R version 2.10.1 (2009-12-14)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(126.304,125.511,125.495,130.133,126.257,110.323,98.417,105.749,120.665,124.075,127.245,146.731,144.979,148.210,144.670,142.970,142.524,146.142,146.522,148.128,148.798,150.181,152.388,155.694,160.662,155.520,158.262,154.338,158.196,160.371,154.856,150.636,145.899,141.242,140.834,141.119,139.104,134.437,129.425,123.155,119.273,120.472,121.523,121.983,123.658,124.794,124.827,120.382,117.395,115.790,114.283,117.271,117.448,118.764,120.550,123.554,125.412,124.182,119.828,115.361,114.226,115.214,115.864,114.276,113.469,114.883,114.172,111.225,112.149,115.618,118.002,121.382,120.663)
> 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] 73
> (np <- floor(n / par1))
[1] 18
> 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,] 126.304 126.257 120.665 144.979 142.524 148.798 160.662 158.196 145.899
[2,] 125.511 110.323 124.075 148.210 146.142 150.181 155.520 160.371 141.242
[3,] 125.495  98.417 127.245 144.670 146.522 152.388 158.262 154.856 140.834
[4,] 130.133 105.749 146.731 142.970 148.128 155.694 154.338 150.636 141.119
       [,10]   [,11]   [,12]   [,13]   [,14]   [,15]   [,16]   [,17]   [,18]
[1,] 139.104 119.273 123.658 117.395 117.448 125.412 114.226 113.469 112.149
[2,] 134.437 120.472 124.794 115.790 118.764 124.182 115.214 114.883 115.618
[3,] 129.425 121.523 124.827 114.283 120.550 119.828 115.864 114.172 118.002
[4,] 123.155 121.983 120.382 117.271 123.554 115.361 114.276 111.225 121.382
> 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] 126.8607 110.1865 129.6790 145.2072 145.8290 151.7653 157.1955 156.0147
 [9] 142.2735 131.5303 120.8127 123.4153 116.1848 120.0790 121.1958 114.8950
[17] 113.4372 116.7878
> arr.sd
 [1]  2.2139474 11.7826446 11.6812110  2.1880380  2.3654911  3.0076189
 [7]  2.8358803  4.2429714  2.4230334  6.8407547  1.2056645  2.0939216
[13]  1.4625463  2.6425273  4.5683513  0.7898194  1.5837833  3.8930645
> arr.range
 [1]  4.638 27.840 26.066  5.240  5.604  6.896  6.324  9.735  5.065 15.949
[11]  2.710  4.445  3.112  6.106 10.051  1.638  3.658  9.233
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    6.75348     -0.02293  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -1.5905         0.5458  

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

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

Coefficients:
(Intercept)     arr.mean  
   15.76753     -0.05527  

> postscript(file="/var/yougetitorg/rcomp/tmp/13khy1305017940.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/yougetitorg/rcomp/tmp/27o381305017940.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/yougetitorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/yougetitorg/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/yougetitorg/rcomp/tmp/3z3aa1305017940.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/yougetitorg/rcomp/tmp/45wgw1305017940.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/yougetitorg/rcomp/tmp/5gtkd1305017940.tab") 
> 
> try(system("convert tmp/13khy1305017940.ps tmp/13khy1305017940.png",intern=TRUE))
character(0)
> try(system("convert tmp/27o381305017940.ps tmp/27o381305017940.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.690   0.390   0.835