R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(14724,14404,14058,13427,19946,19631,14724,11462,11778,11778,12093,12760,13742,13427,11462,11778,20929,22893,17666,14724,15387,15707,17351,18964,19315,16022,16369,12093,24222,27800,19631,17004,18649,20613,23555,27164,27164,24853,23871,17982,27800,32391,28462,24222,24853,27164,30426,34355,31724,30111,30111,24853,32391,37297,33373,29129,30426,35653,37964,41222,38595,34355,33373,25520,30742,36315,30111,26502,30111,33689,35653,40906,38280,31724,32391,26186,31409,36000,30742,27164,30426,34355,33689,41542,40244,35017,35333,28462,32706,39262,34355,31409,36315,39262,36982,47431,44835,38946,37297,29764,34035,37964,33053,33053,38595,41542,39924,51355,48413,42871,40560,32391,35333,40560,36631,35653,40244,44168,39924,50057)
> par1 = '4'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 120
> (np <- floor(n / par1))
[1] 30
> 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] [,11] [,12]
[1,] 14724 19946 11778 13742 20929 15387 19315 24222 18649 27164 27800 24853
[2,] 14404 19631 11778 13427 22893 15707 16022 27800 20613 24853 32391 27164
[3,] 14058 14724 12093 11462 17666 17351 16369 19631 23555 23871 28462 30426
[4,] 13427 11462 12760 11778 14724 18964 12093 17004 27164 17982 24222 34355
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
[1,] 31724 32391 30426 38595 30742 30111 38280 31409 30426 40244 32706 36315
[2,] 30111 37297 35653 34355 36315 33689 31724 36000 34355 35017 39262 39262
[3,] 30111 33373 37964 33373 30111 35653 32391 30742 33689 35333 34355 36982
[4,] 24853 29129 41222 25520 26502 40906 26186 27164 41542 28462 31409 47431
     [,25] [,26] [,27] [,28] [,29] [,30]
[1,] 44835 34035 38595 48413 35333 40244
[2,] 38946 37964 41542 42871 40560 44168
[3,] 37297 33053 39924 40560 36631 39924
[4,] 29764 33053 51355 32391 35653 50057
> 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] 14153.25 16440.75 12102.25 12602.25 19053.00 16852.25 15949.75 22164.25
 [9] 22495.25 23467.50 28218.75 29199.50 29199.75 33047.50 36316.25 32960.75
[17] 30917.50 35089.75 32145.25 31328.75 35003.00 34764.00 34433.00 39997.50
[25] 37710.50 34526.25 42854.00 41058.75 37044.25 43598.25
> arr.sd
 [1]  555.3206 4090.6257  462.9603 1148.7385 3602.2672 1649.9288 2965.3791
 [8] 4797.2752 3708.4049 3908.8466 3347.4469 4127.9052 2995.9321 3364.0172
[15] 4542.9949 5453.5437 4054.2525 4505.4066 4945.8960 3629.3450 4685.2232
[22] 4835.0586 3437.6557 5113.7699 6207.5976 2338.1177 5794.0293 6652.0144
[29] 2407.9886 4718.4451
> arr.range
 [1]  1297  8484   982  2280  8169  3577  7222 10796  8515  9182  8169  9502
[13]  6871  8168 10796 13075  9813 10795 12094  8836 11116 11782  7853 11116
[25] 15071  4911 12760 16022  5227 10133
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   421.0951       0.1159  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -4.645          1.248  

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

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

Coefficients:
(Intercept)     arr.mean  
    803.765        0.275  

> postscript(file="/var/wessaorg/rcomp/tmp/1ap9u1313702310.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/2mpyc1313702310.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/3b5zg1313702310.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4gsk71313702310.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5vmuk1313702310.tab") 
> 
> try(system("convert tmp/1ap9u1313702310.ps tmp/1ap9u1313702310.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mpyc1313702310.ps tmp/2mpyc1313702310.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.643   0.135   0.775