R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> x <- c(1943,1932,1922,1901,2108,2098,1943,1839,1850,1850,1860,1881,1839,1819,1757,1664,1922,1839,1633,1674,1633,1736,1591,1684,1602,1581,1416,1354,1664,1602,1405,1529,1426,1509,1426,1571,1447,1426,1230,1168,1612,1509,1333,1498,1374,1333,1312,1416,1240,1240,1095,1044,1560,1426,1302,1405,1261,1199,1250,1405,1199,1281,1178,1137,1591,1498,1250,1374,1312,1354,1426,1622,1488,1540,1457,1395,1860,1746,1467,1426,1343,1374,1354,1529,1343,1405,1364,1323,1829,1726,1447,1343,1188,1199,1178,1323,1064,1054,1013,899,1467,1405,1095,1002,847,816,713,858,486,444,403,331,940,889,568,506,351,362,300,403)
> 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,] 1943 1839 1602 1447 1240 1199 1488 1343 1064   486
 [2,] 1932 1819 1581 1426 1240 1281 1540 1405 1054   444
 [3,] 1922 1757 1416 1230 1095 1178 1457 1364 1013   403
 [4,] 1901 1664 1354 1168 1044 1137 1395 1323  899   331
 [5,] 2108 1922 1664 1612 1560 1591 1860 1829 1467   940
 [6,] 2098 1839 1602 1509 1426 1498 1746 1726 1405   889
 [7,] 1943 1633 1405 1333 1302 1250 1467 1447 1095   568
 [8,] 1839 1674 1529 1498 1405 1374 1426 1343 1002   506
 [9,] 1850 1633 1426 1374 1261 1312 1343 1188  847   351
[10,] 1850 1736 1509 1333 1199 1354 1374 1199  816   362
[11,] 1860 1591 1426 1312 1250 1426 1354 1178  713   300
[12,] 1881 1684 1571 1416 1405 1622 1529 1323  858   403
> 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] 1927.2500 1732.5833 1507.0833 1388.1667 1285.5833 1351.8333 1498.2500
 [8] 1389.0000 1019.4167  498.5833
> arr.sd
 [1]  90.17470 103.12345  99.07523 123.58717 145.23302 157.89976 157.81008
 [8] 201.21901 226.39445 209.22213
> arr.range
 [1] 269 331 310 444 516 485 517 651 754 640
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  284.51517     -0.09791  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       9.3523        -0.6115  

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

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

Coefficients:
(Intercept)     arr.mean  
    914.563       -0.311  

> postscript(file="/var/wessaorg/rcomp/tmp/1se9u1468831533.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/294ve1468831533.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/3de6h1468831533.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4ef231468831533.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/515ms1468831533.tab") 
> 
> try(system("convert tmp/1se9u1468831533.ps tmp/1se9u1468831533.png",intern=TRUE))
character(0)
> try(system("convert tmp/294ve1468831533.ps tmp/294ve1468831533.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.852   0.059   0.923