R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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> x <- c(101.94,102.62,102.71,103.39,104.51,104.09,104.29,104.57,105.39,105.15,106.13,105.46,106.47,106.62,106.52,108.04,107.15,107.32,107.76,107.26,107.89,109.08,110.4,111.03,112.05,112.28,112.8,114.17,114.92,114.65,115.49,114.67,114.71,115.15,115.03,115.07,116.46,116.37,116.2,116.5,116.38,115.44,114.96,114.48,114.3,114.66,114.97,114.79,116.16,116.52,117.14,117.27,117.58,117.21,117.08,117.06,117.55,117.61,117.74,117.87,118.59,119.09,118.93,119.62,120.09,120.38,120.49,120.02,120.17,120.58,121.54,121.51,121.81,122.85,122.97,122.96,123.4,123.23,123.24,123.72,123.99,125.1,125.4,125.35,126.37,127.17,127.66,128.48,129.21,129.48,128.63,128.16,128.1,128.08,128.14,128.19)
> 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] 96
> (np <- floor(n / par1))
[1] 8
> 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]
 [1,] 101.94 106.47 112.05 116.46 116.16 118.59 121.81 126.37
 [2,] 102.62 106.62 112.28 116.37 116.52 119.09 122.85 127.17
 [3,] 102.71 106.52 112.80 116.20 117.14 118.93 122.97 127.66
 [4,] 103.39 108.04 114.17 116.50 117.27 119.62 122.96 128.48
 [5,] 104.51 107.15 114.92 116.38 117.58 120.09 123.40 129.21
 [6,] 104.09 107.32 114.65 115.44 117.21 120.38 123.23 129.48
 [7,] 104.29 107.76 115.49 114.96 117.08 120.49 123.24 128.63
 [8,] 104.57 107.26 114.67 114.48 117.06 120.02 123.72 128.16
 [9,] 105.39 107.89 114.71 114.30 117.55 120.17 123.99 128.10
[10,] 105.15 109.08 115.15 114.66 117.61 120.58 125.10 128.08
[11,] 106.13 110.40 115.03 114.97 117.74 121.54 125.40 128.14
[12,] 105.46 111.03 115.07 114.79 117.87 121.51 125.35 128.19
> 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] 104.1875 107.9617 114.2492 115.4592 117.2325 120.0842 123.6683 128.1392
> arr.sd
[1] 1.2920254 1.4871928 1.1853305 0.8628226 0.4999477 0.9259144 1.1095686
[8] 0.8316737
> arr.range
[1] 4.19 4.56 3.44 2.20 1.71 2.95 3.59 3.11
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
    3.67471     -0.02278  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
       11.684         -2.462  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
     9.5732      -0.0546  

> postscript(file="/var/wessaorg/rcomp/tmp/1k5a71426195516.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/2kxk61426195516.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/34lvh1426195516.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/42txf1426195516.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/528ek1426195516.tab") 
> 
> try(system("convert tmp/1k5a71426195516.ps tmp/1k5a71426195516.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kxk61426195516.ps tmp/2kxk61426195516.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.886   0.152   1.044