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Type 'q()' to quit R. > x <- c(92.44,94.36,93.42,92.97,94.83,91.47,88.42,86.36,86.01,87.87,89.81,88.41,86.33,89.64,89.53,88.3,99.49,98.81,90.97,92.58,92.98,95,92.47,88.65,84.81,88.6,89.31,92.34,91.53,96.95,95.44,89.59,89.86,91.66,92.7,90.54,86.17,89.15,89.73,91.07,93.36,96.27,95,94.72,97.16,100.92,98.66,95.87,94.6,98.41,98.05,99.82,106.96,107.45,100.25,99.28,101.38,101,97.43,95.38,95.17,94.13,96.43,105.38,98.39,99.8,94.43,90.16,85.49,90.57,88.22,89.66) > 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] 72 > (np <- floor(n / par1)) [1] 6 > 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] [1,] 92.44 86.33 84.81 86.17 94.60 95.17 [2,] 94.36 89.64 88.60 89.15 98.41 94.13 [3,] 93.42 89.53 89.31 89.73 98.05 96.43 [4,] 92.97 88.30 92.34 91.07 99.82 105.38 [5,] 94.83 99.49 91.53 93.36 106.96 98.39 [6,] 91.47 98.81 96.95 96.27 107.45 99.80 [7,] 88.42 90.97 95.44 95.00 100.25 94.43 [8,] 86.36 92.58 89.59 94.72 99.28 90.16 [9,] 86.01 92.98 89.86 97.16 101.38 85.49 [10,] 87.87 95.00 91.66 100.92 101.00 90.57 [11,] 89.81 92.47 92.70 98.66 97.43 88.22 [12,] 88.41 88.65 90.54 95.87 95.38 89.66 > 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] 90.53083 92.06250 91.11083 94.00667 100.00083 93.98583 > arr.sd [1] 3.109459 4.075869 3.173789 4.283309 3.941639 5.568289 > arr.range [1] 8.82 13.16 12.14 14.75 12.85 19.89 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean -3.90051 0.08466 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) -9.048 2.296 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean -13.3714 0.2881 > postscript(file="/var/wessaorg/rcomp/tmp/180ng1447791879.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/2wpks1447791879.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/360k21447791879.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/4dicx1447791879.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/5w97o1447791879.tab") > > try(system("convert tmp/180ng1447791879.ps tmp/180ng1447791879.png",intern=TRUE)) character(0) > try(system("convert tmp/2wpks1447791879.ps tmp/2wpks1447791879.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.912 0.192 1.104