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(235.1
+ ,280.7
+ ,264.6
+ ,240.7
+ ,201.4
+ ,240.8
+ ,241.1
+ ,223.8
+ ,206.1
+ ,174.7
+ ,203.3
+ ,220.5
+ ,299.5
+ ,347.4
+ ,338.3
+ ,327.7
+ ,351.6
+ ,396.6
+ ,438.8
+ ,395.6
+ ,363.5
+ ,378.8
+ ,357
+ ,369
+ ,464.8
+ ,479.1
+ ,431.3
+ ,366.5
+ ,326.3
+ ,355.1
+ ,331.6
+ ,261.3
+ ,249
+ ,205.5
+ ,235.6
+ ,240.9
+ ,264.9
+ ,253.8
+ ,232.3
+ ,193.8
+ ,177
+ ,213.2
+ ,207.2
+ ,180.6
+ ,188.6
+ ,175.4
+ ,199
+ ,179.6
+ ,225.8
+ ,234
+ ,200.2
+ ,183.6
+ ,178.2
+ ,203.2
+ ,208.5
+ ,191.8
+ ,172.8
+ ,148
+ ,159.4
+ ,154.5
+ ,213.2
+ ,196.4
+ ,182.8
+ ,176.4
+ ,153.6
+ ,173.2
+ ,171
+ ,151.2
+ ,161.9
+ ,157.2
+ ,201.7
+ ,236.4
+ ,356.1
+ ,398.3
+ ,403.7
+ ,384.6
+ ,365.8
+ ,368.1
+ ,367.9
+ ,347
+ ,343.3
+ ,292.9
+ ,311.5
+ ,300.9
+ ,366.9
+ ,356.9
+ ,329.7
+ ,316.2
+ ,269
+ ,289.3
+ ,266.2
+ ,253.6
+ ,233.8
+ ,228.4
+ ,253.6
+ ,260.1
+ ,306.6
+ ,309.2
+ ,309.5
+ ,271
+ ,279.9
+ ,317.9
+ ,298.4
+ ,246.7
+ ,227.3
+ ,209.1
+ ,259.9
+ ,266
+ ,320.6
+ ,308.5
+ ,282.2
+ ,262.7
+ ,263.5
+ ,313.1
+ ,284.3
+ ,252.6
+ ,250.3
+ ,246.5
+ ,312.7
+ ,333.2
+ ,446.4
+ ,511.6
+ ,515.5
+ ,506.4
+ ,483.2
+ ,522.3
+ ,509.8
+ ,460.7
+ ,405.8
+ ,375
+ ,378.5
+ ,406.8
+ ,467.8
+ ,469.8
+ ,429.8
+ ,355.8
+ ,332.7
+ ,378
+ ,360.5
+ ,334.7
+ ,319.5
+ ,323.1
+ ,363.6
+ ,352.1
+ ,411.9
+ ,388.6
+ ,416.4
+ ,360.7
+ ,338
+ ,417.2
+ ,388.4
+ ,371.1
+ ,331.5
+ ,353.7
+ ,396.7
+ ,447
+ ,533.5
+ ,565.4
+ ,542.3
+ ,488.7
+ ,467.1
+ ,531.3
+ ,496.1
+ ,444
+ ,403.4
+ ,386.3
+ ,394.1
+ ,404.1
+ ,462.1
+ ,448.1
+ ,432.3
+ ,386.3
+ ,395.2
+ ,421.9
+ ,382.9
+ ,384.2
+ ,345.5
+ ,323.4
+ ,372.6
+ ,376
+ ,462.7
+ ,487
+ ,444.2
+ ,399.3
+ ,394.9
+ ,455.4
+ ,414
+ ,375.5
+ ,347
+ ,339.4
+ ,385.8
+ ,378.8
+ ,451.8
+ ,446.1
+ ,422.5
+ ,383.1
+ ,352.8
+ ,445.3
+ ,367.5
+ ,355.1
+ ,326.2
+ ,319.8
+ ,331.8
+ ,340.9
+ ,394.1
+ ,417.2
+ ,369.9
+ ,349.2
+ ,321.4
+ ,405.7
+ ,342.9
+ ,316.5
+ ,284.2
+ ,270.9
+ ,288.8
+ ,278.8
+ ,324.4
+ ,310.9
+ ,299
+ ,273
+ ,279.3
+ ,359.2
+ ,305
+ ,282.1
+ ,250.3
+ ,246.5
+ ,257.9
+ ,266.5
+ ,315.9
+ ,318.4
+ ,295.4
+ ,266.4
+ ,245.8
+ ,362.8
+ ,324.9
+ ,294.2
+ ,289.5
+ ,295.2
+ ,290.3
+ ,272
+ ,307.4
+ ,328.7
+ ,292.9
+ ,249.1
+ ,230.4
+ ,361.5
+ ,321.7
+ ,277.2
+ ,260.7
+ ,251
+ ,257.6
+ ,241.8
+ ,287.5
+ ,292.3
+ ,274.7
+ ,254.2
+ ,230
+ ,339
+ ,318.2
+ ,287
+ ,295.8
+ ,284
+ ,271
+ ,262.7
+ ,340.6
+ ,379.4
+ ,373.3
+ ,355.2
+ ,338.4
+ ,466.9
+ ,451
+ ,422
+ ,429.2
+ ,425.9
+ ,460.7
+ ,463.6
+ ,541.4
+ ,544.2
+ ,517.5
+ ,469.4
+ ,439.4
+ ,549
+ ,533
+ ,506.1
+ ,484
+ ,457
+ ,481.5
+ ,469.5
+ ,544.7
+ ,541.2
+ ,521.5
+ ,469.7
