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(286.1,307,358.1,341.8,378.8,375.2,295.6,362.7,409.6,336.8,389.1,389.3,355.9,542,648.4,452,582.4,506.5,555.5,530.4,609.4,543.9,616.2,634.6,541.7,549.8,627.6,797.4,689.8,1576.6,1572.1,1626.4,1972.4,1509.6,1584.9,1880,1324,1777.7,2172.4,1780.3,2134.9,1838.4,1557,1755.2,1702,1577.5,1485.9,2179.1,1740.9,1724.5,2328.1,1774.1,2224.2,1536.3,1521.2,2051.8,2483.1,1929.8,1808.6,2584.9,1997.9,1639.9,2379.1,1715,2750.9,1865.4,1647.4,2180.4,2593,2057.2,2635.8,2315.4,1863.6,2038,2235.8,2222.1,2636.9,2076.8,1935.5,2086.3,2470.9,1854.6,2041.3,2170.8,1905.5,2130.2,2791.2,2539.7,2661.3,1764.9,2176.9,2458.5,2179,2242.5,2089.6,2661.6,2112,2367.3,2543,2603.9,3146.7,1789.2,2114.8,2236.3,2288.1,2173.2,1877.7,2807.4,2357.4,2107.7,2856.8,2510.8,2875,2229.7,2055.1,2545.4,2775.1,2252.2,2091.7,2433)
> 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] 120
> (np <- floor(n / par1))
[1] 10
> 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,] 286.1 355.9  541.7 1324.0 1740.9 1997.9 1863.6 1905.5 2112.0 2357.4
 [2,] 307.0 542.0  549.8 1777.7 1724.5 1639.9 2038.0 2130.2 2367.3 2107.7
 [3,] 358.1 648.4  627.6 2172.4 2328.1 2379.1 2235.8 2791.2 2543.0 2856.8
 [4,] 341.8 452.0  797.4 1780.3 1774.1 1715.0 2222.1 2539.7 2603.9 2510.8
 [5,] 378.8 582.4  689.8 2134.9 2224.2 2750.9 2636.9 2661.3 3146.7 2875.0
 [6,] 375.2 506.5 1576.6 1838.4 1536.3 1865.4 2076.8 1764.9 1789.2 2229.7
 [7,] 295.6 555.5 1572.1 1557.0 1521.2 1647.4 1935.5 2176.9 2114.8 2055.1
 [8,] 362.7 530.4 1626.4 1755.2 2051.8 2180.4 2086.3 2458.5 2236.3 2545.4
 [9,] 409.6 609.4 1972.4 1702.0 2483.1 2593.0 2470.9 2179.0 2288.1 2775.1
[10,] 336.8 543.9 1509.6 1577.5 1929.8 2057.2 1854.6 2242.5 2173.2 2252.2
[11,] 389.1 616.2 1584.9 1485.9 1808.6 2635.8 2041.3 2089.6 1877.7 2091.7
[12,] 389.3 634.6 1880.0 2179.1 2584.9 2315.4 2170.8 2661.6 2807.4 2433.0
> 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]  352.5083  548.1000 1244.0250 1773.7000 1975.6250 2148.1167 2136.0500
 [8] 2300.0750 2338.3000 2424.1583
> arr.sd
 [1]  39.74280  82.81614 551.69144 275.35388 357.87954 391.82953 233.50645
 [8] 320.98021 386.34193 294.58761
> arr.range
 [1]  123.5  292.5 1430.7  855.1 1063.7 1111.0  782.3 1026.3 1357.5  819.9
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    98.5077       0.1131  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -2.074          1.034  

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

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

Coefficients:
(Intercept)     arr.mean  
   244.3142       0.3723  

> postscript(file="/var/www/html/rcomp/tmp/1eguy1260368983.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/html/rcomp/tmp/260eu1260368983.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/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/3s4uu1260368983.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4vwxc1260368983.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5iitb1260368983.tab") 
> system("convert tmp/1eguy1260368983.ps tmp/1eguy1260368983.png")
> system("convert tmp/260eu1260368983.ps tmp/260eu1260368983.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.515   0.292   0.630