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Data X:
70 105 67 36 88 86 56 94 86 48 90 103 32 73 74 44 68 63 39 80 82 34 86 93 41 86 77 50 91 111 39 79 71 62 96 103 52 92 89 37 72 75 50 96 88 41 70 84 55 86 85 41 87 70 56 88 104 39 79 88 52 90 77 46 95 77 44 85 72 48 98 70 41 90 83 50 115 110 50 84 91 44 79 80 52 94 91 54 97 86 44 86 85 52 111 107 37 87 93 52 98 87 50 87 84 36 68 73 50 88 84 52 82 86 55 111 99 31 75 75 36 94 87 49 95 79 42 80 82 37 95 95 41 68 84 30 94 85 52 88 95 30 84 63 41 96 78 44 101 85 66 98 86 48 78 75 43 109 98 57 102 71 46 81 63 54 97 71 48 75 84 48 97 81 52 90 93 62 101 79 58 101 63 58 95 93 62 95 92 48 54 93 46 95 83 34 90 80 66 107 111 52 92 92 55 86 79 55 70 69 57 95 83 56 96 80 55 91 91 56 87 97 54 92 85 55 97 85 46 102 99 52 91 67 32 68 87 44 88 68 46 97 81 59 90 80 46 101 93 46 94 93 54 101 102 66 109 104 56 100 90 59 103 85 57 94 92 52 97 82 48 85 85 44 75 89 41 77 77 50 87 79 48 78 76 48 108 101 59 97 81 34 105 92 46 106 89 54 107 81 55 95 77 54 107 95 59 115 85 44 101 81 54 85 76 52 90 93 66 115 104 44 95 89 57 97 76 39 112 77 60 97 71 45 77 79 41 90 89 50 94 81 39 103 99 43 77 81 48 98 84 37 90 85 58 111 111 46 77 78 43 88 111 44 75 78 34 92 87 30 78 92 50 106 93 39 80 70 37 87 84 55 92 75 48 98 105 41 111 96 39 86 85 36 85 87 43 90 75 50 101 103 55 94 86 43 86 77 60 86 74 48 90 74 30 75 76 43 86 83 39 91 101 52 97 83 39 91 92 39 70 74 56 98 87 59 96 71 46 95 79 57 100 83 50 95 80 54 97 90 50 97 80 60 92 96 59 115 109 41 88 98 48 87 85 59 100 83 60 98 86 56 102 72 56 100 83 51 96 75
Names of X columns:
MC30VRB WISCRY7V MVRBIQ0
Response Variable (column number)
Factor Variable (column number)
Include Intercept Term ?
TRUE
TRUE
FALSE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
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){ 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<-levene.test(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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Big Analytics Cloud Computing Center
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