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Data X:
0 50 1 62 0 54 1 71 1 54 1 65 0 73 1 52 1 84 1 42 1 66 1 65 1 78 0 73 0 75 0 72 1 66 0 70 1 61 0 81 1 71 1 69 0 71 1 72 1 68 1 70 1 68 0 61 1 67 0 76 0 70 0 60 1 77 1 72 1 69 1 71 1 62 0 70 1 64 1 58 0 76 1 52 1 59 1 68 1 76 1 65 0 67 1 59 1 69 0 76 1 63 1 75 1 63 1 60 1 73 1 63 1 70 0 75 1 66 0 63 1 63 1 64 0 70 0 75 1 61 0 60 1 62 0 73 1 61 1 66 0 64 0 59 0 64 0 60 1 56 1 66 0 78 1 53 0 67 1 59 0 66 0 68 1 71 0 66 0 73 0 72 1 71 0 59 1 64 1 66 0 78 0 68 0 73 1 62 1 65 1 68 0 65 1 60 0 71 1 65 1 68 1 64 1 74 1 69 0 76 1 68 1 72 1 67 0 63 0 59 0 73 0 66 0 62 0 69 1 66 1 51 1 56 1 67 1 69 0 57 1 56 1 55 0 63 1 67 0 65 0 47 1 76 1 64 1 68 1 64 1 65 1 71 1 63 1 60 0 68 1 72 1 70 1 61 1 61 1 62 1 71 0 71 1 51 1 56 1 70 1 73 1 76 0 59 0 68 0 48 1 52 0 59 0 60 0 59 1 57 0 79 1 60 1 60 0 59 1 62 1 59 1 61 0 71 0 57 0 66 0 63 1 69 0 58 1 59 0 48 1 66 0 73 1 67 0 61 0 68 1 75 0 62 1 69 1 58 1 60 1 74 1 55 0 62 1 63 0 69 0 58 0 58 1 68 0 72 1 62 0 62 0 65 0 69 0 66 1 72 1 62 1 75 1 58 0 66 0 55 1 47 0 72 0 62 0 64 0 64 1 19 1 50 0 68 0 70 1 79 0 69 1 71 1 48 1 66 0 73 1 74 1 66 1 71 0 74 0 78 0 75 1 53 1 60 0 50 1 70 1 69 0 65 0 78 0 78 1 59 1 72 0 70 0 63 0 63 1 71 1 74 0 67 0 66 0 62 1 80 1 73 1 67 1 61 0 73 1 74 1 32 1 69 0 69 0 84 1 64 0 58 1 60 1 59 1 78 0 57 1 60 0 68 1 68 1 73 0 69 1 67 0 60 1 65 0 66 1 74 0 81 0 72 1 55 1 49 0 74 1 53 1 64 0 65 1 57 0 51 0 80 1 67 1 70 0 74 1 75 0 70 0 69 1 65 0 55 0 71 1 65 1 69 1 48 0 69 1 68 1 74 1 67 1 65 0 63 1 74 0 39 0 68 1 69 0 68 1 63 0 67 0 70 1 68 0 66 1 70 1 78 0 59 0 62 0 75 1 74 0 73 1 62 1 69 1 65 1 67 0 73 1 52 0 61 1 53 0 63 0 78 0 65 0 77 0 69 0 68 1 76 1 63 1 41 0 76 0 67 0 69 0 59 0 73 1 72 1 52 1 65 1 63 0 78 1 56 0 68 1 56 1 64 0 68 1 75 0 67 0 55 0 73 0 66 0 75 0 77 1 65 0 75 0 57 1 61 1 71 1 72 1 62 0 66 1 66 1 63 0 60 0 64 0 74 0 59 1 71 0 69 0 63 0 73 0 55 0 77 0 70 1 64 1 78 1 60 0 66 0 77 1 68 0 78 1 68 1 60 1 65 1 64 1 69 0 72 0 50 0 72 0 71 0 80 1 74 0 64 0 69 1 76 0 75 0 79 1 73 0 60 1 76 1 55 0 53 1 62 0 69 1 78 0 68 1 67 1 75 1 59 0 73 1 70 1 59 0 64 1 63 1 67 1 58 1 71 0 79 1 53 0 76 0 66 1 64 0 57 1 67 1 72 0 58 0 74 1 57 1 62 1 74 1 54 0 62 1 66 1 64 1 74 1 71 0 66 0 66 1 63 0 65 1 70 1 66 0 66 1 78 0 77 1 72 0 65 0 67 1 72 1 58 1 84 1 67 0 84 0 58 1 63 0 75 1 55 0 72 1 58 1 69 1 54 1 58 1 67 1 77 1 80 1 67 0 75 1 71 0 72 0 75 1 79 1 76 1 72 1 81 1 52 1 76 1 60 0 72 1 77 1 64 1 67 0 72 1 79 1 40 1 71 1 73 0 75 1 70 1 66 0 66 0 73 1 74 1 58 1 51 1 75 0 70 1 50 0 64 1 77 1 71
Names of X columns:
G E
Column number of first sample
Column number of second sample
Confidence
Alternative
two.sided
two.sided
less
greater
Are observations paired?
paired
unpaired
paired
Null Hypothesis
Chart options
Title:
R Code
par6 <- '0.0' par5 <- 'unpaired' 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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Big Analytics Cloud Computing Center
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