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(7992,6114,5965,8460,8323,6333,5675,10090,9035,6976,6459,10896,9978,7466,7199,10977,9412,6341,7784,11911,10079,7721,8197,12038,11963,8033,8618,13625,11734,8895,8727,13974,12583,9525,9662,15490,13839,10047,9788,14978,13045,9489,8741,13149,14106,9998,10034,15081,13266,9997,9027,14324,13149,11209,10332,15354,13800,11786,10550,16114,13255,11403,10269,14009,15847,12967,11328,15814,18626,13219,13818,18062,15722,12111,11702,15589,14852,13612,12380,15501,16322,12157,11124,14621,14035,11159,10944,15824,14378,11816,12233,17344,16812,12181,13275,18458,17375,14609,13323,18327,16053,15070,13806,18245,17461,14999,16022,20564,16372,15854,15115,18207,19488,16644,18631,21093,22212,19762,19403,21227,23176,20823,20647,21336,23458,22003,21647,26416,25226,24723,19945,24040,25034,24885,21168,23541,26019,24657,20599,24534,28717,26138,22968,26577,28660,30430,27356,25454,30194)
> 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] 149
> (np <- floor(n / par1))
[1] 37
> 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,] 7992  8323  9035  9978  9412 10079 11963 11734 12583 13839 13045 14106
[2,] 6114  6333  6976  7466  6341  7721  8033  8895  9525 10047  9489  9998
[3,] 5965  5675  6459  7199  7784  8197  8618  8727  9662  9788  8741 10034
[4,] 8460 10090 10896 10977 11911 12038 13625 13974 15490 14978 13149 15081
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
[1,] 13266 13149 13800 13255 15847 18626 15722 14852 16322 14035 14378 16812
[2,]  9997 11209 11786 11403 12967 13219 12111 13612 12157 11159 11816 12181
[3,]  9027 10332 10550 10269 11328 13818 11702 12380 11124 10944 12233 13275
[4,] 14324 15354 16114 14009 15814 18062 15589 15501 14621 15824 17344 18458
     [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36]
[1,] 17375 16053 17461 16372 19488 22212 23176 23458 25226 25034 26019 28717
[2,] 14609 15070 14999 15854 16644 19762 20823 22003 24723 24885 24657 26138
[3,] 13323 13806 16022 15115 18631 19403 20647 21647 19945 21168 20599 22968
[4,] 18327 18245 20564 18207 21093 21227 21336 26416 24040 23541 24534 26577
     [,37]
[1,] 28660
[2,] 30430
[3,] 27356
[4,] 25454
> 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]  7132.75  7605.25  8341.50  8905.00  8862.00  9508.75 10559.75 10832.50
 [9] 11815.00 12163.00 11106.00 12304.75 11653.50 12511.00 13062.50 12234.00
[17] 13989.00 15931.25 13781.00 14086.25 13556.00 12990.50 13942.75 15181.50
[25] 15908.50 15793.50 17261.50 16387.00 18964.00 20651.00 21495.50 23381.00
[33] 23483.50 23657.00 23952.25 26100.00 27975.00
> arr.sd
 [1] 1278.201 2002.801 2034.274 1864.195 2388.614 1969.689 2678.291 2507.905
 [9] 2826.951 2636.366 2319.589 2672.668 2541.274 2231.064 2435.684 1707.323
[17] 2229.215 2806.178 2171.596 1381.315 2356.325 2356.711 2530.102 2945.716
[25] 2336.185 1875.349 2422.229 1318.421 1852.971 1305.925 1157.833 2169.700
[33] 2408.550 1790.036 2334.584 2372.557 2100.385
> arr.range
 [1] 2495 4415 4437 3778 5570 4317 5592 5247 5965 5190 4408 5083 5297 5022 5564
[16] 3740 4519 5407 4020 3121 5198 4880 5528 6277 5004 4439 5565 3092 4449 2809
[31] 2529 4769 5281 3866 5420 5749 4976
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  2.316e+03   -9.675e-03  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      8.11118       -0.04749  

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

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

Coefficients:
(Intercept)     arr.mean  
  4.596e+03    5.302e-03  

> postscript(file="/var/yougetitorg/rcomp/tmp/179du1304955179.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/21guq1304955179.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/3jdxh1304955179.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/yougetitorg/rcomp/tmp/4i5p91304955179.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5mkjd1304955179.tab") 
> 
> try(system("convert tmp/179du1304955179.ps tmp/179du1304955179.png",intern=TRUE))
character(0)
> try(system("convert tmp/21guq1304955179.ps tmp/21guq1304955179.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.620   0.310   0.874