R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
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> x <- c(1.56,1.56,1.54,1.54,1.54,1.54,1.57,1.58,1.57,1.57,1.57,1.57,1.56,1.58,1.58,1.58,1.58,1.53,1.48,1.48,1.48,1.48,1.48,1.57,1.57,1.57,1.60,1.60,1.65,1.71,1.71,1.71,1.74,1.78,1.84,1.84,1.76,1.72,1.66,1.65,1.66,1.66,1.66,1.61,1.55,1.56,1.55,1.55,1.61,1.54,1.48,1.42,1.42,1.42,1.43,1.46,1.50,1.47,1.43,1.42,1.39,1.37,1.38,1.51,1.47,1.47,1.53,1.55,1.50,1.52,1.53,1.53,1.52,1.60,1.52,1.64,1.63,1.69,1.73,1.69,1.61,1.52,1.55,1.56,1.56,1.56,1.54,1.53,1.54,1.48,1.38,1.34,1.28,1.28,1.30,1.31,1.31,1.31,1.32,1.31,1.27,1.24,1.24,1.24,1.24,1.24,1.24,1.24,1.23,1.26,1.28,1.32,1.40,1.41,1.37,1.33,1.33,1.34,1.34,1.38,1.43,1.39,1.33,1.33,1.34,1.38,1.37,1.38,1.31,1.38,1.30,1.30,1.29,1.31,1.31,1.32,1.31,1.30,1.31,1.33,1.34,1.42,1.42,1.36,1.36,1.34,1.34,1.33,1.31,1.25,1.23,1.17,1.19,1.19,1.19,1.19)
> 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] 156
> (np <- floor(n / par1))
[1] 13
> 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] [,9] [,10] [,11] [,12] [,13]
 [1,] 1.56 1.56 1.57 1.76 1.61 1.39 1.52 1.56 1.31  1.23  1.43  1.29  1.36
 [2,] 1.56 1.58 1.57 1.72 1.54 1.37 1.60 1.56 1.31  1.26  1.39  1.31  1.34
 [3,] 1.54 1.58 1.60 1.66 1.48 1.38 1.52 1.54 1.32  1.28  1.33  1.31  1.34
 [4,] 1.54 1.58 1.60 1.65 1.42 1.51 1.64 1.53 1.31  1.32  1.33  1.32  1.33
 [5,] 1.54 1.58 1.65 1.66 1.42 1.47 1.63 1.54 1.27  1.40  1.34  1.31  1.31
 [6,] 1.54 1.53 1.71 1.66 1.42 1.47 1.69 1.48 1.24  1.41  1.38  1.30  1.25
 [7,] 1.57 1.48 1.71 1.66 1.43 1.53 1.73 1.38 1.24  1.37  1.37  1.31  1.23
 [8,] 1.58 1.48 1.71 1.61 1.46 1.55 1.69 1.34 1.24  1.33  1.38  1.33  1.17
 [9,] 1.57 1.48 1.74 1.55 1.50 1.50 1.61 1.28 1.24  1.33  1.31  1.34  1.19
[10,] 1.57 1.48 1.78 1.56 1.47 1.52 1.52 1.28 1.24  1.34  1.38  1.42  1.19
[11,] 1.57 1.48 1.84 1.55 1.43 1.53 1.55 1.30 1.24  1.34  1.30  1.42  1.19
[12,] 1.57 1.57 1.84 1.55 1.42 1.53 1.56 1.31 1.24  1.38  1.30  1.36  1.19
> 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] 1.559167 1.531667 1.693333 1.632500 1.466667 1.479167 1.605000 1.425000
 [9] 1.266667 1.332500 1.353333 1.335000 1.257500
> arr.sd
 [1] 0.01505042 0.04764134 0.09689107 0.06969088 0.05928871 0.06444989
 [7] 0.07305042 0.11950656 0.03498918 0.05479300 0.04097301 0.04379705
[13] 0.07312816
> arr.range
 [1] 0.04 0.10 0.27 0.21 0.19 0.18 0.21 0.28 0.08 0.18 0.13 0.13 0.19
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  -0.009415     0.048351  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -3.2054         0.8129  

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

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

Coefficients:
(Intercept)     arr.mean  
   -0.04631      0.14743  

> postscript(file="/var/wessaorg/rcomp/tmp/1rfjm1483968027.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/2rlqv1483968027.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/3cw411483968027.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4trn21483968027.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5iwz21483968027.tab") 
> 
> try(system("convert tmp/1rfjm1483968027.ps tmp/1rfjm1483968027.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rlqv1483968027.ps tmp/2rlqv1483968027.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.879   0.072   0.988