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(133448.00
+ ,132951.00
+ ,132447.00
+ ,131404.00
+ ,141722.00
+ ,141176.00
+ ,133448.00
+ ,128310.00
+ ,128807.00
+ ,128807.00
+ ,129360.00
+ ,130354.00
+ ,131901.00
+ ,131901.00
+ ,130907.00
+ ,128310.00
+ ,141722.00
+ ,143766.00
+ ,140679.00
+ ,133448.00
+ ,136542.00
+ ,131901.00
+ ,133994.00
+ ,134995.00
+ ,136038.00
+ ,133448.00
+ ,133994.00
+ ,130354.00
+ ,141722.00
+ ,145313.00
+ ,142226.00
+ ,136542.00
+ ,142723.00
+ ,136038.00
+ ,142226.00
+ ,141722.00
+ ,143269.00
+ ,137585.00
+ ,143766.00
+ ,143269.00
+ ,152544.00
+ ,150451.00
+ ,142226.00
+ ,138082.00
+ ,143766.00
+ ,136038.00
+ ,141722.00
+ ,142723.00
+ ,144816.00
+ ,140182.00
+ ,142723.00
+ ,144270.00
+ ,149954.00
+ ,145313.00
+ ,139132.00
+ ,132447.00
+ ,138635.00
+ ,121625.00
+ ,129857.00
+ ,134491.00
+ ,139132.00
+ ,132447.00
+ ,132447.00
+ ,132447.00
+ ,136038.00
+ ,130907.00
+ ,124173.00
+ ,118538.00
+ ,122626.00
+ ,106666.00
+ ,116445.00
+ ,122129.00
+ ,123172.00
+ ,117488.00
+ ,117985.00
+ ,116445.00
+ ,121625.00
+ ,117985.00
+ ,110810.00
+ ,105623.00
+ ,114394.00
+ ,95347.00
+ ,107716.00
+ ,113351.00
+ ,113351.00
+ ,106666.00
+ ,100485.00
+ ,99988.00
+ ,105623.00
+ ,100485.00
+ ,90713.00
+ ,83979.00
+ ,91210.00
+ ,74207.00
+ ,89663.00
+ ,97888.00
+ ,100485.00
+ ,94801.00
+ ,87619.00
+ ,92757.00
+ ,94801.00
+ ,93254.00
+ ,77791.00
+ ,70616.00
+ ,75747.00
+ ,60291.00
+ ,76251.00
+ ,81935.00
+ ,86569.00
+ ,78841.00
+ ,71610.00
+ ,75747.00
+ ,77791.00
+ ,73703.00
+ ,58247.00
+ ,51513.00
+ ,57694.00
+ ,40691.00
+ ,59241.00
+ ,70616.00)
> 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,] 133448 131901 136038 143269 144816 139132 123172 113351 100485 86569
 [2,] 132951 131901 133448 137585 140182 132447 117488 106666  94801 78841
 [3,] 132447 130907 133994 143766 142723 132447 117985 100485  87619 71610
 [4,] 131404 128310 130354 143269 144270 132447 116445  99988  92757 75747
 [5,] 141722 141722 141722 152544 149954 136038 121625 105623  94801 77791
 [6,] 141176 143766 145313 150451 145313 130907 117985 100485  93254 73703
 [7,] 133448 140679 142226 142226 139132 124173 110810  90713  77791 58247
 [8,] 128310 133448 136542 138082 132447 118538 105623  83979  70616 51513
 [9,] 128807 136542 142723 143766 138635 122626 114394  91210  75747 57694
[10,] 128807 131901 136038 136038 121625 106666  95347  74207  60291 40691
[11,] 129360 133994 142226 141722 129857 116445 107716  89663  76251 59241
[12,] 130354 134995 141722 142723 134491 122129 113351  97888  81935 70616
> 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] 132686.17 135005.50 138528.83 142953.42 138620.42 126166.25 113495.08
 [8]  96188.17  83862.33  66855.25
> arr.sd
 [1]  4496.511  4771.100  4679.842  4788.101  7884.855  9400.864  7731.055
 [8] 10775.353 12032.127 13316.246
> arr.range
 [1] 13412 15456 14959 16506 28329 32466 27825 39144 40194 45878
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
 21275.7152      -0.1132  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       25.046         -1.386  

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

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

Coefficients:
(Intercept)     arr.mean  
 74188.3818      -0.3983  

> postscript(file="/var/wessaorg/rcomp/tmp/13lbf1439716106.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/2sjve1439716106.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/3r5d01439716106.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4kxl71439716106.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/56b8y1439716106.tab") 
> 
> try(system("convert tmp/13lbf1439716106.ps tmp/13lbf1439716106.png",intern=TRUE))
character(0)
> try(system("convert tmp/2sjve1439716106.ps tmp/2sjve1439716106.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.929   0.162   1.096