R version 2.10.1 (2009-12-14)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(464,675,703,887,1139,1077,1318,1260,1120,963,996,960,530,883,894,1045,1199,1287,1565,1577,1076,918,1008,1063,544,635,804,980,1018,1064,1404,1286,1104,999,996,1015,615,722,832,977,1270,1437,1520,1708,1151,934,1159,1209,699,830,996,1124,1458,1270,1753,2258,1208,1241,1265,1828,809,997,1164,1205,1538,1513,1378,2083,1357,1536,1526,1376,779,1005,1193,1522,1539,1546,2116,2326,1596,1356,1553,1613,814,1150,1225,1691,1759,1754,2100,2062,2012,1897,1964,2186,966,1549,1538,1612,2078,2137,2907,2249,1883,1739,1828,1868,1138,1430,1809,1763,2200,2067,2503,2141,2103,1972,2181,2344,970,1199,1718,1683,2025,2051,2439,2353,2230,1852,2147,2286,1007,1665,1642,1518,1831,2207,2822,2393,2306,1785,2047,2171,1212,1335,2011,1860,1954,2152,2835,2224,2182,1992,2389,2724,891,1247,2017,2257,2255,2255,3057,3330,1896,2096,2374,2535,1041,1728,2201,2455,2204,2660,3670,2665,2639,2226,2586,2684,1185,1749,2459,2618,2585,3310,3923)
> 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] 187
> (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,]  464  530  544  615  699  809  779  814  966  1138   970  1007  1212
 [2,]  675  883  635  722  830  997 1005 1150 1549  1430  1199  1665  1335
 [3,]  703  894  804  832  996 1164 1193 1225 1538  1809  1718  1642  2011
 [4,]  887 1045  980  977 1124 1205 1522 1691 1612  1763  1683  1518  1860
 [5,] 1139 1199 1018 1270 1458 1538 1539 1759 2078  2200  2025  1831  1954
 [6,] 1077 1287 1064 1437 1270 1513 1546 1754 2137  2067  2051  2207  2152
 [7,] 1318 1565 1404 1520 1753 1378 2116 2100 2907  2503  2439  2822  2835
 [8,] 1260 1577 1286 1708 2258 2083 2326 2062 2249  2141  2353  2393  2224
 [9,] 1120 1076 1104 1151 1208 1357 1596 2012 1883  2103  2230  2306  2182
[10,]  963  918  999  934 1241 1536 1356 1897 1739  1972  1852  1785  1992
[11,]  996 1008  996 1159 1265 1526 1553 1964 1828  2181  2147  2047  2389
[12,]  960 1063 1015 1209 1828 1376 1613 2186 1868  2344  2286  2171  2724
      [,14] [,15]
 [1,]   891  1041
 [2,]  1247  1728
 [3,]  2017  2201
 [4,]  2257  2455
 [5,]  2255  2204
 [6,]  2255  2660
 [7,]  3057  3670
 [8,]  3330  2665
 [9,]  1896  2639
[10,]  2096  2226
[11,]  2374  2586
[12,]  2535  2684
> 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]  963.5000 1087.0833  987.4167 1127.8333 1327.5000 1373.5000 1512.0000
 [8] 1717.8333 1862.8333 1970.9167 1912.7500 1949.5000 2072.5000 2184.1667
[15] 2396.5833
> arr.sd
 [1] 250.3218 293.4907 240.9389 328.8848 440.7854 320.8748 423.0592 431.5797
 [9] 471.8522 384.9809 456.2623 476.8279 476.8382 668.6861 627.6030
> arr.range
 [1]  854 1047  860 1093 1559 1274 1547 1372 1941 1365 1469 1815 1623 2439 2629
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    35.5114       0.2356  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -0.6024         0.8974  

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

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

Coefficients:
(Intercept)     arr.mean  
   -38.4092       0.9598  

> postscript(file="/var/www/rcomp/tmp/1o0k41275505871.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/2o0k41275505871.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/3rjj91275505871.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4cjhf1275505871.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5qbx61275505871.tab") 
> 
> try(system("convert tmp/1o0k41275505871.ps tmp/1o0k41275505871.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o0k41275505871.ps tmp/2o0k41275505871.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.550   0.370   0.573