R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(2120,2100,2080,2040,2440,2420,2120,1920,1940,1940,1960,2000,2120,2080,2140,2240,2800,2800,2680,2560,2660,2780,2800,2860,3040,2920,2920,3100,3600,3640,3540,3300,3480,3480,3500,3600,3680,3720,3720,3840,4300,4420,4440,4140,4300,4240,4120,4380,4440,4340,4360,4500,5020,5280,5280,5160,5340,5160,5060,5440,5500,5360,5720,5860,6280,6560,6520,6500,6660,6640,6400,6760,6880,6760,7260,7500,8060,8280,8220,8100,8200,8320,7920,8240,8440,8360,8880,9060,9820,9960,9780,9880,9940,10000,9620,9980,10180,9980,10560,10740,11520,11640,11680,11880,11880,11960,11600,11780,11900,11680,12320,12440,13240,13380,13580,13760,13780,13800,13440,13800)
> 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,] 2120 2120 3040 3680 4440 5500 6880  8440 10180 11900
 [2,] 2100 2080 2920 3720 4340 5360 6760  8360  9980 11680
 [3,] 2080 2140 2920 3720 4360 5720 7260  8880 10560 12320
 [4,] 2040 2240 3100 3840 4500 5860 7500  9060 10740 12440
 [5,] 2440 2800 3600 4300 5020 6280 8060  9820 11520 13240
 [6,] 2420 2800 3640 4420 5280 6560 8280  9960 11640 13380
 [7,] 2120 2680 3540 4440 5280 6520 8220  9780 11680 13580
 [8,] 1920 2560 3300 4140 5160 6500 8100  9880 11880 13760
 [9,] 1940 2660 3480 4300 5340 6660 8200  9940 11880 13780
[10,] 1940 2780 3480 4240 5160 6640 8320 10000 11960 13800
[11,] 1960 2800 3500 4120 5060 6400 7920  9620 11600 13440
[12,] 2000 2860 3600 4380 5440 6760 8240  9980 11780 13800
> 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]  2090.000  2543.333  3343.333  4108.333  4948.333  6230.000  7811.667
 [8]  9476.667 11283.333 13093.333
> arr.sd
 [1] 174.4602 306.7523 274.9986 290.7618 415.3823 487.8524 564.9430 619.3741
 [9] 712.9877 787.5085
> arr.range
 [1]  520  780  720  760 1100 1400 1560 1640 1980 2120
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  119.52286      0.05298  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -0.3870         0.7465  

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

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

Coefficients:
(Intercept)     arr.mean  
   314.8903       0.1453  

> postscript(file="/var/www/rcomp/tmp/110xq1344330881.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/www/rcomp/tmp/29skv1344330881.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/rcomp/tmp/3fs301344330881.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4ta2v1344330881.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/www/rcomp/tmp/5ny9j1344330881.tab") 
> 
> try(system("convert tmp/110xq1344330881.ps tmp/110xq1344330881.png",intern=TRUE))
character(0)
> try(system("convert tmp/29skv1344330881.ps tmp/29skv1344330881.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.620   0.400   1.012