R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(228768.00
+ ,227916.00
+ ,227052.00
+ ,225264.00
+ ,242952.00
+ ,242016.00
+ ,228768.00
+ ,219960.00
+ ,220812.00
+ ,220812.00
+ ,221760.00
+ ,223464.00
+ ,226116.00
+ ,226116.00
+ ,224412.00
+ ,219960.00
+ ,242952.00
+ ,246456.00
+ ,241164.00
+ ,228768.00
+ ,234072.00
+ ,226116.00
+ ,229704.00
+ ,231420.00
+ ,233208.00
+ ,228768.00
+ ,229704.00
+ ,223464.00
+ ,242952.00
+ ,249108.00
+ ,243816.00
+ ,234072.00
+ ,244668.00
+ ,233208.00
+ ,243816.00
+ ,242952.00
+ ,245604.00
+ ,235860.00
+ ,246456.00
+ ,245604.00
+ ,261504.00
+ ,257916.00
+ ,243816.00
+ ,236712.00
+ ,246456.00
+ ,233208.00
+ ,242952.00
+ ,244668.00
+ ,248256.00
+ ,240312.00
+ ,244668.00
+ ,247320.00
+ ,257064.00
+ ,249108.00
+ ,238512.00
+ ,227052.00
+ ,237660.00
+ ,208500.00
+ ,222612.00
+ ,230556.00
+ ,238512.00
+ ,227052.00
+ ,227052.00
+ ,227052.00
+ ,233208.00
+ ,224412.00
+ ,212868.00
+ ,203208.00
+ ,210216.00
+ ,182856.00
+ ,199620.00
+ ,209364.00
+ ,211152.00
+ ,201408.00
+ ,202260.00
+ ,199620.00
+ ,208500.00
+ ,202260.00
+ ,189960.00
+ ,181068.00
+ ,196104.00
+ ,163452.00
+ ,184656.00
+ ,194316.00
+ ,194316.00
+ ,182856.00
+ ,172260.00
+ ,171408.00
+ ,181068.00
+ ,172260.00
+ ,155508.00
+ ,143964.00
+ ,156360.00
+ ,127212.00
+ ,153708.00
+ ,167808.00
+ ,172260.00
+ ,162516.00
+ ,150204.00
+ ,159012.00
+ ,162516.00
+ ,159864.00
+ ,133356.00
+ ,121056.00
+ ,129852.00
+ ,103356.00
+ ,130716.00
+ ,140460.00
+ ,148404.00
+ ,135156.00
+ ,122760.00
+ ,129852.00
+ ,133356.00
+ ,126348.00
+ ,99852.00
+ ,88308.00
+ ,98904.00
+ ,69756.00
+ ,101556.00
+ ,121056.00)
> par1 = '12'
> par1 <- '12'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P. (2012), Standard Deviation-Mean Plot (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_smp.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> 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,] 228768 226116 233208 245604 248256 238512 211152 194316 172260 148404
 [2,] 227916 226116 228768 235860 240312 227052 201408 182856 162516 135156
 [3,] 227052 224412 229704 246456 244668 227052 202260 172260 150204 122760
 [4,] 225264 219960 223464 245604 247320 227052 199620 171408 159012 129852
 [5,] 242952 242952 242952 261504 257064 233208 208500 181068 162516 133356
 [6,] 242016 246456 249108 257916 249108 224412 202260 172260 159864 126348
 [7,] 228768 241164 243816 243816 238512 212868 189960 155508 133356  99852
 [8,] 219960 228768 234072 236712 227052 203208 181068 143964 121056  88308
 [9,] 220812 234072 244668 246456 237660 210216 196104 156360 129852  98904
[10,] 220812 226116 233208 233208 208500 182856 163452 127212 103356  69756
[11,] 221760 229704 243816 242952 222612 199620 184656 153708 130716 101556
[12,] 223464 231420 242952 244668 230556 209364 194316 167808 140460 121056
> 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] 227462 231438 237478 245063 237635 216285 194563 164894 143764 114609
> arr.sd
 [1]  7708.304  8179.029  8022.587  8208.173 13516.894 16115.767 13253.237
 [8] 18472.033 20626.503 22827.850
> arr.range
 [1] 22992 26496 25644 28296 48564 55656 47700 67104 68904 78648
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
 36472.6547      -0.1132  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       26.332         -1.386  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.272e+05   -3.983e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1k3fh1438180282.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/wessaorg/rcomp/tmp/2irpu1438180282.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/3k7i11438180282.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4ccxm1438180282.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/wessaorg/rcomp/tmp/53dct1438180282.tab") 
> 
> try(system("convert tmp/1k3fh1438180282.ps tmp/1k3fh1438180282.png",intern=TRUE))
character(0)
> try(system("convert tmp/2irpu1438180282.ps tmp/2irpu1438180282.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.935   0.132   1.073