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(4213144,4197453,4181541,4148612,4474366,4457128,4213144,4050930,4066621,4066621,4084080,4115462,4164303,4164303,4132921,4050930,4474366,4538898,4441437,4213144,4310826,4164303,4230382,4261985,4294914,4213144,4230382,4115462,4474366,4587739,4490278,4310826,4505969,4294914,4490278,4474366,4523207,4343755,4538898,4523207,4816032,4749953,4490278,4359446,4538898,4294914,4474366,4505969,4572048,4425746,4505969,4554810,4734262,4587739,4392596,4181541,4376905,3839875,4099771,4246073,4392596,4181541,4181541,4181541,4294914,4132921,3920319,3742414,3871478,3367598,3676335,3855787,3888716,3709264,3724955,3676335,3839875,3724955,3498430,3334669,3611582,3010241,3400748,3578653,3578653,3367598,3172455,3156764,3334669,3172455,2863939,2651337,2879630,2342821,2830789,3090464,3172455,2993003,2766257,2928471,2993003,2944162,2455973,2229448,2391441,1903473,2407353,2586805,2733107,2489123,2260830,2391441,2455973,2326909,1838941,1626339,1821482,1284673,1870323,2229448)
> par1 = '12'
> par1 <- '12'
> 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,] 4213144 4164303 4294914 4523207 4572048 4392596 3888716 3578653 3172455
 [2,] 4197453 4164303 4213144 4343755 4425746 4181541 3709264 3367598 2993003
 [3,] 4181541 4132921 4230382 4538898 4505969 4181541 3724955 3172455 2766257
 [4,] 4148612 4050930 4115462 4523207 4554810 4181541 3676335 3156764 2928471
 [5,] 4474366 4474366 4474366 4816032 4734262 4294914 3839875 3334669 2993003
 [6,] 4457128 4538898 4587739 4749953 4587739 4132921 3724955 3172455 2944162
 [7,] 4213144 4441437 4490278 4490278 4392596 3920319 3498430 2863939 2455973
 [8,] 4050930 4213144 4310826 4359446 4181541 3742414 3334669 2651337 2229448
 [9,] 4066621 4310826 4505969 4538898 4376905 3871478 3611582 2879630 2391441
[10,] 4066621 4164303 4294914 4294914 3839875 3367598 3010241 2342821 1903473
[11,] 4084080 4230382 4490278 4474366 4099771 3676335 3400748 2830789 2407353
[12,] 4115462 4261985 4474366 4505969 4246073 3855787 3578653 3090464 2586805
        [,10]
 [1,] 2733107
 [2,] 2489123
 [3,] 2260830
 [4,] 2391441
 [5,] 2455973
 [6,] 2326909
 [7,] 1838941
 [8,] 1626339
 [9,] 1821482
[10,] 1284673
[11,] 1870323
[12,] 2229448
> 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] 4189092 4262316 4373553 4513244 4376445 3983249 3583202 3036798 2647654
[10] 2110716
> arr.sd
 [1] 141961.3 150630.5 147749.3 151167.2 248936.1 296798.7 244080.4 340193.3
 [9] 379871.4 420412.9
> arr.range
 [1]  423436  487968  472277  521118  894387 1024998  878475 1235832 1268982
[10] 1448434
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  6.717e+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)  
       33.283         -1.386  

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

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

Coefficients:
(Intercept)     arr.mean  
  2.342e+06   -3.983e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1rdmh1436570103.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/27vbg1436570103.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/3u9h41436570103.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4e4is1436570103.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5hp091436570103.tab") 
> 
> try(system("convert tmp/1rdmh1436570103.ps tmp/1rdmh1436570103.png",intern=TRUE))
character(0)
> try(system("convert tmp/27vbg1436570103.ps tmp/27vbg1436570103.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.876   0.225   1.105