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

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> x <- c(2938,2909,3141,2427,3059,2918,2901,2823,2798,2892,2967,2397,3458,3024,3100,2904,3056,2771,2897,2772,2857,3020,2648,2364,3194,3013,2560,3074,2746,2846,3184,2354,3080,2963,2430,2296,2416,2647,2789,2685,2666,2882,2953,2127,2563,3061,2809,2861,2781,2555,3206,2570,2410,3195,2736,2743,2934,2668,2907,2866,2983,2878,3225,2515,3193,2663,2908,2896,2853,3028,3053,2455,3401,2969,3243,2849,3296,3121,3194,3023,2984,3525,3116,2383,3294,2882,2820,2583,2803,2767,2945,2716,2644,2956,2598,2171,2994,2645,2724,2550,2707,2679,2878,2307,2496,2637,2436,2426,2607,2533,2888,2520,2229,2804,2661,2547,2509,2465,2629,2706,2666,2432,2836,2888,2566,2802,2611,2683,2675,2434,2693,2619,2903,2550,2900,2456,2912,2883,2464,2655,2447,2592,2698,2274,2901,2397,3004,2614,2882,2671,2761,2806,2414,2673,2748,2112,2903,2633,2684,2861,2504,2708,2961,2535,2688,2699,2469,2585,2582,2480,2709,2441,2182,2585,2881,2422,2690,2659,2535,2613)
> 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] 180
> (np <- floor(n / par1))
[1] 15
> 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,] 2938 3458 3194 2416 2781 2983 3401 3294 2994  2607  2666  2903  2901
 [2,] 2909 3024 3013 2647 2555 2878 2969 2882 2645  2533  2432  2550  2397
 [3,] 3141 3100 2560 2789 3206 3225 3243 2820 2724  2888  2836  2900  3004
 [4,] 2427 2904 3074 2685 2570 2515 2849 2583 2550  2520  2888  2456  2614
 [5,] 3059 3056 2746 2666 2410 3193 3296 2803 2707  2229  2566  2912  2882
 [6,] 2918 2771 2846 2882 3195 2663 3121 2767 2679  2804  2802  2883  2671
 [7,] 2901 2897 3184 2953 2736 2908 3194 2945 2878  2661  2611  2464  2761
 [8,] 2823 2772 2354 2127 2743 2896 3023 2716 2307  2547  2683  2655  2806
 [9,] 2798 2857 3080 2563 2934 2853 2984 2644 2496  2509  2675  2447  2414
[10,] 2892 3020 2963 3061 2668 3028 3525 2956 2637  2465  2434  2592  2673
[11,] 2967 2648 2430 2809 2907 3053 3116 2598 2436  2629  2693  2698  2748
[12,] 2397 2364 2296 2861 2866 2455 2383 2171 2426  2706  2619  2274  2112
      [,14] [,15]
 [1,]  2903  2582
 [2,]  2633  2480
 [3,]  2684  2709
 [4,]  2861  2441
 [5,]  2504  2182
 [6,]  2708  2585
 [7,]  2961  2881
 [8,]  2535  2422
 [9,]  2688  2690
[10,]  2699  2659
[11,]  2469  2535
[12,]  2585  2613
> 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] 2847.500 2905.917 2811.667 2704.917 2797.583 2887.500 3092.000 2764.917
 [9] 2623.250 2591.500 2658.750 2644.500 2665.250 2685.833 2564.917
> arr.sd
 [1] 223.5582 268.1172 327.3776 253.1315 242.0944 241.4865 294.2621 269.3046
 [9] 195.1294 169.8622 141.7303 217.3370 251.7261 156.6768 175.4695
> arr.range
 [1]  744 1094  898  934  796  770 1142 1123  687  659  456  638  892  492  699
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  -461.2372       0.2508  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -19.812          3.185  

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

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

Coefficients:
(Intercept)     arr.mean  
  -1846.149        0.963  

> postscript(file="/var/www/html/rcomp/tmp/1ouxo1291550888.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/2ouxo1291550888.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/39uwc1291550888.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4dvvi1291550888.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5gwt61291550888.tab") 
> 
> try(system("convert tmp/1ouxo1291550888.ps tmp/1ouxo1291550888.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ouxo1291550888.ps tmp/2ouxo1291550888.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.512   0.288   1.473