R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(5204472,5185089,5165433,5124756,5527158,5505864,5204472,5004090,5023473,5023473,5045040,5083806,5144139,5144139,5105373,5004090,5527158,5606874,5486481,5204472,5325138,5144139,5225766,5264805,5305482,5204472,5225766,5083806,5527158,5667207,5546814,5325138,5566197,5305482,5546814,5527158,5587491,5365815,5606874,5587491,5949216,5867589,5546814,5385198,5606874,5305482,5527158,5566197,5647824,5467098,5566197,5626530,5848206,5667207,5426148,5165433,5406765,4743375,5064423,5245149,5426148,5165433,5165433,5165433,5305482,5105373,4842747,4622982,4782414,4159974,4541355,4763031,4803708,4582032,4601415,4541355,4743375,4601415,4321590,4119297,4461366,3718533,4200924,4420689,4420689,4159974,3918915,3899532,4119297,3918915,3537807,3275181,3557190,2894073,3496857,3817632,3918915,3697239,3417141,3617523,3697239,3636906,3033849,2754024,2954133,2351349,2973789,3195465,3376191,3074799,2792790,2954133,3033849,2874417,2271633,2009007,2250066,1586949,2310399,2754024)
> 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]
 [1,] 5204472 5144139 5305482 5587491 5647824 5426148 4803708 4420689 3918915
 [2,] 5185089 5144139 5204472 5365815 5467098 5165433 4582032 4159974 3697239
 [3,] 5165433 5105373 5225766 5606874 5566197 5165433 4601415 3918915 3417141
 [4,] 5124756 5004090 5083806 5587491 5626530 5165433 4541355 3899532 3617523
 [5,] 5527158 5527158 5527158 5949216 5848206 5305482 4743375 4119297 3697239
 [6,] 5505864 5606874 5667207 5867589 5667207 5105373 4601415 3918915 3636906
 [7,] 5204472 5486481 5546814 5546814 5426148 4842747 4321590 3537807 3033849
 [8,] 5004090 5204472 5325138 5385198 5165433 4622982 4119297 3275181 2754024
 [9,] 5023473 5325138 5566197 5606874 5406765 4782414 4461366 3557190 2954133
[10,] 5023473 5144139 5305482 5305482 4743375 4159974 3718533 2894073 2351349
[11,] 5045040 5225766 5546814 5527158 5064423 4541355 4200924 3496857 2973789
[12,] 5083806 5264805 5527158 5566197 5245149 4763031 4420689 3817632 3195465
        [,10]
 [1,] 3376191
 [2,] 3074799
 [3,] 2792790
 [4,] 2954133
 [5,] 3033849
 [6,] 2874417
 [7,] 2271633
 [8,] 2009007
 [9,] 2250066
[10,] 1586949
[11,] 2310399
[12,] 2754024
> 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] 5174760 5265214 5402624 5575183 5406196 4920484 4426308 3751338 3270631
[10] 2607355
> arr.sd
 [1] 175363.9 186072.9 182513.8 186735.9 307509.3 366633.7 301511.1 420238.8
 [9] 469252.9 519333.6
> arr.range
 [1]  523068  602784  583401  643734 1104831 1266174 1085175 1526616 1567566
[10] 1789242
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  8.298e+05   -1.132e-01  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       33.787         -1.386  

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

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

Coefficients:
(Intercept)     arr.mean  
  2.893e+06   -3.983e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1wx2t1439736538.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/2b1411439736538.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/3lbmx1439736538.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4i6bz1439736538.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/55wc91439736538.tab") 
> 
> try(system("convert tmp/1wx2t1439736538.ps tmp/1wx2t1439736538.png",intern=TRUE))
character(0)
> try(system("convert tmp/2b1411439736538.ps tmp/2b1411439736538.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.892   0.148   1.042