R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(71.59,71.65,71.47,71.82,71.76,71.88,73.31,73.22,72.74,72.95,73.71,74.45,76.54,77.41,76.87,76.51,75.66,75.09,75.16,75,75.05,74.78,75.43,75.61,77.12,83.09,86.09,87.64,88.29,89.3,89.99,90.43,91.03,91.4,92.19,92.45,92.42,90.2,88.23,84.91,82.92,81.8,81.7,83.22,82.7,82.83,83.66,84.28,84.37,86.49,87.62,88.59,89.74,89.73,89.14,88.37,88.65,89.16,89.56,89.37,89.67,93.04,94.4,95.5,101.66,102.86,102.48,102.02,101.83,101.3,101.29,100.53,100.45,101.88,101.95,102.18,100.95,100.52,100.39,99.61,99.43,99.34,100.73,102.14,102.22,101.14,100.91,101.62,100,99.92,100.07,98.48,98.3,98.86,98.96,99.52,99.06,100.47,100.24,86.43,85.14,85.41,86.13,86.19,86.29,87.55,87.87,88.37)
> 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] 108
> (np <- floor(n / par1))
[1] 9
> 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]
 [1,] 71.59 76.54 77.12 92.42 84.37  89.67 100.45 102.22  99.06
 [2,] 71.65 77.41 83.09 90.20 86.49  93.04 101.88 101.14 100.47
 [3,] 71.47 76.87 86.09 88.23 87.62  94.40 101.95 100.91 100.24
 [4,] 71.82 76.51 87.64 84.91 88.59  95.50 102.18 101.62  86.43
 [5,] 71.76 75.66 88.29 82.92 89.74 101.66 100.95 100.00  85.14
 [6,] 71.88 75.09 89.30 81.80 89.73 102.86 100.52  99.92  85.41
 [7,] 73.31 75.16 89.99 81.70 89.14 102.48 100.39 100.07  86.13
 [8,] 73.22 75.00 90.43 83.22 88.37 102.02  99.61  98.48  86.19
 [9,] 72.74 75.05 91.03 82.70 88.65 101.83  99.43  98.30  86.29
[10,] 72.95 74.78 91.40 82.83 89.16 101.30  99.34  98.86  87.55
[11,] 73.71 75.43 92.19 83.66 89.56 101.29 100.73  98.96  87.87
[12,] 74.45 75.61 92.45 84.28 89.37 100.53 102.14  99.52  88.37
> 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]  72.54583  75.75917  88.25167  84.90583  88.39917  98.88167 100.79750
[8] 100.00000  89.92917
> arr.sd
[1] 0.9854345 0.8590635 4.4234783 3.4820147 1.5832387 4.4711435 1.0448934
[8] 1.2614494 6.1080267
> arr.range
[1]  2.98  2.63 15.33 10.72  5.37 13.19  2.84  3.92 15.33
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.99019      0.04144  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -8.013          1.952  

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

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

Coefficients:
(Intercept)     arr.mean  
    -1.8035       0.1108  

> postscript(file="/var/wessaorg/rcomp/tmp/1wtou1447870806.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/2q2d21447870806.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/39j0r1447870806.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4q8to1447870806.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5r4ar1447870806.tab") 
> 
> try(system("convert tmp/1wtou1447870806.ps tmp/1wtou1447870806.png",intern=TRUE))
character(0)
> try(system("convert tmp/2q2d21447870806.ps tmp/2q2d21447870806.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.892   0.142   1.038