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Data X:
26 21 21 23 17 23 4 20 16 15 24 17 20 4 19 19 18 22 18 20 6 19 18 11 20 21 21 8 20 16 8 24 20 24 8 25 23 19 27 28 22 4 25 17 4 28 19 23 4 22 12 20 27 22 20 8 26 19 16 24 16 25 5 22 16 14 23 18 23 4 17 19 10 24 25 27 4 22 20 13 27 17 27 4 19 13 14 27 14 22 4 24 20 8 28 11 24 4 26 27 23 27 27 25 4 21 17 11 23 20 22 8 13 8 9 24 22 28 4 26 25 24 28 22 28 4 20 26 5 27 21 27 4 22 13 15 25 23 25 8 14 19 5 19 17 16 4 21 15 19 24 24 28 7 7 5 6 20 14 21 4 23 16 13 28 17 24 4 17 14 11 26 23 27 5 25 24 17 23 24 14 4 25 24 17 23 24 14 4 19 9 5 20 8 27 4 20 19 9 11 22 20 4 23 19 15 24 23 21 4 22 25 17 25 25 22 4 22 19 17 23 21 21 4 21 18 20 18 24 12 15 15 15 12 20 15 20 10 20 12 7 20 22 24 4 22 21 16 24 21 19 8 18 12 7 23 25 28 4 20 15 14 25 16 23 4 28 28 24 28 28 27 4 22 25 15 26 23 22 4 18 19 15 26 21 27 7 23 20 10 23 21 26 4 20 24 14 22 26 22 6 25 26 18 24 22 21 5 26 25 12 21 21 19 4 15 12 9 20 18 24 16 17 12 9 22 12 19 5 23 15 8 20 25 26 12 21 17 18 25 17 22 6 13 14 10 20 24 28 9 18 16 17 22 15 21 9 19 11 14 23 13 23 4 22 20 16 25 26 28 5 16 11 10 23 16 10 4 24 22 19 23 24 24 4 18 20 10 22 21 21 5 20 19 14 24 20 21 4 24 17 10 25 14 24 4 14 21 4 21 25 24 4 22 23 19 12 25 25 5 24 18 9 17 20 25 4 18 17 12 20 22 23 6 21 27 16 23 20 21 4 23 25 11 23 26 16 4 17 19 18 20 18 17 18 22 22 11 28 22 25 4 24 24 24 24 24 24 6 21 20 17 24 17 23 4 22 19 18 24 24 25 4 16 11 9 24 20 23 5 21 22 19 28 19 28 4 23 22 18 25 20 26 4 22 16 12 21 15 22 5 24 20 23 25 23 19 10 24 24 22 25 26 26 5 16 16 14 18 22 18 8 16 16 14 17 20 18 8 21 22 16 26 24 25 5 26 24 23 28 26 27 4 15 16 7 21 21 12 4 25 27 10 27 25 15 4 18 11 12 22 13 21 5 23 21 12 21 20 23 4 20 20 12 25 22 22 4 17 20 17 22 23 21 8 25 27 21 23 28 24 4 24 20 16 26 22 27 5 17 12 11 19 20 22 14 19 8 14 25 6 28 8 20 21 13 21 21 26 8 15 18 9 13 20 10 4 27 24 19 24 18 19 4 22 16 13 25 23 22 6 23 18 19 26 20 21 4 16 20 13 25 24 24 7 19 20 13 25 22 25 7 25 19 13 22 21 21 4 19 17 14 21 18 20 6 19 16 12 23 21 21 4 26 26 22 25 23 24 7 21 15 11 24 23 23 4 20 22 5 21 15 18 4 24 17 18 21 21 24 8 22 23 19 25 24 24 4 20 21 14 22 23 19 4 18 19 15 20 21 20 10 18 14 12 20 21 18 8 24 17 19 23 20 20 6 24 12 15 28 11 27 4 22 24 17 23 22 23 4 23 18 8 28 27 26 4 22 20 10 24 25 23 5 20 16 12 18 18 17 4 18 20 12 20 20 21 6 25 22 20 28 24 25 4 18 12 12 21 10 23 5 16 16 12 21 27 27 7 20 17 14 25 21 24 8 19 22 6 19 21 20 5 15 12 10 18 18 27 8 19 14 18 21 15 21 10 19 23 18 22 24 24 8 16 15 7 24 22 21 5 17 17 18 15 14 15 12 28 28 9 28 28 25 4 23 20 17 26 18 25 5 25 23 22 23 26 22 4 20 13 11 26 17 24 6 17 18 15 20 19 21 4 23 23 17 22 22 22 4 16 19 15 20 18 23 7 23 23 22 23 24 22 7 11 12 9 22 15 20 10 18 16 13 24 18 23 4 24 23 20 23 26 25 5 23 13 14 22 11 23 8 21 22 14 26 26 22 11 16 18 12 23 21 25 7 24 23 20 27 23 26 4 23 20 20 23 23 22 8 18 10 8 21 15 24 6 20 17 17 26 22 24 7 9 18 9 23 26 25 5 24 15 18 21 16 20 4 25 23 22 27 20 26 8 20 17 10 19 18 21 4 21 17 13 23 22 26 8 25 22 15 25 16 21 6 22 20 18 23 19 22 4 21 20 18 22 20 16 9 21 19 12 22 19 26 5 22 18 12 25 23 28 6 27 22 20 25 24 18 4 24 20 12 28 25 25 4 24 22 16 28 21 23 4 21 18 16 20 21 21 5 18 16 18 25 23 20 6 16 16 16 19 27 25 16 22 16 13 25 23 22 6 20 16 17 22 18 21 6 18 17 13 18 16 16 4 20 18 17 20 16 18 4
Names of X columns:
I1 I2 I3 E1 E2 E3 A
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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