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Data X:
13 12 14 12 53 16 11 18 11 86 19 15 11 14 66 15 6 12 12 67 14 13 16 21 76 13 10 18 12 78 19 12 14 22 53 15 14 14 11 80 14 12 15 10 74 15 6 15 13 76 16 10 17 10 79 16 12 19 8 54 16 12 10 15 67 16 11 16 14 54 17 15 18 10 87 15 12 14 14 58 15 10 14 14 75 20 12 17 11 88 18 11 14 10 64 16 12 16 13 57 16 11 18 7 66 16 12 11 14 68 19 13 14 12 54 16 11 12 14 56 17 9 17 11 86 17 13 9 9 80 16 10 16 11 76 15 14 14 15 69 16 12 15 14 78 14 10 11 13 67 15 12 16 9 80 12 8 13 15 54 14 10 17 10 71 16 12 15 11 84 14 12 14 13 74 7 7 16 8 71 10 6 9 20 63 14 12 15 12 71 16 10 17 10 76 16 10 13 10 69 16 10 15 9 74 14 12 16 14 75 20 15 16 8 54 14 10 12 14 52 14 10 12 11 69 11 12 11 13 68 14 13 15 9 65 15 11 15 11 75 16 11 17 15 74 14 12 13 11 75 16 14 16 10 72 14 10 14 14 67 12 12 11 18 63 16 13 12 14 62 9 5 12 11 63 14 6 15 12 76 16 12 16 13 74 16 12 15 9 67 15 11 12 10 73 16 10 12 15 70 12 7 8 20 53 16 12 13 12 77 16 14 11 12 77 14 11 14 14 52 16 12 15 13 54 17 13 10 11 80 18 14 11 17 66 18 11 12 12 73 12 12 15 13 63 16 12 15 14 69 10 8 14 13 67 14 11 16 15 54 18 14 15 13 81 18 14 15 10 69 16 12 13 11 84 17 9 12 19 80 16 13 17 13 70 16 11 13 17 69 13 12 15 13 77 16 12 13 9 54 16 12 15 11 79 20 12 16 10 30 16 12 15 9 71 15 12 16 12 73 15 11 15 12 72 16 10 14 13 77 14 9 15 13 75 16 12 14 12 69 16 12 13 15 54 15 12 7 22 70 12 9 17 13 73 17 15 13 15 54 16 12 15 13 77 15 12 14 15 82 13 12 13 10 80 16 10 16 11 80 16 13 12 16 69 16 9 14 11 78 16 12 17 11 81 14 10 15 10 76 16 14 17 10 76 16 11 12 16 73 20 15 16 12 85 15 11 11 11 66 16 11 15 16 79 13 12 9 19 68 17 12 16 11 76 16 12 15 16 71 16 11 10 15 54 12 7 10 24 46 16 12 15 14 82 16 14 11 15 74 17 11 13 11 88 13 11 14 15 38 12 10 18 12 76 18 13 16 10 86 14 13 14 14 54 14 8 14 13 70 13 11 14 9 69 16 12 14 15 90 13 11 12 15 54 16 13 14 14 76 13 12 15 11 89 16 14 15 8 76 15 13 15 11 73 16 15 13 11 79 15 10 17 8 90 17 11 17 10 74 15 9 19 11 81 12 11 15 13 72 16 10 13 11 71 10 11 9 20 66 16 8 15 10 77 12 11 15 15 65 14 12 15 12 74 15 12 16 14 82 13 9 11 23 54 15 11 14 14 63 11 10 11 16 54 12 8 15 11 64 8 9 13 12 69 16 8 15 10 54 15 9 16 14 84 17 15 14 12 86 16 11 15 12 77 10 8 16 11 89 18 13 16 12 76 13 12 11 13 60 16 12 12 11 75 13 9 9 19 73 10 7 16 12 85 15 13 13 17 79 16 9 16 9 71 16 6 12 12 72 14 8 9 19 69 10 8 13 18 78 17 15 13 15 54 13 6 14 14 69 15 9 19 11 81 16 11 13 9 84 12 8 12 18 84 13 8 13 16 69
Names of X columns:
Learning Software Happiness Depression Belonging
Factor 1
Factor 2
Type of test to use
(?)