+ ,434.4
+ ,542.6
+ ,517.3
+ ,485.7
+ ,465.8
+ ,447
+ ,426.6
+ ,411.6
+ ,467.5
+ ,484.5
+ ,451.2
+ ,417.4
+ ,379.9
+ ,484.7
+ ,455
+ ,420.8
+ ,416.5
+ ,376.3
+ ,405.6
+ ,405.8
+ ,500.8
+ ,514
+ ,475.5
+ ,430.1
+ ,414.4
+ ,538
+ ,526
+ ,488.5
+ ,520.2
+ ,504.4
+ ,568.5
+ ,610.6
+ ,818
+ ,830.9
+ ,835.9
+ ,782
+ ,762.3
+ ,856.9
+ ,820.9
+ ,769.6
+ ,752.2
+ ,724.4
+ ,723.1
+ ,719.5
+ ,817.4
+ ,803.3
+ ,752.5
+ ,689
+ ,630.4
+ ,765.5
+ ,757.7
+ ,732.2
+ ,702.6
+ ,683.3
+ ,709.5
+ ,702.2
+ ,784.8
+ ,810.9
+ ,755.6
+ ,656.8
+ ,615.1
+ ,745.3
+ ,694.1
+ ,675.7
+ ,643.7
+ ,622.1
+ ,634.6
+ ,588
+ ,689.7
+ ,673.9
+ ,647.9
+ ,568.8
+ ,545.7
+ ,632.6
+ ,643.8
+ ,593.1
+ ,579.7
+ ,546
+ ,562.9
+ ,572.5)
> 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] 372
> (np <- floor(n / par1))
[1] 31
> 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] [,11] [,12]
 [1,] 235.1 299.5 464.8 264.9 225.8 213.2 356.1 366.9 306.6 320.6 446.4 467.8
 [2,] 280.7 347.4 479.1 253.8 234.0 196.4 398.3 356.9 309.2 308.5 511.6 469.8
 [3,] 264.6 338.3 431.3 232.3 200.2 182.8 403.7 329.7 309.5 282.2 515.5 429.8
 [4,] 240.7 327.7 366.5 193.8 183.6 176.4 384.6 316.2 271.0 262.7 506.4 355.8
 [5,] 201.4 351.6 326.3 177.0 178.2 153.6 365.8 269.0 279.9 263.5 483.2 332.7
 [6,] 240.8 396.6 355.1 213.2 203.2 173.2 368.1 289.3 317.9 313.1 522.3 378.0
 [7,] 241.1 438.8 331.6 207.2 208.5 171.0 367.9 266.2 298.4 284.3 509.8 360.5
 [8,] 223.8 395.6 261.3 180.6 191.8 151.2 347.0 253.6 246.7 252.6 460.7 334.7
 [9,] 206.1 363.5 249.0 188.6 172.8 161.9 343.3 233.8 227.3 250.3 405.8 319.5
[10,] 174.7 378.8 205.5 175.4 148.0 157.2 292.9 228.4 209.1 246.5 375.0 323.1
[11,] 203.3 357.0 235.6 199.0 159.4 201.7 311.5 253.6 259.9 312.7 378.5 363.6
[12,] 220.5 369.0 240.9 179.6 154.5 236.4 300.9 260.1 266.0 333.2 406.8 352.1
      [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
 [1,] 411.9 533.5 462.1 462.7 451.8 394.1 324.4 315.9 307.4 287.5 340.6 541.4
 [2,] 388.6 565.4 448.1 487.0 446.1 417.2 310.9 318.4 328.7 292.3 379.4 544.2
 [3,] 416.4 542.3 432.3 444.2 422.5 369.9 299.0 295.4 292.9 274.7 373.3 517.5
 [4,] 360.7 488.7 386.3 399.3 383.1 349.2 273.0 266.4 249.1 254.2 355.2 469.4
 [5,] 338.0 467.1 395.2 394.9 352.8 321.4 279.3 245.8 230.4 230.0 338.4 439.4
 [6,] 417.2 531.3 421.9 455.4 445.3 405.7 359.2 362.8 361.5 339.0 466.9 549.0
 [7,] 388.4 496.1 382.9 414.0 367.5 342.9 305.0 324.9 321.7 318.2 451.0 533.0
 [8,] 371.1 444.0 384.2 375.5 355.1 316.5 282.1 294.2 277.2 287.0 422.0 506.1
 [9,] 331.5 403.4 345.5 347.0 326.2 284.2 250.3 289.5 260.7 295.8 429.2 484.0
[10,] 353.7 386.3 323.4 339.4 319.8 270.9 246.5 295.2 251.0 284.0 425.9 457.0
