R version 3.2.2 (2015-08-14) -- "Fire Safety"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(79.58,80.08,80.41,80.34,80.32,80.39,81.01,81.54,82.48,84.68,88.26,90.6,92.46,93.31,93.58,93.92,93.92,93.67,93.76,93.95,93.89,94.07,93.93,93.35,93.58,93.55,93.44,93.38,93.17,92.95,93.37,94.13,94.07,94,94.47,94.81,94.18,94.14,93.96,93.23,93.13,92.51,92.49,92.73,92.75,92.83,92.85,93.27,93.98,94.34,94.57,94.62,94.82,95.07,95.72,96.06,96.54,96.38,96.8,97.02,97.29,97.45,97.95,97.69,97.63,97.35,97.38,98.06,98.34,98.53,98.79,98.77,99.2,99.76,99.84,99.83,99.88,99.48,99.66,99.58,99.89,100.7,101.19,100.99,101.52,101.75,101.56,102.57,102.66,102.62,102.76,102.73,102.26,101.72,101.48,100.93)
> 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] 96
> (np <- floor(n / par1))
[1] 8
> 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]
 [1,] 79.58 92.46 93.58 94.18 93.98 97.29  99.20 101.52
 [2,] 80.08 93.31 93.55 94.14 94.34 97.45  99.76 101.75
 [3,] 80.41 93.58 93.44 93.96 94.57 97.95  99.84 101.56
 [4,] 80.34 93.92 93.38 93.23 94.62 97.69  99.83 102.57
 [5,] 80.32 93.92 93.17 93.13 94.82 97.63  99.88 102.66
 [6,] 80.39 93.67 92.95 92.51 95.07 97.35  99.48 102.62
 [7,] 81.01 93.76 93.37 92.49 95.72 97.38  99.66 102.76
 [8,] 81.54 93.95 94.13 92.73 96.06 98.06  99.58 102.73
 [9,] 82.48 93.89 94.07 92.75 96.54 98.34  99.89 102.26
[10,] 84.68 94.07 94.00 92.83 96.38 98.53 100.70 101.72
[11,] 88.26 93.93 94.47 92.85 96.80 98.79 101.19 101.48
[12,] 90.60 93.35 94.81 93.27 97.02 98.77 100.99 100.93
> 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]  82.47417  93.65083  93.74333  93.17250  95.49333  97.93583 100.00000
[8] 102.04667
> arr.sd
[1] 3.5585376 0.4459201 0.5537859 0.6094875 1.0514262 0.5573225 0.6199120
[8] 0.6235577
> arr.range
[1] 11.02  1.61  1.86  1.69  3.04  1.50  1.99  1.83
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    14.7706      -0.1452  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       36.053         -7.981  

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

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

Coefficients:
(Intercept)     arr.mean  
     46.210       -0.455  

> postscript(file="/var/wessaorg/rcomp/tmp/1lyoe1447713407.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/2263r1447713407.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/300r01447713407.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/46nh21447713407.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5bx2l1447713407.tab") 
> 
> try(system("convert tmp/1lyoe1447713407.ps tmp/1lyoe1447713407.png",intern=TRUE))
character(0)
> try(system("convert tmp/2263r1447713407.ps tmp/2263r1447713407.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.902   0.152   1.051