R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(571000
+ ,584000
+ ,599000
+ ,582000
+ ,530000
+ ,528000
+ ,536000
+ ,546000
+ ,559000
+ ,562000
+ ,541000
+ ,539000
+ ,548000
+ ,563000
+ ,581000
+ ,572000
+ ,519000
+ ,521000
+ ,531000
+ ,540000
+ ,548000
+ ,556000
+ ,551000
+ ,549000
+ ,564000
+ ,586000
+ ,604000
+ ,601000
+ ,545000
+ ,537000
+ ,552000
+ ,563000
+ ,575000
+ ,580000
+ ,575000
+ ,558000
+ ,564000
+ ,581000
+ ,597000
+ ,587000
+ ,536000
+ ,524000
+ ,537000
+ ,536000
+ ,533000
+ ,528000
+ ,516000
+ ,502000
+ ,506000
+ ,518000
+ ,534000
+ ,528000
+ ,478000
+ ,469000
+ ,490000
+ ,493000
+ ,508000
+ ,517000
+ ,514000
+ ,510000
+ ,527000
+ ,542000
+ ,565000
+ ,555000
+ ,499000
+ ,511000
+ ,526000
+ ,532000
+ ,549000
+ ,561000
+ ,557000
+ ,566000
+ ,588000
+ ,620000
+ ,626000
+ ,620000
+ ,573000
+ ,573000
+ ,574000
+ ,580000
+ ,590000
+ ,593000
+ ,597000
+ ,595000
+ ,612000
+ ,628000
+ ,629000
+ ,621000
+ ,569000
+ ,567000
+ ,573000
+ ,584000
+ ,589000
+ ,591000
+ ,595000
+ ,594000
+ ,611000
+ ,613000
+ ,611000
+ ,594000
+ ,543000
+ ,537000
+ ,544000
+ ,555000
+ ,561000
+ ,562000
+ ,555000
+ ,547000
+ ,565000
+ ,578000
+ ,580000
+ ,569000
+ ,507000
+ ,501000
+ ,509000
+ ,510000
+ ,517000
+ ,519000
+ ,512000
+ ,509000
+ ,519000
+ ,523000
+ ,525000
+ ,517000
+ ,456000
+ ,455000
+ ,461000
+ ,470000
+ ,475000
+ ,476000
+ ,471000
+ ,471000
+ ,503000
+ ,513000
+ ,510000
+ ,484000
+ ,431000
+ ,436000
+ ,443000
+ ,448000
+ ,460000
+ ,467000
+ ,460000
+ ,464000
+ ,485000
+ ,501000
+ ,521000
+ ,488000
+ ,439000
+ ,442000
+ ,457000
+ ,462000
+ ,481000
+ ,493000)
> 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] 154
> (np <- floor(n / par1))
[1] 12
> 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,] 571000 548000 564000 564000 506000 527000 588000 612000 611000 565000
 [2,] 584000 563000 586000 581000 518000 542000 620000 628000 613000 578000
 [3,] 599000 581000 604000 597000 534000 565000 626000 629000 611000 580000
 [4,] 582000 572000 601000 587000 528000 555000 620000 621000 594000 569000
 [5,] 530000 519000 545000 536000 478000 499000 573000 569000 543000 507000
 [6,] 528000 521000 537000 524000 469000 511000 573000 567000 537000 501000
 [7,] 536000 531000 552000 537000 490000 526000 574000 573000 544000 509000
 [8,] 546000 540000 563000 536000 493000 532000 580000 584000 555000 510000
 [9,] 559000 548000 575000 533000 508000 549000 590000 589000 561000 517000
[10,] 562000 556000 580000 528000 517000 561000 593000 591000 562000 519000
[11,] 541000 551000 575000 516000 514000 557000 597000 595000 555000 512000
[12,] 539000 549000 558000 502000 510000 566000 595000 594000 547000 509000
       [,11]  [,12]
 [1,] 519000 503000
 [2,] 523000 513000
 [3,] 525000 510000
 [4,] 517000 484000
 [5,] 456000 431000
 [6,] 455000 436000
 [7,] 461000 443000
 [8,] 470000 448000
 [9,] 475000 460000
[10,] 476000 467000
[11,] 471000 460000
[12,] 471000 464000
> 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] 556416.7 548250.0 570000.0 545083.3 505416.7 540833.3 594083.3 596000.0
 [9] 569416.7 531333.3 484916.7 468250.0
> arr.sd
 [1] 23453.86 18796.16 20867.55 30022.59 19519.03 21916.51 18870.17 21983.46
 [9] 29234.03 31326.24 27533.31 28336.05
> arr.range
 [1] 71000 62000 67000 95000 65000 67000 53000 62000 76000 79000 70000 82000
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  4.832e+04   -4.424e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      22.8290        -0.9656  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.323e+05   -1.135e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1rgke1353432906.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/2o0u21353432906.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/3uiyj1353432906.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4sqjk1353432907.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5p0ut1353432907.tab") 
> 
> try(system("convert tmp/1rgke1353432906.ps tmp/1rgke1353432906.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o0u21353432906.ps tmp/2o0u21353432906.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.518   0.693   4.200