R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(299.81,299.01,296.82,296.67,296.95,296.80,296.80,295.93,293.77,291.02,288.61,284.55,284.55,278.14,273.28,270.14,268.36,267.15,267.15,265.47,261.75,256.51,252.98,251.17,251.17,244.27,240.54,238.92,237.47,235.91,235.91,231.41,224.94,222.19,219.06,217.83,217.83,216.89,213.84,212.90,213.98,215.31,215.31,214.09,213.71,211.54,209.40,207.33,207.33,202.75,200.26,198.99,198.82,198.43,198.43,195.68,195.45,193.65,191.38,189.71,189.71,185.49,183.01,182.38,181.60,182.13,182.13,180.81,180.25,179.84,178.50,178.11,178.11,178.10,177.52,177.34,175.53,176.01,175.94,175.47,175.48,173.76,173.74,173.65,172.00,171.50,170.41,171.50,171.43,170.69,170.40,169.90,170.21,170.55,169.98,169.34)
> 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] 96
> (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,] 299.81 284.55 251.17 217.83 207.33 189.71 178.11 172.00
 [2,] 299.01 278.14 244.27 216.89 202.75 185.49 178.10 171.50
 [3,] 296.82 273.28 240.54 213.84 200.26 183.01 177.52 170.41
 [4,] 296.67 270.14 238.92 212.90 198.99 182.38 177.34 171.50
 [5,] 296.95 268.36 237.47 213.98 198.82 181.60 175.53 171.43
 [6,] 296.80 267.15 235.91 215.31 198.43 182.13 176.01 170.69
 [7,] 296.80 267.15 235.91 215.31 198.43 182.13 175.94 170.40
 [8,] 295.93 265.47 231.41 214.09 195.68 180.81 175.47 169.90
 [9,] 293.77 261.75 224.94 213.71 195.45 180.25 175.48 170.21
[10,] 291.02 256.51 222.19 211.54 193.65 179.84 173.76 170.55
[11,] 288.61 252.98 219.06 209.40 191.38 178.50 173.74 169.98
[12,] 284.55 251.17 217.83 207.33 189.71 178.11 173.65 169.34
> 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] 294.7283 266.3875 233.3017 213.5108 197.5733 181.9967 175.8875 170.6592
> arr.sd
[1]  4.5021931  9.8437134 10.4171413  2.9635742  4.8421696  3.1552073  1.6303883
[8]  0.7935932
> arr.range
[1] 15.26 33.38 33.34 10.50 17.62 11.60  4.46  2.66
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -5.86561      0.04906  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -15.56           3.14  

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

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

Coefficients:
(Intercept)     arr.mean  
   -19.2851       0.1633  

> postscript(file="/var/wessaorg/rcomp/tmp/1hp6l1426169218.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/20bw91426169218.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/3ay581426169218.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4i4su1426169218.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5x0qf1426169218.tab") 
> 
> try(system("convert tmp/1hp6l1426169218.ps tmp/1hp6l1426169218.png",intern=TRUE))
character(0)
> try(system("convert tmp/20bw91426169218.ps tmp/20bw91426169218.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.872   0.112   0.991