Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
94.8 93.7 95.4 94.8 96.1 96.2 88.7 87.1 91.2 91.6 91.0 88.7 96.6 96.6 91.9 92.1 94.5 92.8 91.8 91.9 96.3 95.1 90.0 89.9 97.0 96.3 97.4 95.5 93.4 94.0 95.0 95.6 95.2 95.3 95.5 94.5 94.3 93.3 94.7 92.4 95.6 95.8 92.4 92.7 91.6 92.0 92.7 92.8 94.6 94.6 94.0 94.2 97.0 96.9 96.6 96.3 93.4 92.3 94.3 92.9 93.7 94.1 91.9 92.6 92.6 92.9 102.8 100.9 92.6 90.6 94.7 94.3 92.3 89.7 95.5 95.9 94.5 93.7 91.2 89.4 96.8 95.9 96.7 96.9 98.0 97.4 92.5 90.7 92.4 92.6 95.0 94.6 94.9 95.0 93.6 93.7 95.7 95.9 94.2 94.1 93.9 92.8 99.9 97.3 94.7 95.0 92.6 90.1 98.3 97.6 93.8 93.6 93.7 93.7 102.3 100.4 99.2 99.0 93.9 93.8 94.7 95.0 90.9 88.5 92.4 92.6 96.9 97.0 95.3 93.6 84.2 82.5 97.4 97.4 94.7 92.6 92.2 92.5 90.5 88.6 97.0 96.9 93.7 93.9 93.8 94.1 93.7 93.2 95.6 96.2 95.9 94.2 96.3 97.4 94.3 94.3 95.8 94.4 99.0 97.1 94.2 91.7 91.5 91.9 93.2 93.4 94.5 94.8 95.3 94.1 93.3 93.9 92.5 90.7 97.1 96.8 95.1 95.9 95.0 95.1 90.2 88.2 90.0 87.7 95.4 94.8 96.1 95.8 92.6 93.2 93.4 93.6 97.4 94.8 96.2 96.0 93.6 93.5 94.1 93.5 96.8 96.5 90.1 87.6 94.6 95.6 93.9 94.0 91.7 89.2 95.7 95.4 98.1 97.9 94.9 94.7 91.4 88.8 94.5 92.0 95.6 95.9 92.4 93.0 99.3 99.4 93.3 93.5 95.0 95.1 99.7 99.5 97.0 97.0 95.7 95.9 94.6 94.9 95.7 95.9 92.3 90.2 91.4 90.3 89.5 87.5 94.7 91.8 95.8 94.5 98.9 98.4 95.1 95.5 93.1 93.2 90.2 90.2 97.3 97.5 89.8 87.8 94.6 93.0 94.7 94.4 94.0 94.4 88.7 89.3 94.0 92.6 96.4 96.4 95.7 95.9 93.4 93.7 97.3 97.0 92.0 91.5 95.5 96.1 93.9 93.9 96.6 96.2 98.0 96.1 94.5 94.8 95.5 95.3 93.3 93.4 94.8 95.0 92.2 90.1 96.7 95.0 94.4 94.9 94.3 93.6 94.5 94.9 90.4 88.1 96.1 95.0 97.5 97.7 93.1 93.3 95.0 94.4 91.6 89.3 93.8 93.9 95.2 95.3 94.8 94.9 93.7 93.1 93.6 93.5 93.6 93.4 93.9 94.2 95.5 94.9 93.8 93.5 94.4 93.9 94.0 93.8 95.7 93.8 93.1 93.1 93.6 95.0 96.0 96.0 94.8 94.4 94.9 95.2 94.6 95.1 89.2 86.3 91.6 91.9 95.3 95.7 95.5 95.6 95.1 95.1 95.9 96.0 97.8 97.8 97.2 94.3 100.6 98.5 93.3 92.2 89.9 90.4 97.5 96.1 92.9 91.3 94.1 94.1 97.6 97.2 101.6 100.8 94.2 94.5 92.7 90.4 93.6 94.0 92.2 92.8 94.2 92.8 92.0 89.5 94.1 94.2 96.0 95.6 94.5 94.5 93.4 93.0 94.5 95.1 91.9 90.0 93.5 93.6 95.8 96.5 93.8 94.2 96.0 96.5 90.8 89.8 88.9 87.3 95.0 95.7 92.4 92.5 94.9 94.4 94.8 92.7 89.6 90.7 94.9 95.2 95.5 96.2 96.1 96.4 95.6 94.3 97.7 98.4 93.9 94.3 95.5 95.4 92.7 92.6 92.0 90.4 95.7 94.0 94.8 93.9 95.8 96.8 92.4 90.7 94.3 92.8 95.6 93.9 93.1 93.5 97.3 96.6 97.7 98.2 98.6 96.7 91.4 89.0 84.5 82.1 94.2 94.6 92.8 92.8 91.9 89.6 93.0 91.1 96.5 95.3 93.5 93.9 96.6 96.9 94.7 95.3 92.9 93.3 94.0 94.7 94.9 94.1 96.7 96.5 90.1 87.9 90.9 91.5 90.8 90.6 93.0 92.3 96.8 95.1 97.4 96.5 89.7 90.2 93.9 94.4 92.0 89.9 95.9 95.4 93.6 93.2 90.8 88.8 94.1 92.4 94.3 94.5 97.5 97.7 98.5 96.6 96.0 95.0 91.4 89.4 96.7 95.1 94.3 94.8 96.6 96.2 85.1 83.1 91.7 89.9 91.0 88.6 91.8 91.8 89.9 90.3 91.6 91.7 89.2 89.3 88.7 88.7 88.2 89.4 94.0 92.3 95.9 96.1 91.0 90.9 100.8 99.0 95.5 95.3 94.9 94.4 96.5 94.4 95.3 95.5 98.4 96.4 95.3 95.8 94.2 94.4 94.3 94.6 99.1 99.3 94.1 93.7 96.4 95.3 95.0 95.1 90.1 90.3 91.6 91.3 93.8 92.4 94.2 92.9 92.8 93.1 94.5 94.6 94.4 93.1 94.6 94.7 95.1 95.4 95.8 95.2 91.9 91.1 96.0 95.8 94.9 95.1 94.6 94.6 94.1 92.1 96.5 95.6 93.3 91.5 95.9 95.1 92.7 92.3 92.0 89.8 90.9 88.8 91.7 92.5 95.4 96.3 94.6 92.8 96.7 96.9 94.7 93.8 95.5 93.6 95.4 93.6 96.9 95.9 93.6 93.4 94.7 93.8 96.0 96.0 91.1 89.0 93.7 93.6 94.8 95.6 92.2 90.5 95.3 95.7 95.0 95.2 93.1 93.1 93.7 93.9 96.8 96.0 98.7 98.6 93.9 93.5 95.3 92.4 92.1 92.3 98.5 96.5 91.1 89.2 94.9 93.0 93.6 94.0 95.9 95.9 97.3 96.9 91.9 90.2 91.7 89.6 97.2 95.6 93.4 93.7 95.9 95.9 96.7 96.9 95.6 96.1 94.6 93.4 96.0 95.8 95.2 95.2 92.4 93.2 97.9 96.0 95.4 95.8 96.2 96.2 97.2 95.8 93.3 93.8 96.1 94.5 95.6 94.7 93.9 93.6 94.2 94.9 98.7 95.7 98.0 98.0
Names of X columns:
Juli Augustus
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) myWlabel <- 'Wilcoxon Signed-Rank Test' if (par5=='unpaired') myWlabel = 'Wilcoxon Rank-Sum Test (Mann–Whitney U test)' a<-table.element(a,paste(myWlabel,' 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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation