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> x <- c(173019,173690,172439,171914,171968,169500,173898,172308,171568,164939,161275,160770,162466,160185,154836,154103,150495,142707,149962,149967,144572,143819,141070,144119,145330,143279,139063,139202,133632,134476,141859,140693,138047,138346,140167,146796,152228,155410,159032,160312,157687,160141,167421,167628,164403,163405,163229,171154,173323,172381,168983,165380,161641,161933,172018,168455,164332,161193,157645,161694,163411,161834,159511,156359,154223,151497,160607,159672,155601,154668,153960,157307,165218,165616,162212,159787,157454,156485,165887,166836,163541,163973,164805,167521,174347,173374,172198,171055,168385,167281,177670,177280,174846,174476,174595,178392,185345,183293,181081,177795,173552,170734,179293,178659,175894,174815,173506,175376)
> 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,] 173019 162466 145330 152228 173323 163411 165218 174347 185345
 [2,] 173690 160185 143279 155410 172381 161834 165616 173374 183293
 [3,] 172439 154836 139063 159032 168983 159511 162212 172198 181081
 [4,] 171914 154103 139202 160312 165380 156359 159787 171055 177795
 [5,] 171968 150495 133632 157687 161641 154223 157454 168385 173552
 [6,] 169500 142707 134476 160141 161933 151497 156485 167281 170734
 [7,] 173898 149962 141859 167421 172018 160607 165887 177670 179293
 [8,] 172308 149967 140693 167628 168455 159672 166836 177280 178659
 [9,] 171568 144572 138047 164403 164332 155601 163541 174846 175894
[10,] 164939 143819 138346 163405 161193 154668 163973 174476 174815
[11,] 161275 141070 140167 163229 157645 153960 164805 174595 173506
[12,] 160770 144119 146796 171154 161694 157307 167521 178392 175376
> 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] 169774.0 149858.4 140074.2 161837.5 165748.2 157387.5 163277.9 173658.2
[9] 177445.2
> arr.sd
[1] 4726.760 6971.049 3912.394 5447.565 5177.635 3621.384 3605.177 3470.885
[9] 4308.057
> arr.range
[1] 13128 21396 13164 18926 15678 11914 11036 11111 14611
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
 8283.35859     -0.02283  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      15.5077        -0.5922  

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

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

Coefficients:
(Intercept)     arr.mean  
  2.808e+04   -8.342e-02  

> postscript(file="/var/wessaorg/rcomp/tmp/1buy21448202667.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/2tsai1448202667.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/3i6pm1448202667.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4mrpb1448202667.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5tscu1448202667.tab") 
> 
> try(system("convert tmp/1buy21448202667.ps tmp/1buy21448202667.png",intern=TRUE))
character(0)
> try(system("convert tmp/2tsai1448202667.ps tmp/2tsai1448202667.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.855   0.132   0.988