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Data X:
0 26 50 1 57 62 0 37 54 1 67 71 1 43 54 1 52 65 0 52 73 1 43 52 1 84 84 1 67 42 1 49 66 1 70 65 1 52 78 0 58 73 0 68 75 0 62 72 1 43 66 0 56 70 1 56 61 0 74 81 1 65 71 1 63 69 0 58 71 1 57 72 1 63 68 1 53 70 1 57 68 0 51 61 1 64 67 0 53 76 0 29 70 0 54 60 1 58 72 1 43 69 1 51 71 1 53 62 0 54 70 1 56 64 1 61 58 0 47 76 1 39 52 1 48 59 1 50 68 1 35 76 1 30 65 0 68 67 1 49 59 1 61 69 0 67 76 1 47 63 1 56 75 1 50 63 1 43 60 1 67 73 1 62 63 1 57 70 0 41 75 1 54 66 0 45 63 1 48 63 1 61 64 0 56 70 0 41 75 1 43 61 0 53 60 1 44 62 0 66 73 1 58 61 1 46 66 0 37 64 0 51 59 0 51 64 0 56 60 1 66 56 0 37 78 1 59 53 0 42 67 1 38 59 0 66 66 0 34 68 1 53 71 0 49 66 0 55 73 0 49 72 1 59 71 0 40 59 1 58 64 1 60 66 0 63 78 0 56 68 0 54 73 1 52 62 1 34 65 1 69 68 0 32 65 1 48 60 0 67 71 1 58 65 1 57 68 1 42 64 1 64 74 1 58 69 0 66 76 1 26 68 1 61 72 1 52 67 0 51 63 0 55 59 0 50 73 0 60 66 0 56 62 0 63 69 1 61 66 1 52 51 1 16 56 1 46 67 1 56 69 0 52 57 1 55 56 1 50 55 0 59 63 1 60 67 0 52 65 0 44 47 1 67 76 1 52 64 1 55 68 1 37 64 1 54 65 1 72 71 1 51 63 1 48 60 0 60 68 1 50 72 1 63 70 1 33 61 1 67 61 1 46 62 1 54 71 0 59 71 1 61 51 1 33 56 1 47 70 1 69 73 1 52 76 0 55 68 0 41 48 1 73 52 0 52 60 0 50 59 1 51 57 0 60 79 1 56 60 1 56 60 0 29 59 1 66 62 1 66 59 1 73 61 0 55 71 0 64 57 0 40 66 0 46 63 1 58 69 0 43 58 1 61 59 0 51 48 1 50 66 0 52 73 1 54 67 0 66 61 0 61 68 1 80 75 0 51 62 1 56 69 1 56 58 1 56 60 1 53 74 1 47 55 0 25 62 1 47 63 0 46 69 0 50 58 0 39 58 1 51 68 0 58 72 1 35 62 0 58 62 0 60 65 0 62 69 0 63 66 1 53 72 1 46 62 1 67 75 1 59 58 0 64 66 0 38 55 1 50 47 0 48 72 0 48 62 0 47 64 0 66 64 1 47 19 1 63 50 0 58 68 0 44 70 1 51 79 0 43 69 1 55 71 1 38 48 0 45 73 1 50 74 1 54 66 1 57 71 0 60 74 0 55 78 0 56 75 1 49 53 1 37 60 1 59 70 1 46 69 0 51 65 0 58 78 0 64 78 1 53 59 1 48 72 0 51 70 0 47 63 0 59 63 1 62 71 1 62 74 0 51 67 0 64 66 0 52 62 1 67 80 1 50 73 1 54 67 1 58 61 0 56 73 1 63 74 1 31 32 1 65 69 0 71 69 0 50 84 1 57 64 0 47 58 1 47 59 1 57 78 0 43 57 1 41 60 0 63 68 1 63 68 1 56 73 0 51 69 1 50 67 0 22 60 1 41 65 0 59 66 1 56 74 0 66 81 0 53 72 1 42 55 1 52 49 0 54 74 1 44 53 1 62 64 0 53 65 1 50 57 0 36 51 0 76 80 1 66 67 1 62 70 0 59 74 1 47 75 0 55 70 0 58 69 1 60 65 0 44 55 0 57 71 1 45 65
Names of X columns:
gender AMS.I AMS.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 <- '' par5 <- 'paired' par4 <- 'two.sided' par3 <- '0,95' par2 <- '3' par1 <- '2' 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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