 + ,21.223 + ,10.603 + ,26.848 + ,34.811 + ,49.218 + ,69.064 + ,18.673 + ,14.786 + ,35.802 + ,89.232 + ,33.974 + ,15.173 + ,36.972 + ,241.66 + ,53.976 + ,8.752 + ,15.467 + ,60.535 + ,23.843 + ,60.535 + ,18.062 + ,26.052 + ,68.125 + ,30.669 + ,23.937 + ,86 + ,66.659 + ,10.632 + ,24.112 + ,4.928 + ,48.172 + ,35.723 + ,13.891 + ,40.424 + ,20.966 + ,9.706 + ,26.81 + ,26.532 + ,52.004 + ,35.681 + ,32.354 + ,31.479 + ,57.393 + ,250.234 + ,194.731 + ,49.469 + ,20.407 + ,42.951 + ,13.681 + ,43.402 + ,79.659 + ,56.95 + ,53.48 + ,17.313 + ,85.903 + ,25.658 + ,35.351 + ,32.048 + ,1.455 + ,19.797 + ,32.789 + ,31.317 + ,35.162 + ,22.708 + ,38.095 + ,27.128 + ,24.5 + ,26.529 + ,302.912 + ,28.392 + ,16.488 + ,9.415 + ,10.831 + ,91.076 + ,33.189 + ,57.751 + ,7.314 + ,8.236 + ,54.179 + ,6.906 + ,145.846 + ,37.877 + ,23.525 + ,283.801 + ,21.804 + ,5.974 + ,26.301 + ,3.441 + ,41.33 + ,51.987 + ,60.31 + ,13.22 + ,34.256 + ,18.187 + ,22.561 + ,21.29 + ,13.151 + ,5.686 + ,27.426 + ,4.944 + ,15.355 + ,50.494 + ,13.82 + ,19.172 + ,27.257 + ,20.573 + ,23.556 + ,42.042 + ,50.108 + ,25.027 + ,13.474 + ,32.36 + ,50.202 + ,6.193 + ,37.7 + ,6.343 + ,23.025 + ,48.578 + ,21.564 + ,33.697 + ,19.172 + ,21.075 + ,60.5 + ,33.686 + ,40.838 + ,13.491 + ,106.637 + ,35.897 + ,49.094 + ,14.667 + ,18.56 + ,10.5 + ,13.338 + ,48.267 + ,41.559 + ,32.45 + ,10.951 + ,57.095 + ,19.105 + ,47.21 + ,110.349 + ,34.985 + ,18.158 + ,87.357 + ,18.187 + ,28.33 + ,26.244) + ,dim=c(2 + ,98) + ,dimnames=list(c('Timing_first_click_Man' + ,'Timing_First_click_Vrouw') + ,1:98)) > y <- array(NA,dim=c(2,98),dimnames=list(c('Timing_first_click_Man','Timing_First_click_Vrouw'),1:98)) > 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' > 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 = 0.0462, df = 194, p-value = 0.9632 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -12.23305 12.81936 sample estimates: mean of x mean of y 40.01981 39.72665 > (v.t <- var.test(z[,par1],z[,par2],conf.level=par3)) F test to compare two variances data: z[, par1] and z[, par2] F = 1.5806, num df = 97, denom df = 97, p-value = 0.02516 alternative hypothesis: true ratio of variances is not equal to 1 95 percent confidence interval: 1.059115 2.358788 sample estimates: ratio of variances 1.580579 > (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 = 0.0462, df = 184.654, p-value = 0.9632 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -12.23703 12.82334 sample estimates: mean of x mean of y 40.01981 39.72665 > (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 = 4360, p-value = 0.2662 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 = 0.1837, p-value = 0.07331 alternative hypothesis: two-sided Warning message: In ks.test(z[, par1], z[, par2], alternative = par4) : cannot compute exact 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 = 0.1837, p-value = 0.07331 alternative hypothesis: two-sided Warning message: In ks.test(newsam1, newsam2, alternative = par4) : cannot compute exact p-values with ties > mydf <- data.frame(cbind(z[,par1],z[,par2])) > colnames(mydf) <- c('Variable 1','Variable 2') > postscript(file="/var/fisher/rcomp/tmp/1lr0l1355226913.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/26a5l1355226913.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/3zuts1355226913.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$conf.int[2],']',sep='')) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/4013z1355226914.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,paste('Welch Two Sample t-test (',par5,')',sep=''),2,TRUE) > a<-table.row.end(a) > if(!paired){ + a<-table.row.start(a) + a<-table.element(a,'Mean of Sample 1',header=TRUE) + a<-table.element(a,r.w$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/5hsml1355226914.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/6pxjp1355226914.tab") > > try(system("convert tmp/1lr0l1355226913.ps tmp/1lr0l1355226913.png",intern=TRUE)) character(0) > try(system("convert tmp/26a5l1355226913.ps tmp/26a5l1355226913.png",intern=TRUE)) character(0) > try(system("convert tmp/3zuts1355226913.ps tmp/3zuts1355226913.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.906 0.569 2.472