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Data X:
13 12.9 8 12.2 14 12.8 16 7.4 14 6.7 13 12.6 15 14.8 13 13.3 20 11.1 17 8.2 15 11.4 16 6.4 12 10.6 17 12 11 6.3 16 11.3 16 11.9 15 9.3 13 9.6 14 10 19 6.4 16 13.8 17 10.8 10 13.8 15 11.7 14 10.9 14 16.1 16 13.4 15 9.9 17 11.5 14 8.3 16 11.7 15 9 16 9.7 16 10.8 10 10.3 8 10.4 17 12.7 14 9.3 10 11.8 14 5.9 12 11.4 16 13 16 10.8 16 12.3 8 11.3 16 11.8 15 7.9 8 12.7 13 12.3 14 11.6 13 6.7 16 10.9 19 12.1 19 13.3 14 10.1 15 5.7 13 14.3 10 8 16 13.3 15 9.3 11 12.5 9 7.6 16 15.9 12 9.2 12 9.1 14 11.1 14 13 13 14.5 15 12.2 17 12.3 14 11.4 11 8.8 9 14.6 7 12.6 15 13 12 12.6 15 13.2 14 9.9 16 7.7 14 10.5 13 13.4 16 10.9 13 4.3 16 10.3 16 11.8 16 11.2 10 11.4 12 8.6 12 13.2 12 12.6 12 5.6 19 9.9 14 8.8 13 7.7 16 9 15 7.3 12 11.4 8 13.6 10 7.9 16 10.7 16 10.3 10 8.3 18 9.6 12 14.2 16 8.5 10 13.5 14 4.9 12 6.4 11 9.6 15 11.6 7 11.1 16 4.35 16 12.7 16 18.1 16 17.85 12 16.6 15 12.6 14 17.1 15 19.1 16 16.1 13 13.35 10 18.4 17 14.7 15 10.6 18 12.6 16 16.2 20 13.6 16 18.9 17 14.1 16 14.5 15 16.15 13 14.75 16 14.8 16 12.45 16 12.65 17 17.35 20 8.6 14 18.4 17 16.1 6 11.6 16 17.75 15 15.25 16 17.65 16 16.35 14 17.65 16 13.6 16 14.35 16 14.75 14 18.25 14 9.9 16 16 16 18.25 15 16.85 16 14.6 16 13.85 18 18.95 15 15.6 16 14.85 16 11.75 16 18.45 17 15.9 14 17.1 18 16.1 9 19.9 15 10.95 14 18.45 15 15.1 13 15 16 11.35 20 15.95 14 18.1 12 14.6 15 15.4 15 15.4 15 17.6 16 13.35 11 19.1 16 15.35 7 7.6 11 13.4 9 13.9 15 19.1 16 15.25 14 12.9 15 16.1 13 17.35 13 13.15 12 12.15 16 12.6 14 10.35 16 15.4 14 9.6 15 18.2 10 13.6 16 14.85 14 14.75 16 14.1 12 14.9 16 16.25 16 19.25 15 13.6 14 13.6 16 15.65 11 12.75 15 14.6 18 9.85 13 12.65 7 19.2 7 16.6 17 11.2 18 15.25 15 11.9 8 13.2 13 16.35 13 12.4 15 15.85 18 18.15 16 11.15 14 15.65 15 17.75 19 7.65 16 12.35 12 15.6 16 19.3 11 15.2 16 17.1 15 15.6 19 18.4 15 19.05 14 18.55 14 19.1 17 13.1 16 12.85 20 9.5 16 4.5 9 11.85 13 13.6 15 11.7 19 12.4 16 13.35 17 11.4 16 14.9 9 19.9 11 11.2 14 14.6 19 17.6 13 14.05 14 16.1 15 13.35 15 11.85 14 11.95 16 14.75 17 15.15 12 13.2 15 16.85 17 7.85 15 7.7 10 12.6 16 7.85 15 10.95 11 12.35 16 9.95 16 14.9 16 16.65 14 13.4 14 13.95 16 15.7 16 16.85 18 10.95 14 15.35 20 12.2 15 15.1 16 17.75 16 15.2 16 14.6 12 16.65 8 8.1
Names of X columns:
CONFSTATTOT TOT
Response Variable (column number)
Explanatory Variable (column number)
Include Intercept Term ?
TRUE
TRUE
FALSE
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Label x-axis:
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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