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Data X:
0.56 NA 0.79 NA NA 0.68 0.66 NA NA 0.37 NA 0.71 NA 0.35 0.55 NA NA 0.76 NA 0.49 NA 0.56 NA 0.60 NA 0.44 NA 0.55 0.58 NA 0.40 NA 0.42 NA NA 0.58 0.64 NA NA 0.58 0.44 NA NA 0.46 NA 0.64 0.59 NA NA 0.54 NA 0.71 NA 0.20 NA 0.89 0.55 NA NA 0.71 0.48 NA 0.49 NA 0.58 NA NA 0.78 NA 0.71 NA 0.51 NA 0.65 NA 0.68 0.24 NA NA 0.36 NA 0.65 0.79 NA NA 0.67 NA 0.74 NA 0.72 NA 0.73 NA 0.58 0.67 NA NA 0.43 NA 0.59 0.43 NA NA 0.80 NA 0.74 NA 0.43 NA 0.72 NA 0.50 NA 0.45 NA 0.88 0.67 NA NA 0.32 0.20 NA NA 0.84 NA 0.83 0.65 NA 0.74 NA NA 0.53 0.58 NA NA 0.65 0.64 NA NA 0.60 NA 0.52 0.53 NA 0.73 NA 0.52 NA 0.61 NA NA 0.73 NA 0.79 0.29 NA NA 0.86 0.37 NA NA 0.68 0.52 NA 0.26 NA NA 0.74 0.72 NA 0.24 NA 0.71 NA NA 0.59 0.27 NA NA 0.57 NA 0.51 0.69 NA 0.69 NA 0.50 NA NA 0.63 NA 0.65 NA 0.54 0.69 NA NA 0.52 0.53 NA NA 0.74 NA 0.73 NA 0.75 NA 0.70 NA 0.69 0.57 NA NA 0.14 NA 0.42 NA 0.48 0.27 NA 0.21 NA 0.41 NA 0.56 NA 0.44 NA 0.52 NA NA 0.59 NA 0.73 NA 0.79 NA 0.67 NA 0.88 0.96 NA NA 0.43 NA 0.84 0.81 NA NA 0.67 0.45 NA 0.58 NA NA 0.70 NA 0.61 NA 0.44 NA 0.54 NA 0.41 NA 0.66 NA 0.83 NA 0.88 0.40 NA NA 0.54 NA 0.60 NA 0.57 NA 0.59 NA 0.81 NA 0.51 0.65 NA NA 0.59 NA 0.68 NA 0.65 NA 0.06 NA 0.74 0.29 NA 0.73 NA 0.54 NA NA 0.39 0.27 NA 0.40 NA 0.20 NA NA 0.85 0.42 NA NA 0.68 NA 0.72 0.52 NA NA 0.78 NA 0.60 NA 0.93 0.73 NA 0.81 NA 0.51 NA 0.86 NA NA 0.67 0.50 NA NA 0.74 0.85 NA NA 0.75 0.83 NA NA 0.82 0.58 NA 0.72 NA NA 0.89 0.51 NA NA 0.75 NA 0.84 NA 0.84 NA 0.59 NA 0.64 0.45 NA NA 0.57 0.58 NA 0.72 NA 0.38 NA NA 0.68 0.45 NA NA 0.55 0.73 NA 0.73 NA 0.73 NA 0.71 NA NA 0.38 NA 0.79 NA 0.32 NA 0.62 0.42 NA 0.45 NA NA 0.97 0.67 NA 0.08 NA 0.49 NA 0.66 NA NA 0.67 NA 0.55 0.55 NA 0.49 NA NA 0.56 0.69 NA NA 0.47 NA 0.68 NA 0.43 0.00 NA NA 0.48 NA 0.77 NA 0.71 0.43 NA 0.50 NA 0.68 NA NA 0.34 NA 0.47 0.33 NA NA 0.80 NA 0.74 0.82 NA 0.57 NA 0.46 NA NA 0.91 NA 0.41 0.64 NA 0.58 NA 0.45 NA NA 0.77 NA 0.67 0.53 NA 0.07 NA 0.65 NA NA 0.76 NA 0.56 NA 0.07 NA 0.72 0.61 NA NA 0.47 NA 0.06 NA 0.37 0.76 NA 0.47 NA NA 0.55 0.85 NA NA 0.77 NA 0.79 NA 0.70 0.46 NA NA 0.51 0.65 NA NA 0.57 NA 0.68 0.52 NA NA 0.70 0.46 NA NA 0.88 0.76 NA NA 0.74 0.56 NA 0.47 NA NA 0.44 NA 0.75 0.78 NA NA 0.26 NA 0.55 0.49 NA NA 0.81 0.45 NA 0.39 NA NA 0.89 NA 0.66 0.34 NA NA 0.84 0.05 NA 0.79 NA NA 0.60 0.69 NA 0.58 NA NA 0.66
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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