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Data X:
6.475 0 0 0 4.593 1 0 0 6.136 0 0 1 7.494 0 1 1 4.873 1 0 0 8.926 0 0 0 7.296 0 0 1 7.171 0 0 1 8.157 0 0 1 4.681 1 0 0 7.256 0 1 1 7.817 0 0 0 5.685 1 0 0 4.644 1 0 1 8.991 0 0 0 6.550 0 0 1 5.503 1 0 1 6.295 1 1 1 5.808 1 0 0 5.771 1 0 0 8.478 0 0 1 6.451 0 0 0 7.221 0 1 0 8.138 0 1 1 6.566 0 0 1 6.673 0 0 1 6.599 0 0 0 8.897 0 0 1 4.556 1 0 0 8.014 0 1 1 5.522 1 0 0 5.671 1 0 1 5.020 1 0 0 5.632 1 0 1 5.153 1 0 0 5.886 1 0 0 5.303 1 0 1 4.716 1 0 0 9.475 0 1 1 7.332 0 1 0 9.241 0 0 1 5.460 1 0 0 6.132 0 0 0 5.554 1 0 0 8.170 0 0 1 5.232 1 0 0 6.897 0 0 0 8.525 0 0 1 8.103 0 0 1 6.698 0 1 0 5.990 0 1 0 6.832 0 1 0 5.551 1 0 1 7.990 0 0 1 9.244 0 0 1 7.207 0 0 0 5.005 1 0 0 5.585 1 0 0 5.392 1 0 0 7.423 0 0 1 8.370 0 0 1 5.595 1 0 0 8.232 0 1 1 5.671 1 1 0 7.767 0 0 0 6.363 0 0 0 8.097 0 0 1 6.212 1 0 1 6.091 0 0 0 5.941 1 1 0 6.769 0 1 0 7.068 0 0 0 6.801 0 1 0 5.124 1 0 0 4.974 1 0 0 5.234 1 0 0 4.748 1 0 0 8.034 0 0 0 7.610 0 0 0 4.984 1 0 0 5.998 1 0 0 5.648 1 0 0 6.900 0 0 1 7.079 1 1 1 7.747 0 1 1 5.115 1 0 0 6.111 0 1 1 7.036 0 0 1
Names of X columns:
sprint athlete smoking gender
Response Variable (column number)
Factor Variable (column number)
Include Intercept Term ?
No Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendNo Linear TrendTRUE
TRUE
FALSE
Chart options
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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){ '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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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