[11,] 396.7 394.1 372.6 385.8 331.8 288.8 257.9 290.3 257.6 271.0 460.7 481.5
[12,] 447.0 404.1 376.0 378.8 340.9 278.8 266.5 272.0 241.8 262.7 463.6 469.5
      [,25] [,26] [,27] [,28] [,29] [,30] [,31]
 [1,] 544.7 467.5 500.8 818.0 817.4 784.8 689.7
 [2,] 541.2 484.5 514.0 830.9 803.3 810.9 673.9
 [3,] 521.5 451.2 475.5 835.9 752.5 755.6 647.9
 [4,] 469.7 417.4 430.1 782.0 689.0 656.8 568.8
 [5,] 434.4 379.9 414.4 762.3 630.4 615.1 545.7
 [6,] 542.6 484.7 538.0 856.9 765.5 745.3 632.6
 [7,] 517.3 455.0 526.0 820.9 757.7 694.1 643.8
 [8,] 485.7 420.8 488.5 769.6 732.2 675.7 593.1
 [9,] 465.8 416.5 520.2 752.2 702.6 643.7 579.7
[10,] 447.0 376.3 504.4 724.4 683.3 622.1 546.0
[11,] 426.6 405.6 568.5 723.1 709.5 634.6 562.9
[12,] 411.6 405.8 610.6 719.5 702.2 588.0 572.5
> 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] 227.7333 363.6500 328.9167 205.4500 188.3333 181.2500 353.3417 285.3083
 [9] 275.1250 285.8500 460.1667 373.9500 385.1000 471.3583 394.2083 407.0000
[17] 378.5750 336.6333 287.8417 297.5667 281.6667 283.0333 408.8500 499.3333
[25] 484.0083 430.4333 507.5833 782.9750 728.8000 685.5583 604.7167
> arr.sd
 [1] 29.19400 36.32671 93.54585 30.32471 27.37737 26.15720 36.20895 46.60518
 [9] 35.05093 30.74093 56.09698 53.10212 35.14430 64.21302 40.68476 46.60304
[17] 49.96968 51.52910 33.26998 30.47644 40.71404 28.48608 48.93488 37.51599
[25] 48.43902 37.46650 53.87227 48.45555 53.30777 72.54426 50.40404
> arr.range
 [1] 106.0 139.3 273.6  89.5  86.0  85.2 110.8 138.5 108.8  86.7 147.3 150.3
[13] 115.5 179.1 138.7 147.6 132.0 146.3 112.7 117.0 131.1 109.0 128.5 109.6
[25] 133.1 108.4 196.2 137.4 187.0 222.9 144.0
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   25.08186      0.04885  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       0.5961         0.5329  

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

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

Coefficients:
(Intercept)     arr.mean  
    81.9356       0.1377  

> postscript(file="/var/wessaorg/rcomp/tmp/1fhje1355248328.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/2sbi41355248328.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/3qzmt1355248328.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4ury91355248328.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5svii1355248328.tab") 
> 
> try(system("convert tmp/1fhje1355248328.ps tmp/1fhje1355248328.png",intern=TRUE))
character(0)
> try(system("convert tmp/2sbi41355248328.ps tmp/2sbi41355248328.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.775   0.310   2.118