R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(193.230,199.068,195.076,191.563,191.067,186.665,185.508,184.371,183.046,175.714,175.768,171.029,170.465,170.102,156.389,124.291,99.360,86.675,85.056,128.236,164.257,162.401,152.779,156.005,153.387,153.190,148.840,144.211,145.953,145.542,150.271,147.489,143.824,134.754,131.736,126.304,125.511,125.495,130.133,126.257,110.323,98.417,105.749,120.665,124.075,127.245,146.731,144.979,148.210,144.670,142.970,142.524,146.142,146.522,148.128,148.798,150.181,152.388,155.694,160.662,155.520,158.262,154.338,158.196,160.371,154.856,150.636,145.899,141.242,140.834,141.119,139.104,134.437,129.425,123.155,119.273,120.472,121.523,121.983,123.658,124.794,124.827,120.382,117.395,115.790,114.283,117.271,117.448,118.764,120.550,123.554,125.412,124.182,119.828,115.361,114.226,115.214,115.864,114.276,113.469)
> 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] 100
> (np <- floor(n / par1))
[1] 25
> 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]
[1,] 193.230 191.067 183.046 170.465  99.360 164.257 153.387 145.953 143.824
[2,] 199.068 186.665 175.714 170.102  86.675 162.401 153.190 145.542 134.754
[3,] 195.076 185.508 175.768 156.389  85.056 152.779 148.840 150.271 131.736
[4,] 191.563 184.371 171.029 124.291 128.236 156.005 144.211 147.489 126.304
       [,10]   [,11]   [,12]   [,13]   [,14]   [,15]   [,16]   [,17]   [,18]
[1,] 125.511 110.323 124.075 148.210 146.142 150.181 155.520 160.371 141.242
[2,] 125.495  98.417 127.245 144.670 146.522 152.388 158.262 154.856 140.834
[3,] 130.133 105.749 146.731 142.970 148.128 155.694 154.338 150.636 141.119
[4,] 126.257 120.665 144.979 142.524 148.798 160.662 158.196 145.899 139.104
       [,19]   [,20]   [,21]   [,22]   [,23]   [,24]   [,25]
[1,] 134.437 120.472 124.794 115.790 118.764 124.182 115.214
[2,] 129.425 121.523 124.827 114.283 120.550 119.828 115.864
[3,] 123.155 121.983 120.382 117.271 123.554 115.361 114.276
[4,] 119.273 123.658 117.395 117.448 125.412 114.226 113.469
> 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] 194.73425 186.90275 176.38925 155.31175  99.83175 158.86050 149.90700
 [8] 147.31375 134.15450 126.84900 108.78850 135.75750 144.59350 147.39750
[15] 154.73125 156.57900 152.94050 140.57475 126.57250 121.90900 121.84950
[22] 116.19800 122.07000 118.39925 114.70575
> arr.sd
 [1]  3.225822  2.929880  4.962745 21.693470 19.987053  5.378844  4.338640
 [8]  2.142178  7.333442  2.218008  9.313297 11.752974  2.582215  1.269883
[15]  4.556910  1.965599  6.158325  0.995280  6.706940  1.326454  3.630047
[22]  1.477331  2.978325  4.550769  1.051047
> arr.range
 [1]  7.505  6.696 12.017 46.174 43.180 11.478  9.176  4.729 17.520  4.638
[11] 22.248 22.656  5.686  2.656 10.481  3.924 14.472  2.138 15.164  3.186
[21]  7.432  3.165  6.648  9.956  2.395
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   10.45661     -0.03612  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       2.9414        -0.3285  

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

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

Coefficients:
(Intercept)     arr.mean  
   22.60687     -0.07681  

> postscript(file="/var/www/html/freestat/rcomp/tmp/1u2b21305849807.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/freestat/rcomp/tmp/2919f1305849807.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/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/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/freestat/rcomp/tmp/33w4z1305849807.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/4kszn1305849807.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/freestat/rcomp/tmp/5uovk1305849807.tab") 
> 
> try(system("convert tmp/1u2b21305849807.ps tmp/1u2b21305849807.png",intern=TRUE))
character(0)
> try(system("convert tmp/2919f1305849807.ps tmp/2919f1305849807.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.766   0.078   0.842