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Data X:
7.5 12 6 8 6.5 11 1 13 1 11 5.5 10 8.5 7 6.5 10 4.5 15 2 12 5 12 0.5 10 5 10 5 14 2.5 6 5 12 5.5 14 3.5 11 3 8 4 12 0.5 15 6.5 13 4.5 11 7.5 12 5.5 7 4 11 7.5 7 7 12 4 12 5.5 13 2.5 9 5.5 11 3.5 12 2.5 15 4.5 12 4.5 6 4.5 5 6 13 2.5 11 5 6 0 12 5 10 6.5 6 5 12 6 11 4.5 6 5.5 12 1 12 7.5 8 6 10 5 11 1 7 5 12 6.5 13 7 14 4.5 12 0 6 8.5 14 3.5 10 7.5 12 3.5 11 6 10 1.5 7 9 12 3.5 7 3.5 12 4 12 6.5 10 7.5 10 6 12 5 12 5.5 12 3.5 8 7.5 10 6.5 5 6.5 10 6.5 12 7 11 3.5 9 1.5 12 4 11 7.5 10 4.5 12 0 10 3.5 9 5.5 11 5 12 4.5 7 2.5 11 7.5 12 7 6 0 9 4.5 15 3 10 1.5 11 3.5 12 2.5 12 5.5 12 8 11 1 9 5 11 4.5 12 3 12 3 14 8 8 2.5 10 7 9 0 10 1 9 3.5 10 5.5 12 5.5 11 0.5 9 7.5 11 9 12 9.5 12 8.5 7 7 12 8 12 10 12 7 10 8.5 15 9 10 9.5 15 4 10 6 15 8 9 5.5 15 9.5 12 7.5 13 7 12 7.5 12 8 8 7 9 7 15 6 12 10 12 2.5 15 9 11 8 12 6 6 8.5 14 6 12 9 12 8 12 9 11 5.5 12 7 12 5.5 12 9 12 2 8 8.5 8 9 12 8.5 12 9 11 7.5 10 10 11 9 12 7.5 13 6 12 10.5 12 8.5 10 8 10 10 11 10.5 8 6.5 12 9.5 9 8.5 12 7.5 9 5 11 8 15 10 8 7 8 7.5 11 7.5 11 9.5 11 6 13 10 7 7 12 3 8 6 8 7 4 10 11 7 10 3.5 7 8 12 10 11 5.5 9 6 10 6.5 8 6.5 8 8.5 11 4 12 9.5 10 8 10 8.5 12 5.5 8 7 11 9 8 8 10 10 14 8 9 6 9 8 10 5 13 9 12 4.5 13 8.5 8 9.5 3 8.5 8 7.5 12 7.5 11 5 9 7 12 8 12 5.5 12 8.5 10 9.5 13 7 9 8 12 8.5 11 3.5 14 6.5 11 6.5 9 10.5 12 8.5 8 8 15 10 12 10 14 9.5 12 9 9 10 9 7.5 13 4.5 13 4.5 15 0.5 11 6.5 7 4.5 10 5.5 11 5 14 6 14 4 13 8 12 10.5 8 6.5 13 8 9 8.5 12 5.5 13 7 11 5 11 3.5 13 5 12 9 12 8.5 10 5 9 9.5 10 3 13 1.5 13 6 9 0.5 11 6.5 12 7.5 8 4.5 12 8 12 9 12 7.5 9 8.5 12 7 12 9.5 11 6.5 12 9.5 6 6 7 8 10 9.5 12 8 10 8 12 9 9 5 3
Names of X columns:
Ex CONFSOFTTOT
Response Variable (column number)
Explanatory Variable (column number)
Include Intercept Term ?
TRUE
TRUE
FALSE
Chart options
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Label y-axis:
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R Code
cat1 <- as.numeric(par1) cat2<- as.numeric(par2) intercept<-as.logical(par3) x <- t(x) xdf<-data.frame(t(y)) (V1<-dimnames(y)[[1]][cat1]) (V2<-dimnames(y)[[1]][cat2]) xdf <- data.frame(xdf[[cat1]], xdf[[cat2]]) names(xdf)<-c('Y', 'X') if(intercept == FALSE) (lmxdf<-lm(Y~ X - 1, data = xdf) ) else (lmxdf<-lm(Y~ X, data = xdf) ) sumlmxdf<-summary(lmxdf) (aov.xdf<-aov(lmxdf) ) (anova.xdf<-anova(lmxdf) ) load(file='createtable') a<-table.start() nc <- ncol(sumlmxdf$'coefficients') nr <- nrow(sumlmxdf$'coefficients') a<-table.row.start(a) a<-table.element(a,'Linear Regression Model', nc+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, lmxdf$call['formula'],nc+1) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'coefficients:',1,TRUE) a<-table.element(a, ' ',nc,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ',1,TRUE) for(i in 1 : nc){ a<-table.element(a, dimnames(sumlmxdf$'coefficients')[[2]][i],1,TRUE) }#end header a<-table.row.end(a) for(i in 1: nr){ a<-table.element(a,dimnames(sumlmxdf$'coefficients')[[1]][i] ,1,TRUE) for(j in 1 : nc){ a<-table.element(a, round(sumlmxdf$coefficients[i, j], digits=3), 1 ,FALSE) } a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a, '- - - ',1,TRUE) a<-table.element(a, ' ',nc,FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residual Std. Err. ',1,TRUE) a<-table.element(a, paste(round(sumlmxdf$'sigma', digits=3), ' on ', sumlmxdf$'df'[2], 'df') ,nc, FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R-sq. ',1,TRUE) a<-table.element(a, round(sumlmxdf$'r.squared', digits=3) ,nc, FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Adjusted R-sq. ',1,TRUE) a<-table.element(a, round(sumlmxdf$'adj.r.squared', digits=3) ,nc, 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, ' ',1,TRUE) a<-table.element(a, 'Df',1,TRUE) a<-table.element(a, 'Sum Sq',1,TRUE) a<-table.element(a, 'Mean Sq',1,TRUE) a<-table.element(a, 'F value',1,TRUE) a<-table.element(a, 'Pr(>F)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, V2,1,TRUE) a<-table.element(a, anova.xdf$Df[1]) a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3)) a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3)) a<-table.element(a, round(anova.xdf$'F value'[1], digits=3)) a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residuals',1,TRUE) a<-table.element(a, anova.xdf$Df[2]) a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3)) a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3)) a<-table.element(a, ' ') a<-table.element(a, ' ') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') bitmap(file='regressionplot.png') plot(Y~ X, data=xdf, xlab=V2, ylab=V1, main='Regression Solution') if(intercept == TRUE) abline(coef(lmxdf), col='red') if(intercept == FALSE) abline(0.0, coef(lmxdf), col='red') dev.off() library(car) bitmap(file='residualsQQplot.png') qq.plot(resid(lmxdf), main='QQplot of Residuals of Fit') dev.off() bitmap(file='residualsplot.png') plot(xdf$X, resid(lmxdf), main='Scatterplot of Residuals of Model Fit') dev.off() bitmap(file='cooksDistanceLmplot.png') plot.lm(lmxdf, which=4) dev.off()
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