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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:
Uncluttered Cluttered
Alternative


Column number for the first variable


Column number for the second variable


Test to Perform


Are observations paired?


Value of Difference of Means to Test


Confidence Level to test (?)


Display a Boxplot


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]), 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]), digits=5) ) a <- table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab')

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

T-Test
Difference: Mean1 - Mean2	0.11733
T Statistic	2.19269
P-value	0.98175
Lower Confidence Limit	-Inf
Upper Confidence Limit	0.20826

Standard Deviations
Variable 1	0.19709
Variable 2	0.1887