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(350840
+ ,354950
+ ,342750
+ ,318610
+ ,303890
+ ,293480
+ ,286820
+ ,283650
+ ,276190
+ ,268670
+ ,275960
+ ,287040
+ ,291500
+ ,287540
+ ,272340
+ ,256570
+ ,246190
+ ,237340
+ ,235890
+ ,232790
+ ,226100
+ ,221110
+ ,221950
+ ,222990
+ ,232840
+ ,231380
+ ,221690
+ ,210190
+ ,202210
+ ,195210
+ ,194050
+ ,192360
+ ,187170
+ ,185930
+ ,188840
+ ,189350
+ ,194320
+ ,195850
+ ,188840
+ ,182380
+ ,177200
+ ,169140
+ ,171900
+ ,167320
+ ,164130
+ ,162550
+ ,166260
+ ,166010
+ ,177070
+ ,180800
+ ,179570
+ ,178130
+ ,178180
+ ,179430
+ ,179130
+ ,182220
+ ,183650
+ ,187110
+ ,197780
+ ,204000
+ ,221330
+ ,232500
+ ,237570
+ ,241100
+ ,244420
+ ,247240
+ ,254300
+ ,258970
+ ,262230
+ ,268880
+ ,277950
+ ,286630
+ ,299830
+ ,308090
+ ,311400
+ ,313520
+ ,310980
+ ,314910
+ ,310950
+ ,310720
+ ,310380
+ ,310570
+ ,314790
+ ,323400
+ ,335010
+ ,341630
+ ,340820
+ ,336280
+ ,325490
+ ,323750
+ ,317510
+ ,313890
+ ,308610
+ ,303720
+ ,303090
+ ,305140
+ ,304040
+ ,307100
+ ,304330
+ ,294710
+ ,286890
+ ,279050
+ ,271860
+ ,266710
+ ,259590
+ ,253830
+ ,250640
+ ,249140
+ ,250840
+ ,247590
+ ,237830
+ ,226380
+ ,217230
+ ,211420
+ ,207620
+ ,204310
+ ,197490
+ ,193580
+ ,192330
+ ,191970
+ ,196070
+ ,191940
+ ,185620
+ ,179410
+ ,173920
+ ,169190
+ ,166840
+ ,165170
+ ,161450
+ ,160830
+ ,163670
+ ,170830
+ ,182690
+ ,190940
+ ,197770
+ ,205090
+ ,210720
+ ,220210
+ ,229730
+ ,237070
+ ,241620
+ ,250370
+ ,258570
+ ,269860
+ ,283220
+ ,289610
+ ,281770
+ ,274700
+ ,267650
+ ,261380
+ ,260500
+ ,260730
+ ,254200
+ ,250450
+ ,253380
+ ,263740
+ ,276240
+ ,273820
+ ,265890
+ ,258400
+ ,253520
+ ,250710
+ ,252850
+ ,255260
+ ,251170
+ ,252500
+ ,257780
+ ,269900
+ ,291590
+ ,298870
+ ,295570
+ ,292100
+ ,290870
+ ,290580
+ ,297970
+ ,304010
+ ,304340
+ ,309850
+ ,322320
+ ,340170
+ ,369280
+ ,376690
+ ,379700
+ ,379520
+ ,377770
+ ,381560
+ ,394580
+ ,399320
+ ,400370
+ ,408200
+ ,419070
+ ,437730)
> 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] 192
> (np <- floor(n / par1))
[1] 16
> 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,] 350840 291500 232840 194320 177070 221330 299830 335010 304040 250840
 [2,] 354950 287540 231380 195850 180800 232500 308090 341630 307100 247590
 [3,] 342750 272340 221690 188840 179570 237570 311400 340820 304330 237830
 [4,] 318610 256570 210190 182380 178130 241100 313520 336280 294710 226380
 [5,] 303890 246190 202210 177200 178180 244420 310980 325490 286890 217230
 [6,] 293480 237340 195210 169140 179430 247240 314910 323750 279050 211420
 [7,] 286820 235890 194050 171900 179130 254300 310950 317510 271860 207620
 [8,] 283650 232790 192360 167320 182220 258970 310720 313890 266710 204310
 [9,] 276190 226100 187170 164130 183650 262230 310380 308610 259590 197490
[10,] 268670 221110 185930 162550 187110 268880 310570 303720 253830 193580
[11,] 275960 221950 188840 166260 197780 277950 314790 303090 250640 192330
[12,] 287040 222990 189350 166010 204000 286630 323400 305140 249140 191970
       [,11]  [,12]  [,13]  [,14]  [,15]  [,16]
 [1,] 196070 182690 283220 276240 291590 369280
 [2,] 191940 190940 289610 273820 298870 376690
 [3,] 185620 197770 281770 265890 295570 379700
 [4,] 179410 205090 274700 258400 292100 379520
 [5,] 173920 210720 267650 253520 290870 377770
 [6,] 169190 220210 261380 250710 290580 381560
 [7,] 166840 229730 260500 252850 297970 394580
 [8,] 165170 237070 260730 255260 304010 399320
 [9,] 161450 241620 254200 251170 304340 400370
[10,] 160830 250370 250450 252500 309850 408200
[11,] 163670 258570 253380 257780 322320 419070
[12,] 170830 269860 263740 269900 340170 437730
> 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] 303570.8 246025.8 202601.7 175491.7 183922.5 252760.0 311628.3 321245.0
 [9] 277324.2 214882.5 173745.0 224553.3 266777.5 259836.7 303186.7 393649.2
> arr.sd
 [1] 30775.046 25363.658 17263.678 12019.806  8493.849 19157.752  5385.777
 [8] 14654.632 21829.480 21306.033 11956.462 27863.062 12787.045  9198.339
[15] 14930.583 20345.287
> arr.range
 [1] 86280 70390 46910 33300 26930 65300 23570 38540 57960 58870 35240 87170
[13] 39160 25530 49590 68450
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  1.221e+04    1.896e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       6.1721         0.2799  

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

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

Coefficients:
(Intercept)     arr.mean  
  2.962e+04    8.251e-02  

> postscript(file="/var/wessaorg/rcomp/tmp/1ww471416833267.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/2x3na1416833267.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/36y9s1416833267.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4ybf61416833267.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5gs3j1416833267.tab") 
> 
> try(system("convert tmp/1ww471416833267.ps tmp/1ww471416833267.png",intern=TRUE))
character(0)
> try(system("convert tmp/2x3na1416833267.ps tmp/2x3na1416833267.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.938   0.152   1.096