R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(64800,62400,66000,52800,68400,67200,72000,74400,82800,72000,68400,85200,72000,54000,63600,48000,67200,55200,73200,66000,69600,78000,76800,91200,66000,55200,61200,44400,63600,49200,69600,66000,58800,84000,75600,86400,64800,60000,54000,44400,58800,52800,72000,69600,60000,80400,74400,96000,76800,46800,46800,46800,55200,55200,74400,68400,61200,76800,70800,102000,80400,46800,49200,40800,56400,64800,81600,80400,64800,75600,67200,96000,73200,58800,52800,39600,58800,70800,82800,78000,57600,82800,64800,99600,82800,60000,55200,37200,58800,56400,85200,85200,64800,84000,62400,97200,82800,61200,46800,32400,63600,61200,80400,92400,68400,76800,57600,99600)
> 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,] 64800 72000 66000 64800  76800 80400 73200 82800 82800
 [2,] 62400 54000 55200 60000  46800 46800 58800 60000 61200
 [3,] 66000 63600 61200 54000  46800 49200 52800 55200 46800
 [4,] 52800 48000 44400 44400  46800 40800 39600 37200 32400
 [5,] 68400 67200 63600 58800  55200 56400 58800 58800 63600
 [6,] 67200 55200 49200 52800  55200 64800 70800 56400 61200
 [7,] 72000 73200 69600 72000  74400 81600 82800 85200 80400
 [8,] 74400 66000 66000 69600  68400 80400 78000 85200 92400
 [9,] 82800 69600 58800 60000  61200 64800 57600 64800 68400
[10,] 72000 78000 84000 80400  76800 75600 82800 84000 76800
[11,] 68400 76800 75600 74400  70800 67200 64800 62400 57600
[12,] 85200 91200 86400 96000 102000 96000 99600 97200 99600
> 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] 69700 67900 65000 65600 65100 67000 68300 69100 68600
> arr.sd
[1]  8690.434 11851.352 12718.490 13931.782 16462.519 16571.169 16224.897
[8] 17430.694 19013.871
> arr.range
[1] 32400 43200 42000 51600 55200 55200 60000 60000 67200
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
 22004.5691      -0.1074  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       23.988         -1.296  

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

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

Coefficients:
(Intercept)     arr.mean  
  3.685e+04    2.229e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1q5jk1437477741.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/2xr5x1437477741.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/3uvoo1437477741.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4mpu11437477741.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5vy171437477741.tab") 
> 
> try(system("convert tmp/1q5jk1437477741.ps tmp/1q5jk1437477741.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xr5x1437477741.ps tmp/2xr5x1437477741.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.905   0.149   1.058