R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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> x <- c(1053000,1014000,1072500,858000,1111500,1092000,1170000,1209000,1345500,1170000,1111500,1384500,1170000,877500,1033500,780000,1092000,897000,1189500,1072500,1131000,1267500,1248000,1482000,1072500,897000,994500,721500,1033500,799500,1131000,1072500,955500,1365000,1228500,1404000,1053000,975000,877500,721500,955500,858000,1170000,1131000,975000,1306500,1209000,1560000,1248000,760500,760500,760500,897000,897000,1209000,1111500,994500,1248000,1150500,1657500,1306500,760500,799500,663000,916500,1053000,1326000,1306500,1053000,1228500,1092000,1560000,1189500,955500,858000,643500,955500,1150500,1345500,1267500,936000,1345500,1053000,1618500,1345500,975000,897000,604500,955500,916500,1384500,1384500,1053000,1365000,1014000,1579500,1345500,994500,760500,526500,1033500,994500,1306500,1501500,1111500,1248000,936000,1618500)
> 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,] 1053000 1170000 1072500 1053000 1248000 1306500 1189500 1345500 1345500
 [2,] 1014000  877500  897000  975000  760500  760500  955500  975000  994500
 [3,] 1072500 1033500  994500  877500  760500  799500  858000  897000  760500
 [4,]  858000  780000  721500  721500  760500  663000  643500  604500  526500
 [5,] 1111500 1092000 1033500  955500  897000  916500  955500  955500 1033500
 [6,] 1092000  897000  799500  858000  897000 1053000 1150500  916500  994500
 [7,] 1170000 1189500 1131000 1170000 1209000 1326000 1345500 1384500 1306500
 [8,] 1209000 1072500 1072500 1131000 1111500 1306500 1267500 1384500 1501500
 [9,] 1345500 1131000  955500  975000  994500 1053000  936000 1053000 1111500
[10,] 1170000 1267500 1365000 1306500 1248000 1228500 1345500 1365000 1248000
[11,] 1111500 1248000 1228500 1209000 1150500 1092000 1053000 1014000  936000
[12,] 1384500 1482000 1404000 1560000 1657500 1560000 1618500 1579500 1618500
> 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] 1132625 1103375 1056250 1066000 1057875 1088750 1109875 1122875 1114750
> arr.sd
[1] 141219.5 192584.5 206675.5 226391.5 267515.9 269281.5 263654.6 283248.8
[9] 308975.4
> arr.range
[1]  526500  702000  682500  838500  897000  897000  975000  975000 1092000
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  3.576e+05   -1.074e-01  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       30.390         -1.296  

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

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

Coefficients:
(Intercept)     arr.mean  
  5.988e+05    2.229e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1g8g11439206970.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/2rp9q1439206970.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/31xhb1439206970.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4xof11439206970.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/531nr1439206970.tab") 
> 
> try(system("convert tmp/1g8g11439206970.ps tmp/1g8g11439206970.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rp9q1439206970.ps tmp/2rp9q1439206970.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.879   0.146   1.031