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(90604,97527,111940,100280,100009,95558,98533,92694,97920,110933,110855,111716,96348,105425,114874,104199,101166,99010,101607,97492,106088,113536,112475,115491,97733,102591,114783,100397,97772,96128,91261,90686,97792,108848,109989,109453,93945,98750,119043,104776,103262,106735,101600,99358,105240,114079,121637,111747,99496,104992,124255,108258,106940,104939,105896,107287,110783,122139,125823,120480,103296,117121,129924,118589,118062,113597,117161,112893,119657,136562,140446,138744,120324,118113,130257,125510,117986,118316,122075,117573,122566,135934,138394,137999,118780,117907,142932,132200,125666,127958,127718,124368,135241,144734,142320,141481,120471,123422,145829,134572,132156,140265,137771,134035,144016,151905,155791,148440,129862,134264,151952,143191,137242,136993,134431,132523,133486,140120,137521,112193,94256,99047,109761,102160,104792,104341,112430,113034,114197,127876,135199,123663,112578,117104,139703,114961,134222,128390,134197,135963,135936,146803,143231,131510)
> 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] 144
> (np <- floor(n / par1))
[1] 12
> 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,]  90604  96348  97733  93945  99496 103296 120324 118780 120471 129862
 [2,]  97527 105425 102591  98750 104992 117121 118113 117907 123422 134264
 [3,] 111940 114874 114783 119043 124255 129924 130257 142932 145829 151952
 [4,] 100280 104199 100397 104776 108258 118589 125510 132200 134572 143191
 [5,] 100009 101166  97772 103262 106940 118062 117986 125666 132156 137242
 [6,]  95558  99010  96128 106735 104939 113597 118316 127958 140265 136993
 [7,]  98533 101607  91261 101600 105896 117161 122075 127718 137771 134431
 [8,]  92694  97492  90686  99358 107287 112893 117573 124368 134035 132523
 [9,]  97920 106088  97792 105240 110783 119657 122566 135241 144016 133486
[10,] 110933 113536 108848 114079 122139 136562 135934 144734 151905 140120
[11,] 110855 112475 109989 121637 125823 140446 138394 142320 155791 137521
[12,] 111716 115491 109453 111747 120480 138744 137999 141481 148440 112193
       [,11]  [,12]
 [1,]  94256 112578
 [2,]  99047 117104
 [3,] 109761 139703
 [4,] 102160 114961
 [5,] 104792 134222
 [6,] 104341 128390
 [7,] 112430 134197
 [8,] 113034 135963
 [9,] 114197 135936
[10,] 127876 146803
[11,] 135199 143231
[12,] 123663 131510
> 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] 101547.4 105642.6 101452.8 106681.0 111774.0 122171.0 125420.6 131775.4
 [9] 139056.1 135314.8 111729.7 131216.5
> arr.sd
 [1]  7760.754  6919.447  7749.488  8414.506  8899.619 11592.896  8126.876
 [8]  9507.965 10827.387  9296.594 12160.123 11040.834
> arr.range
 [1] 21336 19143 24097 27692 26327 37150 20821 26827 35320 39759 40943 34225
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  1.745e+03    6.416e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -1.159          0.881  

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

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

Coefficients:
(Intercept)     arr.mean  
 -5564.8533       0.2953  

> postscript(file="/var/wessaorg/rcomp/tmp/113801324419379.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/2txq51324419379.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/3ur1k1324419379.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/47an01324419379.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/50b341324419379.tab") 
> 
> try(system("convert tmp/113801324419379.ps tmp/113801324419379.png",intern=TRUE))
character(0)
> try(system("convert tmp/2txq51324419379.ps tmp/2txq51324419379.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.741   0.181   0.930