R version 2.10.1 (2009-12-14)
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(1.1591,1.1203,1.0886,1.0701,1.0630,1.0377,1.0370,1.0605,1.0497,1.0706,1.0328,1.0110,1.0131,0.9834,0.9643,0.9449,0.9059,0.9505,0.9386,0.9045,0.8695,0.8525,0.8552,0.8983,0.9376,0.9205,0.9083,0.8925,0.8753,0.8530,0.8615,0.9014,0.9114,0.9050,0.8883,0.8912,0.8832,0.8707,0.8766,0.8860,0.9170,0.9561,0.9935,0.9781,0.9806,0.9812,1.0013,1.0194,1.0622,1.0785,1.0797,1.0862,1.1556,1.1674,1.1365,1.1155,1.1267,1.1714,1.1710,1.2298,1.2638,1.2640,1.2261,1.1989,1.2000,1.2146,1.2266,1.2191,1.2224,1.2507,1.2997,1.3406,1.3123,1.3013,1.3185,1.2943,1.2697,1.2155,1.2041,1.2295,1.2234,1.2022,1.1789,1.1861,1.2126,1.1940,1.2028,1.2273,1.2767,1.2661,1.2681,1.2810,1.2722,1.2617,1.2888,1.3205,1.2993,1.3080,1.3246,1.3513,1.3518,1.3421,1.3726,1.3626,1.3910,1.4233,1.4683,1.4559,1.4728,1.4759,1.5520,1.5754,1.5554,1.5562,1.5759,1.4955,1.4342,1.3266,1.2744,1.3511,1.3244,1.2797,1.3050,1.3199,1.3646,1.4014,1.4092,1.4266,1.4575,1.4821,1.4908,1.4579)
> 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] 132
> (np <- floor(n / par1))
[1] 11
> 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,] 1.1591 1.0131 0.9376 0.8832 1.0622 1.2638 1.3123 1.2126 1.2993 1.4728
 [2,] 1.1203 0.9834 0.9205 0.8707 1.0785 1.2640 1.3013 1.1940 1.3080 1.4759
 [3,] 1.0886 0.9643 0.9083 0.8766 1.0797 1.2261 1.3185 1.2028 1.3246 1.5520
 [4,] 1.0701 0.9449 0.8925 0.8860 1.0862 1.1989 1.2943 1.2273 1.3513 1.5754
 [5,] 1.0630 0.9059 0.8753 0.9170 1.1556 1.2000 1.2697 1.2767 1.3518 1.5554
 [6,] 1.0377 0.9505 0.8530 0.9561 1.1674 1.2146 1.2155 1.2661 1.3421 1.5562
 [7,] 1.0370 0.9386 0.8615 0.9935 1.1365 1.2266 1.2041 1.2681 1.3726 1.5759
 [8,] 1.0605 0.9045 0.9014 0.9781 1.1155 1.2191 1.2295 1.2810 1.3626 1.4955
 [9,] 1.0497 0.8695 0.9114 0.9806 1.1267 1.2224 1.2234 1.2722 1.3910 1.4342
[10,] 1.0706 0.8525 0.9050 0.9812 1.1714 1.2507 1.2022 1.2617 1.4233 1.3266
[11,] 1.0328 0.8552 0.8883 1.0013 1.1710 1.2997 1.1789 1.2888 1.4683 1.2744
[12,] 1.0110 0.8983 0.8912 1.0194 1.2298 1.3406 1.1861 1.3205 1.4559 1.3511
       [,11]
 [1,] 1.3244
 [2,] 1.2797
 [3,] 1.3050
 [4,] 1.3199
 [5,] 1.3646
 [6,] 1.4014
 [7,] 1.4092
 [8,] 1.4266
 [9,] 1.4575
[10,] 1.4821
[11,] 1.4908
[12,] 1.4579
> 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] 1.0667000 0.9233917 0.8955000 0.9453083 1.1317083 1.2438750 1.2446500
 [8] 1.2559833 1.3709000 1.4704500 1.3932583
> arr.sd
 [1] 0.04071299 0.05101099 0.02409968 0.05488506 0.04984987 0.04244237
 [7] 0.05139904 0.03839320 0.05455471 0.10388097 0.07309650
> arr.range
 [1] 0.1481 0.1606 0.0846 0.1487 0.1676 0.1417 0.1396 0.1265 0.1690 0.3015
[11] 0.2111
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.02777      0.06876  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -3.200          1.354  

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

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

Coefficients:
(Intercept)     arr.mean  
   -0.05489      0.18566  

> postscript(file="/var/www/rcomp/tmp/1jd3a1274970497.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/rcomp/tmp/2jd3a1274970497.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/3nejy1274970497.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4qehm1274970497.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/rcomp/tmp/5tfga1274970497.tab") 
> try(system("convert tmp/1jd3a1274970497.ps tmp/1jd3a1274970497.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jd3a1274970497.ps tmp/2jd3a1274970497.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.590   0.480   0.986