R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
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> x <- c(94.46,96.91,101.92,104.53,105.85,106.39,106.08,106.42,106.51,106.59,105.71,104.41,103.04,100.99,100.93,99.31,99.79,99.57,99.11,98.96,97.72,99.35,98.15,97.64,97.49,97.94,98.03,98.05,97.54,98.71,99.33,99.16,98.41,98.43,97.02,97.89,97.92,97.37,97.42,96.12,96.72,96.64,95.28,95.3,95.02,95.57,94.78,95.27,96.14,96.16,95.08,94.39,94.15,94.58,94.16,95.02,94.86,94.49,94.81,94.16,94.83,96.02,95.97,95.88,95.97,97.55,97.49,98.4,98.2,97.16,96.96,96.37,96.34,96.86,96.32,95.44,92.85,92.56,91.74,92.44,93.19,92.62,94.04,93.8,96.73,98.99,100.38,101.07,99.92,101.78,100.91,100.49,101.17,100.25,98.94,99.4,100.02,99.91,99.22,98.84,98.42,97.59,97.07,96.59,95.96,94.22,94.48,93.14,93.73,94.24,98.52,99.09,99.84,99.13,100.88,100.83,101.6,101.8,102.77,103.14)
> 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] 120
> (np <- floor(n / par1))
[1] 10
> 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]
 [1,]  94.46 103.04 97.49 97.92 96.14 94.83 96.34  96.73 100.02  93.73
 [2,]  96.91 100.99 97.94 97.37 96.16 96.02 96.86  98.99  99.91  94.24
 [3,] 101.92 100.93 98.03 97.42 95.08 95.97 96.32 100.38  99.22  98.52
 [4,] 104.53  99.31 98.05 96.12 94.39 95.88 95.44 101.07  98.84  99.09
 [5,] 105.85  99.79 97.54 96.72 94.15 95.97 92.85  99.92  98.42  99.84
 [6,] 106.39  99.57 98.71 96.64 94.58 97.55 92.56 101.78  97.59  99.13
 [7,] 106.08  99.11 99.33 95.28 94.16 97.49 91.74 100.91  97.07 100.88
 [8,] 106.42  98.96 99.16 95.30 95.02 98.40 92.44 100.49  96.59 100.83
 [9,] 106.51  97.72 98.41 95.02 94.86 98.20 93.19 101.17  95.96 101.60
[10,] 106.59  99.35 98.43 95.57 94.49 97.16 92.62 100.25  94.22 101.80
[11,] 105.71  98.15 97.02 94.78 94.81 96.96 94.04  98.94  94.48 102.77
[12,] 104.41  97.64 97.89 95.27 94.16 96.37 93.80  99.40  93.14 103.14
> 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] 103.81500  99.54667  98.16667  96.11750  94.83333  96.73333  94.01667
 [8] 100.00250  97.12167  99.63083
> arr.sd
 [1] 4.0552334 1.5318517 0.6802050 1.0673427 0.6952218 1.0685107 1.7747539
 [8] 1.3537901 2.3026145 3.0068390
> arr.range
 [1] 12.13  5.40  2.31  3.14  2.01  3.57  5.12  5.05  6.88  9.41
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    -23.232        0.255  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -54.02          11.87  

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

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

Coefficients:
(Intercept)     arr.mean  
   -75.2689       0.8242  

> postscript(file="/var/wessaorg/rcomp/tmp/11gso1483956471.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/2h9rh1483956471.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/3dky11483956471.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/42luv1483956471.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5x19y1483956471.tab") 
> 
> try(system("convert tmp/11gso1483956471.ps tmp/11gso1483956471.png",intern=TRUE))
character(0)
> try(system("convert tmp/2h9rh1483956471.ps tmp/2h9rh1483956471.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.762   0.085   0.856