Pearson Chi-Squared
Pearson Chi-Squared
Exact Pearson Chi-Squared by Simulation
McNemar Chi-Squared
Fisher Exact Test
Chart options
Title:
R Code
library(vcd) cat1 <- as.numeric(par1) # cat2<- as.numeric(par2) # simulate.p.value=FALSE if (par3 == 'Exact Pearson Chi-Squared by Simulation') simulate.p.value=TRUE x <- t(x) (z <- array(unlist(x),dim=c(length(x[,1]),length(x[1,])))) (table1 <- table(z[,cat1],z[,cat2])) (V1<-dimnames(y)[[1]][cat1]) (V2<-dimnames(y)[[1]][cat2]) bitmap(file='pic1.png') assoc(ftable(z[,cat1],z[,cat2],row.vars=1,dnn=c(V1,V2)),shade=T) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Tabulation of Results',ncol(table1)+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ', 1,TRUE) for(nc in 1:ncol(table1)){ a<-table.element(a, colnames(table1)[nc], 1, TRUE) } a<-table.row.end(a) for(nr in 1:nrow(table1) ){ a<-table.element(a, rownames(table1)[nr], 1, TRUE) for(nc in 1:ncol(table1) ){ a<-table.element(a, table1[nr, nc], 1, FALSE) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') (cst<-chisq.test(table1, simulate.p.value=simulate.p.value) ) if (par3 == 'McNemar Chi-Squared') { (cst <- mcnemar.test(table1)) } if (par3=='Fisher Exact Test') { (cst <- fisher.test(table1)) } if ((par3 != 'McNemar Chi-Squared') & (par3 != 'Fisher Exact Test')) { a<-table.start() a<-table.row.start(a) a<-table.element(a,'Tabulation of Expected Results',ncol(table1)+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ', 1,TRUE) for(nc in 1:ncol(table1)){ a<-table.element(a, colnames(table1)[nc], 1, TRUE) } a<-table.row.end(a) for(nr in 1:nrow(table1) ){ a<-table.element(a, rownames(table1)[nr], 1, TRUE) for(nc in 1:ncol(table1) ){ a<-table.element(a, round(cst$expected[nr, nc], digits=2), 1, FALSE) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') } a<-table.start() a<-table.row.start(a) a<-table.element(a,'Statistical Results',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, cst$method, 2,TRUE) a<-table.row.end(a) a<-table.row.start(a) if (par3=='Pearson Chi-Squared') a<-table.element(a, 'Pearson Chi Square Statistic', 1, TRUE) if (par3=='Exact Pearson Chi-Squared by Simulation') a<-table.element(a, 'Exact Pearson Chi Square Statistic', 1, TRUE) if (par3=='McNemar Chi-Squared') a<-table.element(a, 'McNemar Chi Square Statistic', 1, TRUE) if (par3=='Fisher Exact Test') a<-table.element(a, 'Odds Ratio', 1, TRUE) if (par3=='Fisher Exact Test') { if ((ncol(table1) == 2) & (nrow(table1) == 2)) { a<-table.element(a, round(cst$estimate, digits=2), 1,FALSE) } else { a<-table.element(a, '--', 1,FALSE) } } else { a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE) } a<-table.row.end(a) if(!simulate.p.value){ if(par3!='Fisher Exact Test') { a<-table.row.start(a) a<-table.element(a, 'Degrees of Freedom', 1, TRUE) a<-table.element(a, cst$parameter, 1,FALSE) a<-table.row.end(a) } } a<-table.row.start(a) a<-table.element(a, 'P value', 1, TRUE) a<-table.element(a, round(cst$p.value, digits=2), 1,FALSE) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable2.tab')
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Summary of computational transaction
Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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