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(5745,4549,5074,3602,2732,2589,2148,2330,2752,3241,4517,6550,6778,6240,5570,3558,3299,2447,2380,2378,2947,3651,4816,6436,7090,4682,4198,3860,3056,2563,2568,2472,2821,4015,4686,5418,5649,4572,4695,3766,2900,2528,2549,2478,2828,4139,5390,5621,5291,5272,4677,3520,2842,2723,2581,2429,2606,3787,4630,5505,5577,4911,4701,3557,2921,2734,2636,2433,2640,3794,4745,5698,5909,5119,5200,3876,3104,2251,2386,2794,2967,3392,4741,5909,5901,4962,4751,3909,3130,2860,2568,2540,2894,4216,4530,5144,6206,5645,4601,3645,3140,2264,2557,2431,2747,4587,4512,5313,6011,5328,5014,3630,3102,2739,2877,2659,2957,3785,4785,5757,5458,5427,5018,3498,3204,2763,2589,2591,2805,3278,4615,5524,6167,5380,5377,3603,2774,2470,2407,2512,2451,3134,4210,4859,5022,4584,4267,3022,2777,2428,2389,2496,2820,3854,4748,5666,5293,4905,4920,3854,2659,2491,2455,2472,3030,3987,4453,5417)
> 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] 168
> (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,] 5745 6778 7090 5649 5291 5577 5909 5901 6206  6011  5458  6167  5022
 [2,] 4549 6240 4682 4572 5272 4911 5119 4962 5645  5328  5427  5380  4584
 [3,] 5074 5570 4198 4695 4677 4701 5200 4751 4601  5014  5018  5377  4267
 [4,] 3602 3558 3860 3766 3520 3557 3876 3909 3645  3630  3498  3603  3022
 [5,] 2732 3299 3056 2900 2842 2921 3104 3130 3140  3102  3204  2774  2777
 [6,] 2589 2447 2563 2528 2723 2734 2251 2860 2264  2739  2763  2470  2428
 [7,] 2148 2380 2568 2549 2581 2636 2386 2568 2557  2877  2589  2407  2389
 [8,] 2330 2378 2472 2478 2429 2433 2794 2540 2431  2659  2591  2512  2496
 [9,] 2752 2947 2821 2828 2606 2640 2967 2894 2747  2957  2805  2451  2820
[10,] 3241 3651 4015 4139 3787 3794 3392 4216 4587  3785  3278  3134  3854
[11,] 4517 4816 4686 5390 4630 4745 4741 4530 4512  4785  4615  4210  4748
[12,] 6550 6436 5418 5621 5505 5698 5909 5144 5313  5757  5524  4859  5666
      [,14]
 [1,]  5293
 [2,]  4905
 [3,]  4920
 [4,]  3854
 [5,]  2659
 [6,]  2491
 [7,]  2455
 [8,]  2472
 [9,]  3030
[10,]  3987
[11,]  4453
[12,]  5417
> 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] 3819.083 4208.333 3952.417 3926.250 3821.917 3862.250 3970.667 3950.417
 [9] 3970.667 4053.667 3897.500 3778.667 3672.750 3828.000
> arr.sd
 [1] 1445.572 1675.041 1390.159 1253.004 1194.558 1213.187 1344.783 1135.392
 [9] 1356.713 1251.600 1210.351 1368.253 1156.060 1165.992
> arr.range
 [1] 4402 4400 4618 3171 3076 3265 3658 3361 3942 3352 2935 3760 3277 2962
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
 -1284.4719       0.6606  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -7.964          1.829  

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

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

Coefficients:
(Intercept)     arr.mean  
  -2809.675        1.636  

> postscript(file="/var/www/html/rcomp/tmp/1dzng1292876718.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/www/html/rcomp/tmp/2dzng1292876718.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/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/3yim41292876718.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4213s1292876718.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/55jjy1292876718.tab") 
> 
> try(system("convert tmp/1dzng1292876718.ps tmp/1dzng1292876718.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dzng1292876718.ps tmp/2dzng1292876718.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.522   0.304   1.183