R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(76990,17,37460,7,54157,15,49862,14,84337,14,64175,18,59382,12,119308,16,76702,21,103425,19,70344,16,43410,1,104838,16,62215,10,69304,19,53117,12,19764,2,86680,14,84105,17,77945,19,89113,14,91005,11,40248,4,64187,16,50857,20,56613,12,62792,15,72535,16),dim=c(2,28),dimnames=list(c('time_in_RFC','Compendiums_reviewed'),1:28)) > y <- array(NA,dim=c(2,28),dimnames=list(c('time_in_RFC','Compendiums_reviewed'),1:28)) > 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 = '2' > par1 = '1' > ylab = 'Y Variable Name' > xlab = 'X Variable Name' > main = 'Title Goes Here' > par3 <- 'TRUE' > par2 <- '2' > par1 <- '1' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: aston2 > #To cite this work: Ian E. Holliday, 2012, Simple Linear Regression (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_Simple%20Regression%20Y%20~%20X.wasp/ > #Source of accompanying publication: > # > cat1 <- as.numeric(par1) > cat2<- as.numeric(par2) > intercept<-as.logical(par3) > x <- t(x) > xdf<-data.frame(t(y)) > (V1<-dimnames(y)[[1]][cat1]) [1] "time_in_RFC" > (V2<-dimnames(y)[[1]][cat2]) [1] "Compendiums_reviewed" > xdf <- data.frame(xdf[[cat1]], xdf[[cat2]]) > names(xdf)<-c('Y', 'X') > if(intercept == FALSE) (lmxdf<-lm(Y~ X - 1, data = xdf) ) else (lmxdf<-lm(Y~ X, data = xdf) ) Call: lm(formula = Y ~ X, data = xdf) Coefficients: (Intercept) X 33283 2566 > sumlmxdf<-summary(lmxdf) > (aov.xdf<-aov(lmxdf) ) Call: aov(formula = lmxdf) Terms: X Residuals Sum of Squares 4700985546 8625286785 Deg. of Freedom 1 26 Residual standard error: 18213.78 Estimated effects may be unbalanced > (anova.xdf<-anova(lmxdf) ) Analysis of Variance Table Response: Y Df Sum Sq Mean Sq F value Pr(>F) X 1 4700985546 4700985546 14.171 0.0008617 *** Residuals 26 8625286785 331741799 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > nc <- ncol(sumlmxdf$'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$coefficients[i, j], digits=3), 1 ,FALSE) + } + a<-table.row.end(a) + } > a<-table.row.start(a) > a<-table.element(a, '- - - ',1,TRUE) > a<-table.element(a, ' ',nc,FALSE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Std. Err. ',1,TRUE) > a<-table.element(a, paste(round(sumlmxdf$'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$'adj.r.squared', digits=3) ,nc, FALSE) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/1qzr71355262752.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, ' ',1,TRUE) > a<-table.element(a, 'Df',1,TRUE) > a<-table.element(a, 'Sum Sq',1,TRUE) > a<-table.element(a, 'Mean Sq',1,TRUE) > a<-table.element(a, 'F value',1,TRUE) > a<-table.element(a, 'Pr(>F)',1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, V2,1,TRUE) > a<-table.element(a, anova.xdf$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$'Mean Sq'[2], digits=3)) > a<-table.element(a, ' ') > a<-table.element(a, ' ') > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/2vqj51355262752.tab") > postscript(file="/var/wessaorg/rcomp/tmp/3582r1355262752.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(Y~ X, data=xdf, xlab=V2, ylab=V1, main='Regression Solution') > if(intercept == TRUE) abline(coef(lmxdf), col='red') > if(intercept == FALSE) abline(0.0, coef(lmxdf), col='red') > dev.off() null device 1 > library(car) Loading required package: MASS Loading required package: nnet > postscript(file="/var/wessaorg/rcomp/tmp/47t4v1355262752.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qq.plot(resid(lmxdf), main='QQplot of Residuals of Fit') Warning message: 'qq.plot' is deprecated. Use 'qqPlot' instead. See help("Deprecated") and help("car-deprecated"). > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/56n2p1355262752.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(xdf$X, resid(lmxdf), main='Scatterplot of Residuals of Model Fit') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/6400r1355262752.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot.lm(lmxdf, which=4) > dev.off() null device 1 > > try(system("convert tmp/3582r1355262752.ps tmp/3582r1355262752.png",intern=TRUE)) character(0) > try(system("convert tmp/47t4v1355262752.ps tmp/47t4v1355262752.png",intern=TRUE)) character(0) > try(system("convert tmp/56n2p1355262752.ps tmp/56n2p1355262752.png",intern=TRUE)) character(0) > try(system("convert tmp/6400r1355262752.ps tmp/6400r1355262752.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.237 0.369 2.592