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Data X:
1 36 92 2 36 88 2 56 94 3 48 90 1 32 73 1 44 68 2 39 80 2 34 86 1 41 86 3 50 91 1 39 79 3 62 96 2 52 92 1 37 72 2 50 96 2 41 70 2 55 86 1 41 87 3 56 88 2 39 79 1 52 90 1 46 95 1 44 85 1 48 92 2 41 90 3 50 115 2 50 84 2 44 79 2 52 94 2 54 97 2 44 86 3 52 111 2 37 87 2 52 98 2 50 87 1 36 68 2 50 88 2 52 82 3 55 111 1 31 75 2 36 94 1 49 95 2 42 80 2 37 95 2 41 68 2 30 94 2 52 88 1 30 84 1 41 92 2 44 101 2 66 98 1 48 78 3 43 109 1 57 102 1 46 81 1 54 97 2 48 75 2 48 97 2 52 92 1 62 101 1 58 101 2 58 95 2 62 95 2 48 92 1 46 95 1 34 90 3 66 107 2 52 92 1 55 86 1 55 70 2 57 95 2 56 96 2 55 91 3 56 87 2 54 92 2 55 97 3 46 102 1 52 91 2 32 68 1 44 88 2 46 97 2 59 90 2 46 101 2 46 94 3 54 101 3 66 109 2 56 100 2 59 103 2 57 94 2 52 97 2 48 85 2 44 75 1 41 77 1 50 87 1 48 78 3 48 108 2 59 97 2 34 105 2 46 106 2 54 107 1 55 95 2 54 107 2 59 115 2 44 101 1 54 85 2 52 90 3 66 115 2 44 95 1 57 97 1 39 112 1 60 97 1 45 77 2 41 90 2 50 94 3 39 103 2 43 77 2 48 98 2 37 90 3 58 111 1 46 77 3 43 88 1 44 75 2 34 92 2 30 78 2 50 106 1 39 80 2 37 87 2 55 92 3 48 92 3 41 111 2 39 86 2 36 85 1 43 90 3 50 101 2 55 94 1 43 86 1 60 86 1 48 90 1 30 75 2 43 86 3 39 91 2 52 97 2 39 91 1 39 70 2 56 98 1 59 96 1 46 95 2 57 100 2 50 95 2 54 97 2 50 97 3 60 92 3 59 115 3 41 88 2 48 87 2 59 100 2 60 98 1 56 102 2 56 92 1 51 96
Names of X columns:
VRBIQ 30M YR7
Response Variable (column number)
Factor Variable (column number)
Include Intercept Term ?
FALSE
TRUE
FALSE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
par3 <- 'TRUE' par2 <- '3' par1 <- '1' cat1 <- as.numeric(par1) # cat2<- as.numeric(par2) # intercept<-as.logical(par3) x <- t(x) x1<-as.numeric(x[,cat1]) f1<-as.character(x[,cat2]) xdf<-data.frame(x1,f1) (V1<-dimnames(y)[[1]][cat1]) (V2<-dimnames(y)[[1]][cat2]) names(xdf)<-c('Response', 'Treatment') if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) ) (aov.xdf<-aov(lmxdf) ) (anova.xdf<-anova(lmxdf) ) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'means',,TRUE) for(i in 1:length(lmxdf$coefficients)){ a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE) } 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,'ANOVA Statistics', 5+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ',,TRUE) a<-table.element(a, 'Df',,FALSE) a<-table.element(a, 'Sum Sq',,FALSE) a<-table.element(a, 'Mean Sq',,FALSE) a<-table.element(a, 'F value',,FALSE) a<-table.element(a, 'Pr(>F)',,FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, V2,,TRUE) a<-table.element(a, anova.xdf$Df[1],,FALSE) a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residuals',,TRUE) a<-table.element(a, anova.xdf$Df[2],,FALSE) a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE) a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE) a<-table.element(a, ' ',,FALSE) a<-table.element(a, ' ',,FALSE) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') bitmap(file='anovaplot.png') boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1) dev.off() if(intercept==TRUE){ 'Tukey Plot' thsd<-TukeyHSD(aov.xdf) bitmap(file='TukeyHSDPlot.png') plot(thsd) dev.off() } if(intercept==TRUE){ a<-table.start() a<-table.row.start(a) a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ', 1, TRUE) for(i in 1:4){ a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE) } a<-table.row.end(a) for(i in 1:length(rownames(thsd[[1]]))){ a<-table.row.start(a) a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE) for(j in 1:4){ a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') } if(intercept==FALSE){ a<-table.start() a<-table.row.start(a) a<-table.element(a,'TukeyHSD Message', 1,TRUE) a<-table.row.end(a) a<-table.start() a<-table.row.start(a) a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable2.tab') } library(car) lt.lmxdf<-leveneTest(lmxdf) a<-table.start() a<-table.row.start(a) a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ', 1, TRUE) for (i in 1:3){ a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE) } a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Group', 1, TRUE) for (i in 1:3){ a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE) } a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ', 1, TRUE) a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE) a<-table.element(a,' ', 1, FALSE) a<-table.element(a,' ', 1, FALSE) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable3.tab')
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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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