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Data X:
NA 18 NA 7 31 NA NA 39 46 NA 31 NA 67 NA NA 35 52 NA 77 NA 37 NA 32 NA 36 NA 38 NA NA 69 NA 21 NA 26 54 NA NA 36 42 NA NA 23 34 NA 112 NA NA 35 47 NA 47 NA 37 NA 109 NA NA 24 20 NA NA 22 NA 23 NA 32 7 NA 30 NA 92 NA 43 NA 55 NA NA 16 49 NA 71 NA NA 43 29 NA 56 NA 46 NA 19 NA 23 NA NA 59 30 NA 61 NA NA 7 38 NA 32 NA 16 NA 19 NA 22 NA 48 NA 23 NA NA 26 33 NA NA 9 24 NA 34 NA NA 48 NA 18 43 NA NA 33 28 NA NA 71 26 NA 67 NA NA 34 NA 80 NA 29 NA 16 59 NA 58 NA NA 32 47 NA NA 43 38 NA NA 29 NA 36 32 NA NA 35 NA 21 NA 29 12 NA NA 37 37 NA 47 NA NA 51 NA 32 NA 21 13 NA 14 NA -2 NA NA 20 24 NA NA 11 23 NA 24 NA 14 NA 52 NA 15 NA NA 23 19 NA 35 NA 24 NA NA 39 NA 29 NA 13 NA 8 NA 18 NA 24 19 NA 22.56555556 NA 16.41472222 NA 33.3825 NA 31.6025 NA NA 36.96916667 13.61 NA 51.62388889 NA NA 75.25916667 71.99777778 NA NA 14.96 NA 28.56638889 12.61611111 NA 40.04277778 NA 18.85388889 NA 23.93861111 NA 120.6683333 NA 93.31277778 NA 35.92777778 NA 23.28805556 NA NA 85.22722222 40.79166667 NA 46.36555556 NA 18.22972222 NA 35.3275 NA 16.83055556 NA 3.585833333 NA NA 28.13083333 44.04666667 NA 9.845 NA 37.73777778 NA 57.42638889 NA 22.93833333 NA NA 25.59388889 NA 35.69694444 NA 22.08305556 40.14444444 NA NA 18.18 NA 31.18805556 NA 11.47638889 37.92194444 NA NA 24.2275 36.77277778 NA 36.81194444 NA NA 22.07194444 14.94416667 NA 1.893611111 NA 43.25694444 NA NA 30.76888889 NA 29.16083333 NA 45.08055556 NA 24.85666667 4.036388889 NA NA 31.31666667 -3.818055556 NA NA 66.33777778 61.31722222 NA NA 31.84222222 31.40166667 NA NA 39.25305556 NA 19.14055556 30.70916667 NA NA 35.62861111 42.40888889 NA 20.63166667 NA 20.63166667 NA 24.88 NA 31.55611111 NA NA 25.70361111 28.01111111 NA NA 31.75583333 NA 41.02972222 NA 29.16111111 32.91 NA NA 16.75527778 13.00861111 NA NA 32.29111111 NA 29.70222222 NA 34.21527778 NA 59.21638889 12.92888889 NA 23.16277778 NA 10.40527778 NA 5.150555556 NA NA 31.27722222 NA 19.32333333 31.69833333 NA NA 30.48638889 NA 25.14305556 NA 48.47555556 NA 34.77194444 67.28166667 NA 15.245 NA NA 22.45166667 NA 17.83222222 33.32416667 NA NA 46.3975 23.83722222 NA 13.77194444 NA 23.18611111 NA NA 11.84277778 38.21722222 NA 11.76138889 NA 28.34138889 NA NA 40.84694444 NA 12.36694444 NA 31.105 33.35916667 NA 34.38055556 NA NA 41.03138889 21.30944444 NA 19.74055556 NA NA 44.33722222 NA 52.20944444 NA 6.740277778 29.30888889 NA 10.78361111 NA NA 26.40666667 NA 23.60333333 NA 7.179722222 60.27833333 NA 12.84222222 NA NA 20.37888889 NA 52.31583333 NA 28.28055556 25.31222222 NA 39.10944444 NA 9.040833333 NA 18.78444444 NA NA 13.12972222 60.17222222 NA 19.14 NA 33.89555556 NA NA 13.95805556 NA 16.59083333 45.1025 NA NA 66.33777778 24.47666667 NA 48.28305556 NA 29.14722222 NA NA -2.452222222 51.39916667 NA NA 1.588888889 23.59138889 NA 39.81083333 NA NA 19.58194444 18.73833333 NA NA 16.43333333 19.64138889 NA NA 40.1325 27.03277778 NA NA 25.36333333 NA 48.6925 39.39777778 NA 61.31722222 NA NA 19.37555556 67.26638889 NA 45.1025 NA NA 30.18444444 7.915555556 NA NA 19.48916667 NA 51.92583333 22.1425 NA 17.24083333 NA NA 32.63333333 34.11888889 NA NA 21.92333333 NA 29.59833333 24.94833333 NA NA 37.68388889 NA 25.81805556 13.03722222 NA
Names of X columns:
PRH_Male PRH_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
par6 <- '0' par5 <- 'paired' par4 <- 'two.sided' par3 <- '0.95' par2 <- '2' par1 <- '1' 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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