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Data X:
26 50 51 68 57 62 37 54 67 71 43 54 52 65 52 73 43 52 84 84 67 42 49 66 70 65 52 78 58 73 68 75 62 72 43 66 56 70 56 61 74 81 65 71 63 69 58 71 57 72 63 68 53 70 57 68 51 61 64 67 53 76 29 70 54 60 51 77 58 72 43 69 51 71 53 62 54 70 56 64 61 58 47 76 39 52 48 59 50 68 35 76 30 65 68 67 49 59 61 69 67 76 47 63 56 75 50 63 43 60 67 73 62 63 57 70 41 75 54 66 45 63 48 63 61 64 56 70 41 75 43 61 53 60 44 62 66 73 58 61 46 66 37 64 51 59 51 64 56 60 66 56 45 66 37 78 59 53 42 67 38 59 66 66 34 68 53 71 49 66 55 73 49 72 59 71 40 59 58 64 60 66 63 78 56 68 54 73 52 62 34 65 69 68 32 65 48 60 67 71 58 65 57 68 42 64 64 74 58 69 66 76 26 68 61 72 52 67 51 63 55 59 50 73 60 66 56 62 63 69 61 66 52 51 16 56 46 67 56 69 52 57 55 56 50 55 59 63 60 67 52 65 44 47 67 76 52 64 55 68 37 64 54 65 72 71 51 63 48 60 60 68 50 72 63 70 33 61 67 61 46 62 54 71 59 71 61 51 33 56 47 70 69 73 52 76 55 59 55 68 41 48 73 52 51 59 52 60 50 59 51 57 60 79 56 60 56 60 29 59 66 62 66 59 73 61 55 71 64 57 40 66 46 63 58 69 43 58 61 59 51 48 50 66 52 73 54 67 66 61 61 68 80 75 51 62 56 69 56 58 56 60 53 74 47 55 25 62 47 63 46 69 50 58 39 58 51 68 58 72 35 62 58 62 60 65 62 69 63 66 53 72 46 62 67 75 59 58 64 66 38 55 50 47 48 72 48 62 47 64 66 64 47 19 63 50 58 68 44 70 51 79 43 69 55 71 38 48 56 66 45 73 50 74 54 66 57 71 60 74 55 78 56 75 49 53 37 60 43 50 59 70 46 69 51 65 58 78 64 78 53 59 48 72 51 70 47 63 59 63 62 71 62 74 51 67 64 66 52 62 67 80 50 73 54 67 58 61 56 73 63 74 31 32 65 69 71 69 50 84 57 64 47 58 54 60 47 59 57 78 43 57 41 60 63 68 63 68 56 73 51 69 50 67 22 60 41 65 59 66 56 74 66 81 53 72 42 55 52 49 54 74 44 53 62 64 53 65 50 57 36 51 76 80 66 67 62 70 59 74 47 75 55 70 58 69 60 65 44 55 57 71 45 65 58 69 51 48 57 69 30 68 46 74 51 67 56 65 58 63 44 74 14 39 53 68 42 69 49 68 44 63 62 67 30 70 46 68 56 66 50 70 54 78 48 59 55 62 35 75 55 74 41 73 59 62 54 69 66 65 55 67 45 73 51 52 47 61 42 53 53 63 53 78 41 65 55 77 55 69 46 68 63 76 43 63 65 41 59 76 39 67 44 69 60 59 57 73 67 72 52 52 52 65 69 63 46 78 46 56 53 68 40 56 70 64 54 68 77 75 45 67 60 55 47 73 50 66 66 75 60 77 41 65 53 75 34 57 51 61 69 71 60 72 45 62 58 66 39 66 51 63 52 60 49 64 63 74 44 59 51 71 52 69 60 63 53 73 53 55 52 77 31 70 51 64 65 78 51 60 49 66 61 77 58 68 62 78 54 68 52 60 72 65 50 64 65 69 53 72 56 50 63 72 62 71 66 80 50 74 45 64 58 69 52 76 53 75 68 79 59 73 58 60 52 76 45 55 58 53 70 62 69 69 71 78 46 68 58 67 39 75 46 59 64 73 67 70 44 59 54 64 41 63 68 67 63 58 57 71 61 79 39 53 69 76 64 66 38 64 59 57 51 67 59 72 51 58 65 74 47 57 50 62 57 74 21 54 47 62 51 66 37 64 67 74 43 71 58 66 51 66 40 63 41 65 58 70 64 66 64 66 58 78 50 77 59 72 55 65 59 67 58 72 41 58 56 84 63 67 77 84 60 58 58 63 64 75 47 55 46 72 62 58 60 69 50 54 46 58 44 67 58 77 56 80 43 67 54 75 54 71 56 72 65 75 66 79 62 76 58 72 67 81 25 52 56 76 53 60 56 72 59 77 46 64 49 67 56 72 76 79 33 40 49 71 53 73 58 75 72 70 51 66 42 66 69 73 51 74 54 58 52 51 59 75 51 70 67 50 64 64 58 77
Names of X columns:
int ext
Column number of first sample
Column number of second sample
Confidence
Alternative
two.sided
less
greater
Are observations paired?
unpaired
paired
Null Hypothesis
Chart options
Title:
R Code
par6 <- '0.0' 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('Totale intrinsieke motivatie','Totale extrinsieke motivatie') 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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