R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(1375.06,1334.38,1335.61,1307.24,1183.2,1187.79,1270.81,1238.67,1204.45,1178.5,1044.64,1076.59,1129.68,1144.93,1140.21,1100.29,1153.79,1114.2,1079.27,1014.05,903.69,912.55,867.81,854.54,911.17,899.26,895.87,837.61,846.62,890.19,935.96,988,992.55,989.53,1019.44,1038.73,1049.9,1080.64,1132.52,1143.37,1123.98,1133.07,1102.78,1132.76,1105.85,1088.93,1117.66,1118.07,1168.94,1199.21,1181.4,1199.63,1194.9,1164.42,1178.28,1202.25,1222.24,1224.27,1225.91,1191.96,1237.37,1262.07,1278.72,1276.65,1293.83,1302.18,1290,1253.12,1260.24,1287.15,1317.81,1363.38,1388.63,1416.42,1424.16,1444.65,1406.95,1463.65,1511.14,1514.49,1520.98,1454.62,1497.12,1539.66,1463.39,1479.23,1378.76,1354.87,1316.94,1370.47,1403.22,1341.25,1257.33,1281.47,1216.93,969.13,883.04)
> 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] 97
> (np <- floor(n / par1))
[1] 8
> 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]
 [1,] 1375.06 1129.68  911.17 1049.90 1168.94 1237.37 1388.63 1463.39
 [2,] 1334.38 1144.93  899.26 1080.64 1199.21 1262.07 1416.42 1479.23
 [3,] 1335.61 1140.21  895.87 1132.52 1181.40 1278.72 1424.16 1378.76
 [4,] 1307.24 1100.29  837.61 1143.37 1199.63 1276.65 1444.65 1354.87
 [5,] 1183.20 1153.79  846.62 1123.98 1194.90 1293.83 1406.95 1316.94
 [6,] 1187.79 1114.20  890.19 1133.07 1164.42 1302.18 1463.65 1370.47
 [7,] 1270.81 1079.27  935.96 1102.78 1178.28 1290.00 1511.14 1403.22
 [8,] 1238.67 1014.05  988.00 1132.76 1202.25 1253.12 1514.49 1341.25
 [9,] 1204.45  903.69  992.55 1105.85 1222.24 1260.24 1520.98 1257.33
[10,] 1178.50  912.55  989.53 1088.93 1224.27 1287.15 1454.62 1281.47
[11,] 1044.64  867.81 1019.44 1117.66 1225.91 1317.81 1497.12 1216.93
[12,] 1076.59  854.54 1038.73 1118.07 1191.96 1363.38 1539.66  969.13
> 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] 1228.0783 1034.5842  937.0775 1110.7942 1196.1175 1285.2100 1465.2058
[8] 1319.4158
> arr.sd
[1] 102.65712 117.51821  67.15912  26.91728  20.71220  33.24166  50.51644
[8] 134.72478
> arr.range
[1] 330.42 299.25 201.12  93.47  61.49 126.01 151.03 510.10
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   85.89530     -0.01396  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       6.6951        -0.3762  

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

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

Coefficients:
(Intercept)     arr.mean  
  129.03541      0.07734  

> postscript(file="/var/www/html/rcomp/tmp/1pitz1229012755.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/2bovj1229012755.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/390731229012755.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4e4vi1229012755.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5hk6o1229012755.tab") 
> 
> system("convert tmp/1pitz1229012755.ps tmp/1pitz1229012755.png")
> system("convert tmp/2bovj1229012755.ps tmp/2bovj1229012755.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.509   0.291   0.617