R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(112,118,129,99,116,168,118,129,205,147,150,267,126,129,124,97,102,127,222,214,118,141,154,226,89,77,82,97,127,121,117,117,106,112,134,169,75,108,115,85,101,108,109,124,105,95,135,164,88,85,112,87,91,87,87,142,95,108,139,159,61,82,124,93,108,75,87,103,90,108,123,129,57,65,67,71,76,67,110,118,99,85,107,141,58,65,70,86,93,74,87,73,101,100,96,157,63,115,70,66,67,83,79,77,102,116,100,135,71,60,89,74,73,91,86,74,87,87,109,137,43,69,73,77,69,76,78,70,83,65,110,132,54,55,66,65,60,65,96,55,71,63,74,106,34,47,56,53,53,55,67,52,46,51,58,91,33,40,46,45,41,55,57,54,46,52,48,77,30,35,42,48,44,45,46)
> par1 = '12'
> #'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] 175
> (np <- floor(n / par1))
[1] 14
> 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] [,13]
 [1,]  112  126   89   75   88   61   57   58   63    71    43    54    34
 [2,]  118  129   77  108   85   82   65   65  115    60    69    55    47
 [3,]  129  124   82  115  112  124   67   70   70    89    73    66    56
 [4,]   99   97   97   85   87   93   71   86   66    74    77    65    53
 [5,]  116  102  127  101   91  108   76   93   67    73    69    60    53
 [6,]  168  127  121  108   87   75   67   74   83    91    76    65    55
 [7,]  118  222  117  109   87   87  110   87   79    86    78    96    67
 [8,]  129  214  117  124  142  103  118   73   77    74    70    55    52
 [9,]  205  118  106  105   95   90   99  101  102    87    83    71    46
[10,]  147  141  112   95  108  108   85  100  116    87    65    63    51
[11,]  150  154  134  135  139  123  107   96  100   109   110    74    58
[12,]  267  226  169  164  159  129  141  157  135   137   132   106    91
      [,14]
 [1,]    33
 [2,]    40
 [3,]    46
 [4,]    45
 [5,]    41
 [6,]    55
 [7,]    57
 [8,]    54
 [9,]    46
[10,]    52
[11,]    48
[12,]    77
> 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] 146.50000 148.33333 112.33333 110.33333 106.66667  98.58333  88.58333
 [8]  88.33333  89.41667  86.50000  78.75000  69.16667  55.25000  49.50000
> arr.sd
 [1] 47.70268 46.19983 25.23105 23.25876 25.97668 20.99116 26.08538 25.83280
 [9] 23.62379 20.27313 22.57966 16.24155 13.71214 11.08234
> arr.range
 [1] 168 129  92  89  74  68  84  99  72  77  89  52  57  44
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    -6.7662       0.3339  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -2.140          1.172  

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

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

Coefficients:
(Intercept)     arr.mean  
    -5.1104       0.9528  

> postscript(file="/var/www/html/rcomp/tmp/1anw71274792540.ps",horizontal=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/www/html/rcomp/tmp/2leds1274792540.ps",horizontal=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/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/www/html/rcomp/tmp/3pxcg1274792540.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4sxsl1274792540.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/www/html/rcomp/tmp/5vg8r1274792540.tab") 
> 
> try(system("convert tmp/1anw71274792540.ps tmp/1anw71274792540.png",intern=TRUE))
character(0)
> try(system("convert tmp/2leds1274792540.ps tmp/2leds1274792540.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.502   0.281   0.839