R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(93.61,93.17,91.60,90.30,90.88,91.06,92.05,95.29,96.44,96.49,96.52,96.09,99.16,98.09,99.41,99.87,100.06,99.65,99.92,98.44,102.64,112.33,115.63,118.29,121.43,129.96,147.73,154.10,150.09,144.14,141.54,136.68,129.32,118.99,109.61,106.22,104.97,102.45,101.91,101.77,102.67,103.45,101.41,102.45,102.17,101.40,101.68,100.61,97.93,98.30,99.79,101.62,101.55,102.43,102.09,102.01,102.26,101.24,100.91,100.67,100.33,99.99,99.23,98.17,97.38,96.70,98.65,100.68,101.07,101.12,101.13,99.88,99.20,99.91,103.62,108.05,113.96,117.39,126.04,139.67,145.04,142.37,137.72,132.46)
> 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] 84
> (np <- floor(n / par1))
[1] 7
> 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]
 [1,] 93.61  99.16 121.43 104.97  97.93 100.33  99.20
 [2,] 93.17  98.09 129.96 102.45  98.30  99.99  99.91
 [3,] 91.60  99.41 147.73 101.91  99.79  99.23 103.62
 [4,] 90.30  99.87 154.10 101.77 101.62  98.17 108.05
 [5,] 90.88 100.06 150.09 102.67 101.55  97.38 113.96
 [6,] 91.06  99.65 144.14 103.45 102.43  96.70 117.39
 [7,] 92.05  99.92 141.54 101.41 102.09  98.65 126.04
 [8,] 95.29  98.44 136.68 102.45 102.01 100.68 139.67
 [9,] 96.44 102.64 129.32 102.17 102.26 101.07 145.04
[10,] 96.49 112.33 118.99 101.40 101.24 101.12 142.37
[11,] 96.52 115.63 109.61 101.68 100.91 101.13 137.72
[12,] 96.09 118.29 106.22 100.61 100.67  99.88 132.46
> 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]  93.6250 103.6242 132.4842 102.2450 100.9000  99.5275 122.1192
> arr.sd
[1]  2.436844  7.308086 15.894027  1.123691  1.500339  1.510618 17.206810
> arr.range
[1]  6.22 20.20 47.88  4.36  4.50  4.43 45.84
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -43.0952       0.4621  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -34.962          7.769  

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

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

Coefficients:
(Intercept)     arr.mean  
   -124.880        1.335  

> postscript(file="/var/wessaorg/rcomp/tmp/1b6k41389557261.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/2jg5v1389557261.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/364xp1389557261.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/49dwz1389557261.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5jqgv1389557261.tab") 
> 
> try(system("convert tmp/1b6k41389557261.ps tmp/1b6k41389557261.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jg5v1389557261.ps tmp/2jg5v1389557261.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.509   0.568   3.045