Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
0.06 0.24 0.12 0.73 0.61 0.53 0.89 0.44 0.59 0.45 0.31 0.07 0.67 0.28 0.6 0.45 0.23 0.73 0.44 0.41 0.6 0.67 0.21 0.45 0.66 0.06 0.39 0.33 0.78 0.42 0.57 0.41 0.38 0.52 0.59 0.49 0.48 0.55 0.44 0.13 0.3 0.45 0.63 0.19 0.43 0.2 0.74 0.07 0.48 0.11 0.77 0.45 0.37 0.4 0.61 0.45 0.49 0.19 0.46 0.51
Names of X columns:
Cluttered, Uncluttered
Alternative
two.sided
two.sided
less
greater
Column number for the first variable
Column number for the second variable
Test to Perform
T-Test
Wilcoxon-Mann_Whitney
T-Test
Are observations paired?
paired
unpaired
paired
Value of Difference of Means to Test
Confidence Level to test
(?)
Display a Boxplot
TRUE
TRUE
FALSE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
par2 <- as.numeric(par2) par3 <- as.numeric(par3) par4 <- as.character(par4) par5 <- as.character(par5) par6 <- as.numeric(par6) par7 <- as.numeric(par7) par8 <- as.logical(par8) if ( par5 == 'unpaired') paired <- FALSE else paired <- TRUE x <- t(y) if(par8){ bitmap(file='test1.png') (r<-boxplot(x ,xlab=xlab,ylab=ylab,main=main,notch=FALSE,col=2)) dev.off() } load(file='createtable') if( par4 == 'Wilcoxon-Mann_Whitney'){ a<-table.start() a <- table.row.start(a) a <- table.element(a,'Wilcoxon Test',3,TRUE) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'',1,TRUE) a <- table.element(a,'Statistic',1,TRUE) a <- table.element(a,'P-value',1,TRUE) a <- table.row.end(a) W <- wilcox.test(x[,par2],x[,par3],alternative=par1, paired = paired) a<-table.row.start(a) a<-table.element(a,'Wilcoxon Test',1,TRUE) a<-table.element(a,W$statistic[[1]]) a<-table.element(a,round(W$p.value, digits=5) ) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') } if( par4 == 'T-Test') { T <- t.test(x[,par2],x[,par3],alternative=par1, paired=paired, mu=par6, conf.level=par7) a<-table.start() a <- table.row.start(a) a <- table.element(a,'T-Test',3,TRUE) a <- table.row.end(a) if(paired){ a <- table.row.start(a) a <- table.element(a,'Difference: Mean1 - Mean2',1,TRUE) a<-table.element(a,round(T$estimate, digits=5) ) a <- table.row.end(a) } if(!paired){ a <- table.row.start(a) a <- table.element(a,'Mean1',1,TRUE) a<-table.element(a,round(T$estimate[1], digits=5) ) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'Mean2',1,TRUE) a<-table.element(a,round(T$estimate[2], digits=5) ) a <- table.row.end(a) } a <- table.row.start(a) a <- table.element(a,'T Statistic',1,TRUE) a<-table.element(a,round(T$statistic, digits=5) ) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'P-value',1,TRUE) a<-table.element(a,round(T$p.value, digits=5) ) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'Lower Confidence Limit',1,TRUE) a<-table.element(a,round(T$conf.int[1], digits=5) ) a <- table.row.end(a) a<-table.row.start(a) a <- table.element(a,'Upper Confidence Limit',1,TRUE) a<-table.element(a,round(T$conf.int[2], digits=5) ) 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,'Standard Deviations',3,TRUE) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'Variable 1',1,TRUE) a<-table.element(a,round(sd(x[,par2], na.rm=TRUE), digits=5) ) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'Variable 2',1,TRUE) a<-table.element(a,round(sd(x[,par3], na.rm=TRUE), digits=5) ) a <- table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.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