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(76.93,79.32,79.35,80.94,80.13,81.38,81.1,81.53,80.46,79.71,78.66,79.96,80.64,81.8,81.06,81.67,79.72,81.28,81.36,85.26,90,93,95.62,102.15,105.73,109.79,113.77,114.3,114.76,113.69,113.88,114.47,112.57,114.43,112.7,113.48,113.05,112.22,111.44,111.67,111.91,111.7,104.26,101.13,98.55,97.06,96.22,95.15,94.54,94.29,93.98,93.76,94.16,93.83,93.97,94.19,94.14,94.24,94.27,94.21,93.45,95.84,98.59,97,96.45,96.48,96.1,95.49,95.85,95.85,98.52,101.77,101.2,102.85,102.98,102.87,100.48,97.59,97.55,99.06,100.43,102.93,104.22,105.26,105.44,106.97,105.82,104.4,102.03,100.17,98.01,96.49,95.63,95.4,94.97,94.68,95.87,94.99,94.65,94.35,94.1,94.21,95.2,95.55,95.68,95.27,95.3,95.93)
> 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] 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,] 76.93  80.64 105.73 113.05 94.54  93.45 101.20 105.44 95.87
 [2,] 79.32  81.80 109.79 112.22 94.29  95.84 102.85 106.97 94.99
 [3,] 79.35  81.06 113.77 111.44 93.98  98.59 102.98 105.82 94.65
 [4,] 80.94  81.67 114.30 111.67 93.76  97.00 102.87 104.40 94.35
 [5,] 80.13  79.72 114.76 111.91 94.16  96.45 100.48 102.03 94.10
 [6,] 81.38  81.28 113.69 111.70 93.83  96.48  97.59 100.17 94.21
 [7,] 81.10  81.36 113.88 104.26 93.97  96.10  97.55  98.01 95.20
 [8,] 81.53  85.26 114.47 101.13 94.19  95.49  99.06  96.49 95.55
 [9,] 80.46  90.00 112.57  98.55 94.14  95.85 100.43  95.63 95.68
[10,] 79.71  93.00 114.43  97.06 94.24  95.85 102.93  95.40 95.27
[11,] 78.66  95.62 112.70  96.22 94.27  98.52 104.22  94.97 95.30
[12,] 79.96 102.15 113.48  95.15 94.21 101.77 105.26  94.68 95.93
> 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]  79.95583  86.13000 112.79750 105.36333  94.13167  96.78250 101.45167
[8] 100.00083  95.09167
> arr.sd
[1] 1.3050633 7.3328662 2.5938218 7.3126843 0.2156105 2.0732018 2.4965825
[8] 4.7261083 0.6373216
> arr.range
[1]  4.60 22.43  9.03 17.90  0.78  8.32  7.71 12.29  1.83
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.25429      0.03554  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -10.108          2.368  

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

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

Coefficients:
(Intercept)     arr.mean  
    3.63436      0.05986  

> postscript(file="/var/wessaorg/rcomp/tmp/18bjz1447955049.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/2j8i91447955049.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/31i6p1447955049.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4dihs1447955049.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/56txy1447955049.tab") 
> 
> try(system("convert tmp/18bjz1447955049.ps tmp/18bjz1447955049.png",intern=TRUE))
character(0)
> try(system("convert tmp/2j8i91447955049.ps tmp/2j8i91447955049.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.846   0.188   1.039