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Data X:
12.9 21 12.2 26 12.8 22 7.4 22 6.7 18 12.6 23 14.8 12 13.3 20 11.1 22 8.2 21 11.4 19 6.4 22 10.6 15 12 20 6.3 19 11.3 18 11.9 15 9.3 20 9.6 21 10 21 6.4 15 13.8 16 10.8 23 13.8 21 11.7 18 10.9 25 16.1 9 13.4 30 9.9 20 11.5 23 8.3 16 11.7 16 9 19 9.7 25 10.8 25 10.3 18 10.4 23 12.7 21 9.3 10 11.8 14 5.9 22 11.4 26 13 23 10.8 23 12.3 24 11.3 24 11.8 18 7.9 23 12.7 15 12.3 19 11.6 16 6.7 25 10.9 23 12.1 17 13.3 19 10.1 21 5.7 18 14.3 27 8 21 13.3 13 9.3 8 12.5 29 7.6 28 15.9 23 9.2 21 9.1 19 11.1 19 13 20 14.5 18 12.2 19 12.3 17 11.4 19 8.8 25 14.6 19 12.6 22 13 26 12.6 14 13.2 28 9.9 16 7.7 24 10.5 20 13.4 12 10.9 24 4.3 22 10.3 12 11.8 22 11.2 20 11.4 10 8.6 23 13.2 17 12.6 22 5.6 24 9.9 18 8.8 21 7.7 20 9 20 7.3 22 11.4 19 13.6 20 7.9 26 10.7 23 10.3 24 8.3 21 9.6 21 14.2 19 8.5 8 13.5 17 4.9 20 6.4 11 9.6 8 11.6 15 11.1 18 4.35 18 12.7 19 18.1 19 17.85 23 16.6 22 12.6 21 17.1 25 19.1 30 16.1 17 13.35 27 18.4 23 14.7 23 10.6 18 12.6 18 16.2 23 13.6 19 18.9 15 14.1 20 14.5 16 16.15 24 14.75 25 14.8 25 12.45 19 12.65 19 17.35 16 8.6 19 18.4 19 16.1 23 11.6 21 17.75 22 15.25 19 17.65 20 16.35 20 17.65 3 13.6 23 14.35 14 14.75 23 18.25 20 9.9 15 16 13 18.25 16 16.85 7 14.6 24 13.85 17 18.95 24 15.6 24 14.85 19 11.75 25 18.45 20 15.9 28 17.1 23 16.1 27 19.9 18 10.95 28 18.45 21 15.1 19 15 23 11.35 27 15.95 22 18.1 28 14.6 25 15.4 21 15.4 22 17.6 28 13.35 20 19.1 29 15.35 25 7.6 25 13.4 20 13.9 20 19.1 16 15.25 20 12.9 20 16.1 23 17.35 18 13.15 25 12.15 18 12.6 19 10.35 25 15.4 25 9.6 25 18.2 24 13.6 19 14.85 26 14.75 10 14.1 17 14.9 13 16.25 17 19.25 30 13.6 25 13.6 4 15.65 16 12.75 21 14.6 23 9.85 22 12.65 17 19.2 20 16.6 20 11.2 22 15.25 16 11.9 23 13.2 16 16.35 0 12.4 18 15.85 25 18.15 23 11.15 12 15.65 18 17.75 24 7.65 11 12.35 18 15.6 14 19.3 23 15.2 24 17.1 29 15.6 18 18.4 15 19.05 29 18.55 16 19.1 19 13.1 22 12.85 16 9.5 23 4.5 23 11.85 19 13.6 4 11.7 20 12.4 24 13.35 20 11.4 4 14.9 24 19.9 22 11.2 16 14.6 3 17.6 15 14.05 24 16.1 17 13.35 20 11.85 27 11.95 23 14.75 26 15.15 23 13.2 17 16.85 20 7.85 22 7.7 19 12.6 24 7.85 19 10.95 23 12.35 15 9.95 27 14.9 26 16.65 22 13.4 22 13.95 18 15.7 15 16.85 22 10.95 27 15.35 10 12.2 20 15.1 17 17.75 23 15.2 19 14.6 13 16.65 27 8.1 23
Names of X columns:
TOTAL Numeracy
Response Variable (column number)
Explanatory Variable (column number)
Include Intercept Term ?
Exact Pearson Chi-Squared by Simulation
TRUE
FALSE
Chart options
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Label y-axis:
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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