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(19064.00
+ ,18993.00
+ ,18921.00
+ ,18772.00
+ ,20246.00
+ ,20168.00
+ ,19064.00
+ ,18330.00
+ ,18401.00
+ ,18401.00
+ ,18480.00
+ ,18622.00
+ ,18843.00
+ ,18843.00
+ ,18701.00
+ ,18330.00
+ ,20246.00
+ ,20538.00
+ ,20097.00
+ ,19064.00
+ ,19506.00
+ ,18843.00
+ ,19142.00
+ ,19285.00
+ ,19434.00
+ ,19064.00
+ ,19142.00
+ ,18622.00
+ ,20246.00
+ ,20759.00
+ ,20318.00
+ ,19506.00
+ ,20389.00
+ ,19434.00
+ ,20318.00
+ ,20246.00
+ ,20467.00
+ ,19655.00
+ ,20538.00
+ ,20467.00
+ ,21792.00
+ ,21493.00
+ ,20318.00
+ ,19726.00
+ ,20538.00
+ ,19434.00
+ ,20246.00
+ ,20389.00
+ ,20688.00
+ ,20026.00
+ ,20389.00
+ ,20610.00
+ ,21422.00
+ ,20759.00
+ ,19876.00
+ ,18921.00
+ ,19805.00
+ ,17375.00
+ ,18551.00
+ ,19213.00
+ ,19876.00
+ ,18921.00
+ ,18921.00
+ ,18921.00
+ ,19434.00
+ ,18701.00
+ ,17739.00
+ ,16934.00
+ ,17518.00
+ ,15238.00
+ ,16635.00
+ ,17447.00
+ ,17596.00
+ ,16784.00
+ ,16855.00
+ ,16635.00
+ ,17375.00
+ ,16855.00
+ ,15830.00
+ ,15089.00
+ ,16342.00
+ ,13621.00
+ ,15388.00
+ ,16193.00
+ ,16193.00
+ ,15238.00
+ ,14355.00
+ ,14284.00
+ ,15089.00
+ ,14355.00
+ ,12959.00
+ ,11997.00
+ ,13030.00
+ ,10601.00
+ ,12809.00
+ ,13984.00
+ ,14355.00
+ ,13543.00
+ ,12517.00
+ ,13251.00
+ ,13543.00
+ ,13322.00
+ ,11113.00
+ ,10088.00
+ ,10821.00
+ ,8613.00
+ ,10893.00
+ ,11705.00
+ ,12367.00
+ ,11263.00
+ ,10230.00
+ ,10821.00
+ ,11113.00
+ ,10529.00
+ ,8321.00
+ ,7359.00
+ ,8242.00
+ ,5813.00
+ ,8463.00
+ ,10088.00)
> 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] [,10]
 [1,] 19064 18843 19434 20467 20688 19876 17596 16193 14355 12367
 [2,] 18993 18843 19064 19655 20026 18921 16784 15238 13543 11263
 [3,] 18921 18701 19142 20538 20389 18921 16855 14355 12517 10230
 [4,] 18772 18330 18622 20467 20610 18921 16635 14284 13251 10821
 [5,] 20246 20246 20246 21792 21422 19434 17375 15089 13543 11113
 [6,] 20168 20538 20759 21493 20759 18701 16855 14355 13322 10529
 [7,] 19064 20097 20318 20318 19876 17739 15830 12959 11113  8321
 [8,] 18330 19064 19506 19726 18921 16934 15089 11997 10088  7359
 [9,] 18401 19506 20389 20538 19805 17518 16342 13030 10821  8242
[10,] 18401 18843 19434 19434 17375 15238 13621 10601  8613  5813
[11,] 18480 19142 20318 20246 18551 16635 15388 12809 10893  8463
[12,] 18622 19285 20246 20389 19213 17447 16193 13984 11705 10088
> 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] 18955.17 19286.50 19789.83 20421.92 19802.92 18023.75 16213.58 13741.17
 [9] 11980.33  9550.75
> arr.sd
 [1]  642.3587  681.5858  668.5489  684.0144 1126.4078 1342.9806 1104.4364
 [8] 1539.3361 1718.8752 1902.3208
> arr.range
 [1] 1916 2208 2137 2358 4047 4638 3975 5592 5742 6554
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  3039.3879      -0.1132  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       20.404         -1.386  

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

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

Coefficients:
(Intercept)     arr.mean  
 10598.3403      -0.3983  

> postscript(file="/var/wessaorg/rcomp/tmp/1b6x51438966830.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/27ar11438966830.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/3mjxl1438966830.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4zjlt1438966830.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5mpt61438966830.tab") 
> 
> try(system("convert tmp/1b6x51438966830.ps tmp/1b6x51438966830.png",intern=TRUE))
character(0)
> try(system("convert tmp/27ar11438966830.ps tmp/27ar11438966830.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.952   0.175   1.130