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> x <- c(99.13,100.46,101.83,100.82,100.99,99.11,98.99,99.8,100.3,101.56,98.83,101.29,98.24,98.37,99.68,97.8,98.34,98.06,97.19,99.44,99.04,100.81,98.49,101.03,98.59,101.07,99.28,101.65,100.59,101.84,100.27,100.04,97.78,97.59,97.68,100.56,98.9,100.08,101.7,100.9,100.67,100.51,100.01,99.8,97.7,98.14,101.77,99.82,100.03,101.83,98.25,99.88,98.96,98.37,97.52,99.59,97.99,100.68,100.39,99.31,96.93,102.06,97.9,102.29,100.55,100.77,100.68,100.75,100.21,99.85,100.59,101.45)
> 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] 72
> (np <- floor(n / par1))
[1] 6
> 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]
 [1,]  99.13  98.24  98.59  98.90 100.03  96.93
 [2,] 100.46  98.37 101.07 100.08 101.83 102.06
 [3,] 101.83  99.68  99.28 101.70  98.25  97.90
 [4,] 100.82  97.80 101.65 100.90  99.88 102.29
 [5,] 100.99  98.34 100.59 100.67  98.96 100.55
 [6,]  99.11  98.06 101.84 100.51  98.37 100.77
 [7,]  98.99  97.19 100.27 100.01  97.52 100.68
 [8,]  99.80  99.44 100.04  99.80  99.59 100.75
 [9,] 100.30  99.04  97.78  97.70  97.99 100.21
[10,] 101.56 100.81  97.59  98.14 100.68  99.85
[11,]  98.83  98.49  97.68 101.77 100.39 100.59
[12,] 101.29 101.03 100.56  99.82  99.31 101.45
> 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] 100.25917  98.87417  99.74500 100.00000  99.40000 100.33583
> arr.sd
[1] 1.069099 1.172972 1.532505 1.264207 1.253881 1.549390
> arr.range
[1] 3.00 3.84 4.25 4.07 4.31 5.36
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -8.01312      0.09342  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -28.92           6.34  

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

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

Coefficients:
(Intercept)     arr.mean  
   -16.4054       0.2059  

> postscript(file="/var/wessaorg/rcomp/tmp/1udsh1463157823.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/2sdj71463157823.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/3g4pn1463157823.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4urr41463157823.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5uo7k1463157823.tab") 
> 
> try(system("convert tmp/1udsh1463157823.ps tmp/1udsh1463157823.png",intern=TRUE))
character(0)
> try(system("convert tmp/2sdj71463157823.ps tmp/2sdj71463157823.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.802   0.155   0.961