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Type 'q()' to quit R. > x <- c(250.8,247.6,237.8,226.4,217.2,211.4,207.6,204.3,197.5,193.6,192.3,192,196.1,191.9,185.6,179.4,173.9,169.2,166.8,165.2,161.4,160.8,163.7,170.8,182.7,190.9,197.8,205.1,210.7,220.2,229.7,237.1,241.6,250.4,258.6,269.9,283.2,289.6,281.8,274.7,267.6,261.4,260.5,260.7,254.2,250.5,253.4,263.7,276.2,273.8,265.9,258.4,253.5,250.7,252.8,255.3,251.2,252.5,257.8,269.9,291.6,298.9,295.6,292.1,290.9,290.6,298,304,304.3,309.8,322.3,340.2,369.3,376.7,379.7,379.5,377.8,381.6,394.6,399.3,400.4,408.2,419.1,437.7) > 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] 84 > (np <- floor(n / par1)) [1] 7 > 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] [1,] 250.8 196.1 182.7 283.2 276.2 291.6 369.3 [2,] 247.6 191.9 190.9 289.6 273.8 298.9 376.7 [3,] 237.8 185.6 197.8 281.8 265.9 295.6 379.7 [4,] 226.4 179.4 205.1 274.7 258.4 292.1 379.5 [5,] 217.2 173.9 210.7 267.6 253.5 290.9 377.8 [6,] 211.4 169.2 220.2 261.4 250.7 290.6 381.6 [7,] 207.6 166.8 229.7 260.5 252.8 298.0 394.6 [8,] 204.3 165.2 237.1 260.7 255.3 304.0 399.3 [9,] 197.5 161.4 241.6 254.2 251.2 304.3 400.4 [10,] 193.6 160.8 250.4 250.5 252.5 309.8 408.2 [11,] 192.3 163.7 258.6 253.4 257.8 322.3 419.1 [12,] 192.0 170.8 269.9 263.7 269.9 340.2 437.7 > 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] 214.8750 173.7333 224.5583 266.7750 259.8333 303.1917 393.6583 > arr.sd [1] 21.297807 11.959578 27.875256 12.779680 9.190542 14.925053 20.337313 > arr.range [1] 58.8 35.3 87.2 39.1 25.5 49.6 68.4 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean 15.306866 0.006107 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) 1.9121 0.1538 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 35.69557 0.06209 > postscript(file="/var/wessaorg/rcomp/tmp/1k1vy1416557751.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/21m351416557751.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/3i1rb1416557751.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/4648b1416557751.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/543381416557751.tab") > > try(system("convert tmp/1k1vy1416557751.ps tmp/1k1vy1416557751.png",intern=TRUE)) character(0) > try(system("convert tmp/21m351416557751.ps tmp/21m351416557751.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.936 0.139 1.078