R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(5115,5105,5094,5074,5280,5270,5115,5012,5022,5022,5032,5053,5053,4960,4919,4960,5105,5084,4888,4722,4691,4629,4671,4722,4702,4660,4578,4660,4733,4712,4474,4371,4268,4185,4175,4237,4154,4123,4092,4268,4288,4185,3906,3782,3586,3503,3544,3606,3606,3555,3544,3710,3844,3782,3575,3472,3255,3121,3224,3327,3327,3193,3183,3358,3472,3431,3224,3090,2800,2687,2728,2904,2914,2656,2749,2976,3079,3017,2738,2542,2315,2139,2211,2366,2325,2098,2170,2397,2521,2449,2170,2046,1860,1664,1695,1850,1870,1684,1715,1974,2036,1932,1550,1354,1095,837,920,1033,1013,816,930,1209,1333,1271,1023,827,620,382,424,496)
> 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,] 5115 5053 4702 4154 3606 3327 2914 2325 1870  1013
 [2,] 5105 4960 4660 4123 3555 3193 2656 2098 1684   816
 [3,] 5094 4919 4578 4092 3544 3183 2749 2170 1715   930
 [4,] 5074 4960 4660 4268 3710 3358 2976 2397 1974  1209
 [5,] 5280 5105 4733 4288 3844 3472 3079 2521 2036  1333
 [6,] 5270 5084 4712 4185 3782 3431 3017 2449 1932  1271
 [7,] 5115 4888 4474 3906 3575 3224 2738 2170 1550  1023
 [8,] 5012 4722 4371 3782 3472 3090 2542 2046 1354   827
 [9,] 5022 4691 4268 3586 3255 2800 2315 1860 1095   620
[10,] 5022 4629 4185 3503 3121 2687 2139 1664  837   382
[11,] 5032 4671 4175 3544 3224 2728 2211 1695  920   424
[12,] 5053 4722 4237 3606 3327 2904 2366 1850 1033   496
> 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] 5099.500 4867.000 4479.583 3919.750 3501.250 3116.417 2641.833 2103.750
 [9] 1500.000  862.000
> arr.sd
 [1]  90.06513 172.37855 221.04687 301.05243 228.49672 274.88624 326.11622
 [8] 289.92918 436.66879 327.66141
> arr.range
 [1]  268  476  558  785  723  785  940  857 1199  951
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  445.19788     -0.05558  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       9.7225        -0.5294  

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

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

Coefficients:
(Intercept)     arr.mean  
  1284.8956      -0.1654  

> postscript(file="/var/wessaorg/rcomp/tmp/1g6981407862331.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/2pirk1407862331.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/3lh0w1407862331.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/40cjk1407862331.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/54d7o1407862331.tab") 
> 
> try(system("convert tmp/1g6981407862331.ps tmp/1g6981407862331.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pirk1407862331.ps tmp/2pirk1407862331.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.858   0.158   1.021