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Data X:
NA 12.9 NA 7.4 12.2 NA NA 12.8 7.4 NA 6.7 NA 12.6 NA NA 14.8 13.3 NA 11.1 NA 8.2 NA 11.4 NA 6.4 NA 10.6 NA NA 12.0 NA 6.3 NA 11.3 11.9 NA NA 9.3 9.6 NA NA 10.0 6.4 NA 13.8 NA NA 10.8 13.8 NA 11.7 NA 10.9 NA 16.1 NA NA 13.4 9.9 NA NA 11.5 NA 8.3 NA 11.7 6.1 NA 9.0 NA 9.7 NA 10.8 NA 10.3 NA NA 10.4 12.7 NA 9.3 NA NA 11.8 5.9 NA 11.4 NA 13.0 NA 10.8 NA 12.3 NA NA 11.3 11.8 NA 7.9 NA NA 12.7 12.3 NA 11.6 NA 6.7 NA 10.9 NA 12.1 NA 13.3 NA 10.1 NA NA 5.7 14.3 NA NA 8.0 13.3 NA 9.3 NA NA 12.5 NA 7.6 15.9 NA NA 9.2 9.1 NA NA 11.1 13.0 NA 14.5 NA NA 12.2 NA 12.3 NA 11.4 NA 8.8 14.6 NA 7.3 NA NA 12.6 NA NA NA 13.0 12.6 NA NA 13.2 NA 9.9 7.7 NA NA 10.5 NA 13.4 NA 10.9 4.3 NA NA 10.3 11.8 NA 11.2 NA NA 11.4 NA 8.6 NA 13.2 12.6 NA 5.6 NA 9.9 NA NA 8.8 7.7 NA NA 9.0 7.3 NA 11.4 NA 13.6 NA 7.9 NA 10.7 NA NA 10.3 8.3 NA 9.6 NA 14.2 NA NA 8.5 NA 13.5 NA 4.9 NA 6.4 NA 9.6 NA 11.6 11.1 NA 4.4 NA 12.7 NA 18.1 NA 17.9 NA NA 16.6 12.6 NA 17.1 NA NA 19.1 16.1 NA NA 13.4 NA 18.4 14.7 NA 10.6 NA 12.6 NA 16.2 NA 13.6 NA 18.9 NA 14.1 NA 14.5 NA NA 16.2 14.8 NA 14.8 NA 12.5 NA 12.7 NA 17.4 NA 8.6 NA NA 18.4 16.1 NA 11.6 NA 17.8 NA 15.3 NA 17.7 NA NA 15.6 NA 16.4 NA 17.7 13.6 NA NA 11.7 NA 14.4 NA 14.8 18.3 NA NA 9.9 16.0 NA 18.3 NA NA 16.9 14.6 NA 13.9 NA 19.0 NA NA 15.6 NA 14.9 NA 11.8 NA 18.5 15.9 NA NA 17.1 16.1 NA NA 19.9 11.0 NA NA 18.5 15.1 NA NA 15.0 NA 11.4 16.0 NA NA 18.1 14.6 NA 15.4 NA 15.4 NA 17.6 NA 13.4 NA NA 19.1 15.4 NA NA 7.6 NA 13.4 NA 13.9 19.1 NA NA 15.3 12.9 NA NA 16.1 NA 17.4 NA 13.2 NA 12.2 12.6 NA 10.4 NA 15.4 NA 9.6 NA NA 18.2 NA 13.6 14.9 NA NA 14.8 NA 14.1 NA 14.9 NA 16.3 19.3 NA 13.6 NA NA 13.6 NA 15.7 12.8 NA NA 14.6 9.9 NA 12.7 NA 11.9 NA NA 19.2 16.6 NA 11.2 NA 15.3 NA NA 11.9 NA 13.2 NA 16.4 12.4 NA 15.9 NA NA 14.4 18.2 NA 11.2 NA NA 15.7 NA 17.8 NA 7.7 12.4 NA 15.6 NA NA 19.3 NA 15.2 NA 17.1 15.6 NA 18.4 NA NA 19.1 NA 18.6 NA 19.1 13.1 NA 12.9 NA 9.5 NA 4.5 NA NA 11.9 13.6 NA 11.7 NA 12.4 NA NA 13.4 NA 11.4 14.9 NA NA 19.9 17.8 NA 11.2 NA 14.6 NA NA 17.6 14.1 NA NA 16.1 13.4 NA 11.9 NA NA 12.0 14.8 NA NA 15.2 13.2 NA NA 16.9 7.9 NA NA 7.7 NA 12.6 7.9 NA 11.0 NA NA 12.4 10.0 NA 14.9 NA NA 16.7 13.4 NA NA 14.0 NA 15.7 16.9 NA 11.0 NA NA 15.4 12.2 NA NA 15.1 NA 17.8 15.2 NA NA 14.6 NA 16.7 8.1 NA
Names of X columns:
Male Female
Column number of first sample
Column number of second sample
Confidence
Alternative
two.sided
two.sided
less
greater
Are observations paired?
unpaired
unpaired
paired
Null Hypothesis
Chart options
Title:
R Code
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)) (v.t <- var.test(z[,par1],z[,par2],conf.level=par3)) (r.w <- t.test(z[,par1],z[,par2],var.equal=FALSE,alternative=par4,paired=paired,mu=par6,conf.level=par3)) (w.t <- wilcox.test(z[,par1],z[,par2],alternative=par4,paired=paired,mu=par6,conf.level=par3)) (ks.t <- ks.test(z[,par1],z[,par2],alternative=par4)) 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)) mydf <- data.frame(cbind(z[,par1],z[,par2])) colnames(mydf) <- c('Variable 1','Variable 2') bitmap(file='test1.png') boxplot(mydf, notch=TRUE, ylab='value',main=main) dev.off() bitmap(file='test2.png') qqnorm(z[,par1],main='Normal QQplot - Variable 1') qqline(z[,par1]) dev.off() bitmap(file='test3.png') qqnorm(z[,par2],main='Normal QQplot - Variable 2') qqline(z[,par2]) dev.off() load(file='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$conf.int[2],']',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,paste('Welch Two Sample t-test (',par5,')',sep=''),2,TRUE) a<-table.row.end(a) if(!paired){ a<-table.row.start(a) a<-table.element(a,'Mean of Sample 1',header=TRUE) a<-table.element(a,r.w$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='mytable1.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='mytable2.tab')
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Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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