R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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> x <- c(109.03,110.43,111.01,111.01,110.76,111.13,111.07,111.09,110.96,110.64,110.62,110.59,111.33,113.94,114.61,114.64,114.62,114.71,114.72,114.66,114.76,114.68,114.75,114.74,116.36,117.53,118.82,119.83,119.97,121.29,120.94,121.02,120.98,121.02,120.89,120.76,123.28,123.98,125.91,125.84,125.98,127.24,127.23,127.82,127.59,127.74,127.44,127.35,128.54,129.3,130.67,130.76,131.34,130.69,130.96,130.68,130.61,130.59,130.44,129.04,131.46,132.77,134.48,134.52,136.11,136.12,136.03,135.84,137.75,137.45,136.84,136.79,140.12,140.68,140.35,140.42,140.19,140.14,140.13,139.45,139.59,139.44,139.53,139.28)
> 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,] 109.03 111.33 116.36 123.28 128.54 131.46 140.12
 [2,] 110.43 113.94 117.53 123.98 129.30 132.77 140.68
 [3,] 111.01 114.61 118.82 125.91 130.67 134.48 140.35
 [4,] 111.01 114.64 119.83 125.84 130.76 134.52 140.42
 [5,] 110.76 114.62 119.97 125.98 131.34 136.11 140.19
 [6,] 111.13 114.71 121.29 127.24 130.69 136.12 140.14
 [7,] 111.07 114.72 120.94 127.23 130.96 136.03 140.13
 [8,] 111.09 114.66 121.02 127.82 130.68 135.84 139.45
 [9,] 110.96 114.76 120.98 127.59 130.61 137.75 139.59
[10,] 110.64 114.68 121.02 127.74 130.59 137.45 139.44
[11,] 110.62 114.75 120.89 127.44 130.44 136.84 139.53
[12,] 110.59 114.74 120.76 127.35 129.04 136.79 139.28
> 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] 110.6950 114.3467 119.9508 126.4500 130.3017 135.5133 139.9433
> arr.sd
[1] 0.5737358 0.9753632 1.5869437 1.5044661 0.8553132 1.8889840 0.4605596
> arr.range
[1] 2.10 3.43 4.93 4.54 2.80 6.29 1.40
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   0.344327     0.006196  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -1.3506         0.2796  

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

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

Coefficients:
(Intercept)     arr.mean  
    2.04805      0.01272  

> postscript(file="/var/wessaorg/rcomp/tmp/15dyy1416756435.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/2286e1416756435.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/37hjt1416756435.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4pcls1416756435.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5skbd1416756435.tab") 
> 
> try(system("convert tmp/15dyy1416756435.ps tmp/15dyy1416756435.png",intern=TRUE))
character(0)
> try(system("convert tmp/2286e1416756435.ps tmp/2286e1416756435.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.882   0.146   1.034