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Data X:
109 154 107 138 118 152 222 153 103 142 128 142 109 129 131 145 124 193 122 151 122 243 113 131 100 136 124 201 118 148 80 155 142 129 104 138 131 174 110 132 107 160 122 158 109 167 100.1696943 144.3409 110 167 150 147 113 209 131 135.3409 153 129 119 147 127 145 126 115 103 137 123 142 109 147 113 195 100 156 101.1696943 132 105 139 127 139 121 111 105 120 115 128 112 138 106 170 116 140 113 175 112 204 113 126 100 174 104 158 106.1696943 134 110 166 94 190 90 151 125 131 104 155 103 142 112 138.3409 128 176 114 167 112 181 153 168 124 134 136 174 110 112 108 137 98.16969429 114 90 191 136 151 88 122 123 153.3409 109 126 97 139 106 133 126 163 113.1696943 136 105 158 108 153.3409 109 140 130 151 110 181 110 175 114 145 137 163 115 152.3409 94 181 92 160
Names of X columns:
FD MD
Alternative
10
two.sided
less
greater
Column number for the first variable
Column number for the second variable
Test to Perform
Wilcoxon-Mann_Whitney
T-Test
Are observations paired?
unpaired
paired
Value of Difference of Means to Test
Confidence Level to test
(?)
Display a Boxplot
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')
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Raw Input
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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