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(209.704,208.923,208.131,206.492,222.706,221.848,209.704,201.630,202.411,202.411,203.280,204.842,207.273,207.273,205.711,201.630,222.706,225.918,221.067,209.704,214.566,207.273,210.562,212.135,213.774,209.704,210.562,204.842,222.706,228.349,223.498,214.566,224.279,213.774,223.498,222.706,225.137,216.205,225.918,225.137,239.712,236.423,223.498,216.986,225.918,213.774,222.706,224.279,227.568,220.286,224.279,226.710,235.642,228.349,218.636,208.131,217.855,191.125,204.061,211.343,218.636,208.131,208.131,208.131,213.774,205.711,195.129,186.274,192.698,167.618,182.985,191.917,193.556,184.624,185.405,182.985,191.125,185.405,174.130,165.979,179.762,149.831,169.268,178.123,178.123,167.618,157.905,157.124,165.979,157.905,142.549,131.967,143.330,116.611,140.899,153.824,157.905,148.973,137.687,145.761,148.973,146.542,122.243,110.968,119.031,94.743,119.823,128.755,136.037,123.893,112.530,119.031,122.243,115.819,91.531,80.949,90.662,63.943,93.093,110.968)
> 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]
 [1,] 209.704 207.273 213.774 225.137 227.568 218.636 193.556 178.123 157.905
 [2,] 208.923 207.273 209.704 216.205 220.286 208.131 184.624 167.618 148.973
 [3,] 208.131 205.711 210.562 225.918 224.279 208.131 185.405 157.905 137.687
 [4,] 206.492 201.630 204.842 225.137 226.710 208.131 182.985 157.124 145.761
 [5,] 222.706 222.706 222.706 239.712 235.642 213.774 191.125 165.979 148.973
 [6,] 221.848 225.918 228.349 236.423 228.349 205.711 185.405 157.905 146.542
 [7,] 209.704 221.067 223.498 223.498 218.636 195.129 174.130 142.549 122.243
 [8,] 201.630 209.704 214.566 216.986 208.131 186.274 165.979 131.967 110.968
 [9,] 202.411 214.566 224.279 225.918 217.855 192.698 179.762 143.330 119.031
[10,] 202.411 207.273 213.774 213.774 191.125 167.618 149.831 116.611  94.743
[11,] 203.280 210.562 223.498 222.706 204.061 182.985 169.268 140.899 119.823
[12,] 204.842 212.135 222.706 224.279 211.343 191.917 178.123 153.824 128.755
        [,10]
 [1,] 136.037
 [2,] 123.893
 [3,] 112.530
 [4,] 119.031
 [5,] 122.243
 [6,] 115.819
 [7,]  91.531
 [8,]  80.949
 [9,]  90.662
[10,]  63.943
[11,]  93.093
[12,] 110.968
> 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] 208.5068 212.1515 217.6882 224.6411 217.8321 198.2612 178.3494 151.1528
 [9] 131.7837 105.0583
> arr.sd
 [1]  7.065946  7.497444  7.354038  7.524159 12.390486 14.772787 12.148800
 [8] 16.932697 18.907628 20.925529
> arr.range
 [1] 21.076 24.288 23.507 25.938 44.517 51.018 43.725 61.512 63.162 72.094
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    33.4333      -0.1132  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
        9.644         -1.386  

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

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

Coefficients:
(Intercept)     arr.mean  
   116.5817      -0.3983  

> postscript(file="/var/wessaorg/rcomp/tmp/1rjb21437393051.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/26nsi1437393051.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/3jjpu1437393051.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4uvy61437393051.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5w5p11437393051.tab") 
> 
> try(system("convert tmp/1rjb21437393051.ps tmp/1rjb21437393051.png",intern=TRUE))
character(0)
> try(system("convert tmp/26nsi1437393051.ps tmp/26nsi1437393051.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.876   0.152   1.032