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Type 'q()' to quit R. > x <- array(list(1,1.1,2,1.8,2,5.2,1,3.5,2,3.9,1,-1.0,1,0.1,2,2.4,1,0.4,1,3.7,2,7.2,1,-0.4,2,8.4,1,5.9,1,1.4,2,8.0,2,0.0,2,2.8,2,8.2,1,0.9,1,0.6,2,5.0,2,5.9,1,-1.0,1,1.6,2,3.2,1,0.5,2,2.6,1,-2.7,2,5.8,2,2.8,1,1.3,1,5.0,1,1.6,1,3.4,2,9.6,2,7.4),dim=c(2,37),dimnames=list(c('Treatment','wieght'),1:37)) > y <- array(NA,dim=c(2,37),dimnames=list(c('Treatment','wieght'),1:37)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'TRUE' > par2 = '1' > par1 = '2' > ylab = 'Y Variable Name' > xlab = 'X Variable Name' > main = 'Title Goes Here' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > cat1 <- as.numeric(par1) # > cat2<- as.numeric(par2) # > intercept<-as.logical(par3) > x <- t(x) > xdf<-data.frame(t(y)) > (V1<-dimnames(y)[[1]][cat1]) [1] "wieght" > (V2<-dimnames(y)[[1]][cat2]) [1] "Treatment" > xdf <- data.frame(xdf[[cat1]], xdf[[cat2]]) > names(xdf)<-c('Y', 'X') > if(intercept == FALSE) (lmxdf<-lm(Y~ X - 1, data = xdf) ) else (lmxdf<-lm(Y~ X, data = xdf) ) Call: lm(formula = Y ~ X, data = xdf) Coefficients: (Intercept) X -2.285 3.648 > sumlmxdf<-summary(lmxdf) > (aov.xdf<-aov(lmxdf) ) Call: aov(formula = lmxdf) Terms: X Residuals Sum of Squares 123.0050 208.9620 Deg. of Freedom 1 35 Residual standard error: 2.443428 Estimated effects may be unbalanced > (anova.xdf<-anova(lmxdf) ) Analysis of Variance Table Response: Y Df Sum Sq Mean Sq F value Pr(>F) X 1 123.00 123.00 20.603 6.401e-05 *** Residuals 35 208.96 5.97 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > nc <- ncol(sumlmxdf$'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$coefficients[i, j], digits=3), 1 ,FALSE) + }# end cols + a<-table.row.end(a) + } #end rows > a<-table.row.start(a) > a<-table.element(a, '- - - ',1,TRUE) > a<-table.element(a, ' ',nc,FALSE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Std. Err. ',1,TRUE) > a<-table.element(a, paste(round(sumlmxdf$'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$'adj.r.squared', digits=3) ,nc, FALSE) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/1oybp1275471756.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, ' ',1,TRUE) > a<-table.element(a, 'Df',1,TRUE) > a<-table.element(a, 'Sum Sq',1,TRUE) > a<-table.element(a, 'Mean Sq',1,TRUE) > a<-table.element(a, 'F value',1,TRUE) > a<-table.element(a, 'Pr(>F)',1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, V2,1,TRUE) > a<-table.element(a, anova.xdf$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$'Mean Sq'[2], digits=3)) > a<-table.element(a, ' ') > a<-table.element(a, ' ') > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/2k8qx1275471756.tab") > postscript(file="/var/www/html/rcomp/tmp/3k8qx1275471756.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(Y~ X, data=xdf, xlab=V2, ylab=V1, main='Regression Solution') > if(intercept == TRUE) abline(coef(lmxdf), col='red') > if(intercept == FALSE) abline(0.0, coef(lmxdf), col='red') > dev.off() null device 1 > library(car) > postscript(file="/var/www/html/rcomp/tmp/4k8qx1275471756.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qq.plot(resid(lmxdf), main='QQplot of Residuals of Fit') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5k8qx1275471756.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(xdf$X, resid(lmxdf), main='Scatterplot of Residuals of Model Fit') > dev.off() null device 1 > > try(system("convert tmp/3k8qx1275471756.ps tmp/3k8qx1275471756.png",intern=TRUE)) character(0) > try(system("convert tmp/4k8qx1275471756.ps tmp/4k8qx1275471756.png",intern=TRUE)) character(0) > try(system("convert tmp/5k8qx1275471756.ps tmp/5k8qx1275471756.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.770 0.450 2.227