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Type 'q()' to quit R. > x <- c(540,520,550,440,570,560,600,620,690,600,570,710,600,450,530,400,560,460,610,550,580,650,640,760,550,460,510,370,530,410,580,550,490,700,630,720,540,500,450,370,490,440,600,580,500,670,620,800,640,390,390,390,460,460,620,570,510,640,590,850,670,390,410,340,470,540,680,670,540,630,560,800,610,490,440,330,490,590,690,650,480,690,540,830,690,500,460,310,490,470,710,710,540,700,520,810,690,510,390,270,530,510,670,770,570,640,480,830) > par1 = '12' > par1 <- '12' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: root > #To cite this work: Wessa P. (2012), Standard Deviation-Mean Plot (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_smp.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > par1 <- as.numeric(par1) > (n <- length(x)) [1] 108 > (np <- floor(n / par1)) [1] 9 > arr <- array(NA,dim=c(par1,np)) > j <- 0 > k <- 1 > for (i in 1:(np*par1)) + { + j = j + 1 + arr[j,k] <- x[i] + if (j == par1) { + j = 0 + k=k+1 + } + } > arr [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [1,] 540 600 550 540 640 670 610 690 690 [2,] 520 450 460 500 390 390 490 500 510 [3,] 550 530 510 450 390 410 440 460 390 [4,] 440 400 370 370 390 340 330 310 270 [5,] 570 560 530 490 460 470 490 490 530 [6,] 560 460 410 440 460 540 590 470 510 [7,] 600 610 580 600 620 680 690 710 670 [8,] 620 550 550 580 570 670 650 710 770 [9,] 690 580 490 500 510 540 480 540 570 [10,] 600 650 700 670 640 630 690 700 640 [11,] 570 640 630 620 590 560 540 520 480 [12,] 710 760 720 800 850 800 830 810 830 > arr.mean <- array(NA,dim=np) > arr.sd <- array(NA,dim=np) > arr.range <- array(NA,dim=np) > for (j in 1:np) + { + arr.mean[j] <- mean(arr[,j],na.rm=TRUE) + arr.sd[j] <- sd(arr[,j],na.rm=TRUE) + arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE) + } > arr.mean [1] 580.8333 565.8333 541.6667 546.6667 542.5000 558.3333 569.1667 575.8333 [9] 571.6667 > arr.sd [1] 72.42028 98.76127 105.98742 116.09818 137.18766 138.09307 135.20747 [8] 145.25578 158.44892 > arr.range [1] 270 360 350 430 460 460 500 500 560 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean 183.3714 -0.1074 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) 12.994 -1.296 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 307.0718 0.2229 > postscript(file="/var/wessaorg/rcomp/tmp/1cwwn1471264014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2ydhb1471264014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range') > dev.off() null device 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() > a<-table.row.start(a) > a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Section',header=TRUE) > a<-table.element(a,'Mean',header=TRUE) > a<-table.element(a,'Standard Deviation',header=TRUE) > a<-table.element(a,'Range',header=TRUE) > a<-table.row.end(a) > for (j in 1:np) { + a<-table.row.start(a) + a<-table.element(a,j,header=TRUE) + a<-table.element(a,arr.mean[j]) + a<-table.element(a,arr.sd[j] ) + a<-table.element(a,arr.range[j] ) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/3p43b1471264014.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'alpha',header=TRUE) > a<-table.element(a,lm1$coefficients[[1]]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'beta',header=TRUE) > a<-table.element(a,lm1$coefficients[[2]]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,summary(lm1)$coefficients[2,2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'T-STAT',header=TRUE) > a<-table.element(a,summary(lm1)$coefficients[2,3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'p-value',header=TRUE) > a<-table.element(a,summary(lm1)$coefficients[2,4]) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/45bjn1471264014.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'alpha',header=TRUE) > a<-table.element(a,lnlm1$coefficients[[1]]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'beta',header=TRUE) > a<-table.element(a,lnlm1$coefficients[[2]]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,summary(lnlm1)$coefficients[2,2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'T-STAT',header=TRUE) > a<-table.element(a,summary(lnlm1)$coefficients[2,3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'p-value',header=TRUE) > a<-table.element(a,summary(lnlm1)$coefficients[2,4]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Lambda',header=TRUE) > a<-table.element(a,1-lnlm1$coefficients[[2]]) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/5yoh91471264014.tab") > > try(system("convert tmp/1cwwn1471264014.ps tmp/1cwwn1471264014.png",intern=TRUE)) character(0) > try(system("convert tmp/2ydhb1471264014.ps tmp/2ydhb1471264014.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.826 0.089 0.926