R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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> x <- c(101.97,103.9,106.85,106.93,107.13,107.07,107.2,107.78,108,108.11,107.26,105.3,105.55,105.38,106.12,106.85,107.92,107.97,107.76,107.99,108.41,107.61,106.54,106.24,106.19,106.71,106.36,107.53,107.89,108,108.05,108.86,109.27,108.87,108.88,108.19,108.19,108.91,110.39,111.21,111.44,111.87,111.88,111.93,111.76,111.66,110.25,109.05,109.47,109.68,110.93,111.86,112.66,112.96,113.14,113.53,113.62,112.51,111,108.49,108.52,110.66,111.15,112.14,113.38,113.75,113.89,113.92,116.4,115.86,115.16,114.45,114.65,114.85,116.51,118.18,118.75,119.06,119.28,119.68,119.28,117.3,114.23,112.56,112.83,112.35,112.8,113.84,115.02,115.46,115,115.3,116.09,115.49,112.89,110.66)
> 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] 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,] 101.97 105.55 106.19 108.19 109.47 108.52 114.65 112.83
 [2,] 103.90 105.38 106.71 108.91 109.68 110.66 114.85 112.35
 [3,] 106.85 106.12 106.36 110.39 110.93 111.15 116.51 112.80
 [4,] 106.93 106.85 107.53 111.21 111.86 112.14 118.18 113.84
 [5,] 107.13 107.92 107.89 111.44 112.66 113.38 118.75 115.02
 [6,] 107.07 107.97 108.00 111.87 112.96 113.75 119.06 115.46
 [7,] 107.20 107.76 108.05 111.88 113.14 113.89 119.28 115.00
 [8,] 107.78 107.99 108.86 111.93 113.53 113.92 119.68 115.30
 [9,] 108.00 108.41 109.27 111.76 113.62 116.40 119.28 116.09
[10,] 108.11 107.61 108.87 111.66 112.51 115.86 117.30 115.49
[11,] 107.26 106.54 108.88 110.25 111.00 115.16 114.23 112.89
[12,] 105.30 106.24 108.19 109.05 108.49 114.45 112.56 110.66
> 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] 106.4583 107.0283 107.9000 110.7117 111.6542 113.2733 117.0275 113.9775
> arr.sd
[1] 1.840883 1.044839 1.029793 1.336575 1.724552 2.289594 2.414544 1.662113
> arr.range
[1] 6.14 3.03 3.08 3.74 5.13 7.88 7.12 5.43
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    -9.4412       0.1001  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -31.486          6.785  

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

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

Coefficients:
(Intercept)     arr.mean  
    -28.773        0.306  

> postscript(file="/var/wessaorg/rcomp/tmp/1tak91426175117.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/2d27x1426175117.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/3lt4u1426175117.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/490jc1426175117.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5fv921426175117.tab") 
> 
> try(system("convert tmp/1tak91426175117.ps tmp/1tak91426175117.png",intern=TRUE))
character(0)
> try(system("convert tmp/2d27x1426175117.ps tmp/2d27x1426175117.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.889   0.159   1.051