R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(52.61
+ ,65.04
+ ,67.54
+ ,63.58
+ ,57.35
+ ,54.93
+ ,54.30
+ ,58.89
+ ,65.95
+ ,82.65
+ ,100.08
+ ,100.68
+ ,97.53
+ ,92.29
+ ,85.08
+ ,91.61
+ ,93.61
+ ,90.40
+ ,99.31
+ ,107.71
+ ,106.18
+ ,98.80
+ ,99.58
+ ,98.85
+ ,92.69
+ ,91.82
+ ,92.63
+ ,98.41
+ ,94.56
+ ,85.78
+ ,84.59
+ ,83.49
+ ,84.68
+ ,80.12
+ ,84.37
+ ,85.94
+ ,87.07
+ ,84.52
+ ,83.13
+ ,75.95
+ ,70.12
+ ,78.10
+ ,83.06
+ ,87.92
+ ,90.21
+ ,89.95
+ ,97.08
+ ,102.08
+ ,100.64
+ ,97.73
+ ,97.61
+ ,100.32
+ ,102.04
+ ,107.80
+ ,111.51
+ ,110.18
+ ,110.08
+ ,117.40
+ ,119.82
+ ,118.79
+ ,113.18
+ ,122.76
+ ,120.43
+ ,129.16
+ ,132.48
+ ,135.68
+ ,141.49
+ ,122.40
+ ,137.06
+ ,144.84
+ ,154.64
+ ,148.04
+ ,152.76
+ ,172.00
+ ,169.03
+ ,179.68
+ ,190.38
+ ,233.23
+ ,231.45
+ ,244.87
+ ,299.12
+ ,385.01
+ ,381.48
+ ,321.56
+ ,317.27
+ ,323.09
+ ,392.72
+ ,372.37
+ ,386.52
+ ,412.83
+ ,404.91
+ ,406.73
+ ,392.41
+ ,363.31
+ ,357.95
+ ,375.10
+ ,369.74
+ ,386.14
+ ,353.40
+ ,346.87
+ ,362.53
+ ,349.87
+ ,347.03
+ ,332.94
+ ,327.48
+ ,327.92
+ ,308.91
+ ,285.71
+ ,318.81
+ ,284.76
+ ,301.04
+ ,315.16
+ ,388.34
+ ,383.37
+ ,416.77
+ ,423.24
+ ,429.90
+ ,486.07
+ ,394.41
+ ,410.93
+ ,430.88
+ ,447.29
+ ,431.65
+ ,456.53
+ ,452.93
+ ,440.90
+ ,416.46
+ ,451.49
+ ,432.00
+ ,436.19
+ ,428.55
+ ,421.40
+ ,425.18
+ ,437.24
+ ,431.92
+ ,412.65
+ ,419.37
+ ,436.40
+ ,421.37
+ ,423.66
+ ,402.45
+ ,402.82
+ ,400.46
+ ,425.73
+ ,417.93
+ ,403.43
+ ,404.96
+ ,393.64
+ ,399.98
+ ,375.93
+ ,366.57
+ ,353.90
+ ,347.51
+ ,364.10
+ ,328.64
+ ,348.01
+ ,329.63
+ ,350.96
+ ,336.16
+ ,332.15
+ ,349.46
+ ,383.64
+ ,369.82
+ ,345.50
+ ,337.80
+ ,334.76
+ ,338.02
+ ,346.74
+ ,371.84
+ ,375.90
+ ,373.31
+ ,391.91
+ ,374.28
+ ,384.69
+ ,372.16
+ ,371.97
+ ,351.76
+ ,352.89
+ ,330.48
+ ,347.70
+ ,345.58
+ ,360.76
+ ,364.40
+ ,374.62
+ ,369.07
+ ,341.80
+ ,337.87
+ ,336.58
+ ,332.66
+ ,335.74
+ ,321.64
+ ,329.38
+ ,321.84
+ ,324.56
+ ,330.90
+ ,310.91
+ ,318.07
+ ,312.36
+ ,315.19
+ ,332.89
+ ,310.67
+ ,321.26
+ ,316.15
+ ,283.87
+ ,280.65
+ ,280.21
+ ,265.93
+ ,267.80
+ ,278.03
+ ,291.86
+ ,262.61
+ ,264.80
+ ,265.67
+ ,251.05
+ ,256.11
+ ,279.75
+ ,282.52
+ ,288.89
+ ,308.46
+ ,292.89
+ ,280.79
+ ,273.61
+ ,276.67
+ ,277.92
+ ,250.28
+ ,264.70
+ ,268.95
+ ,261.69
+ ,257.99
+ ,251.28
+ ,243.14
+ ,246.81
+ ,224.50
+ ,241.25
+ ,254.97
+ ,261.39
+ ,266.67
+ ,264.28
+ ,270.45
+ ,274.97
+ ,281.13
+ ,300.65
+ ,321.12
+ ,354.79
+ ,318.97
+ ,298.71
+ ,318.85
+ ,327.89
+ ,348.19
+ ,335.18
+ ,332.98
+ ,331.04
+ ,317.52
+ ,325.31
+ ,317.59
+ ,313.37
+ ,313.00
+ ,314.77
+ ,298.37
+ ,311.10
+ ,308.79
+ ,297.30
+ ,293.58
+ ,291.35
+ ,291.51
+ ,289.94
+ ,287.07
+ ,280.74
+ ,294.95
+ ,288.98
+ ,285.63
+ ,294.55
+ ,290.67
+ ,314.78
+ ,306.50
+ ,304.48
+ ,308.65
+ ,307.01
+ ,298.59
+ ,293.51
+ ,294.90
+ ,296.14
+ ,294.25
+ ,291.75
+ ,290.49
+ ,288.68
+ ,310.07
+ ,297.45
+ ,300.81
+ ,301.56
+ ,296.89
+ ,305.23
+ ,298.45
+ ,298.75
+ ,273.02
+ ,266.62
+ ,266.06
+ ,284.48
+ ,275.71
+ ,284.19
+ ,284.81
+ ,267.29
+ ,272.95
+ ,262.35
+ ,246.34
+ ,251.03
+ ,247.54
+ ,254.80
+ ,245.08
+ ,251.30
+ ,261.48
+ ,258.85
+ ,270.89
+ ,257.55
+ ,253.08
+ ,238.81
+ ,241.22
+ ,280.75
+ ,284.56
+ ,289.35
+ ,289.56
+ ,289.55
+ ,305.00
+ ,289.22
+ ,301.82
+ ,293.56
+ ,300.59
+ ,298.67
+ ,311.55
+ ,310.08
+ ,312.06
+ ,309.13
+ ,292.31
+ ,284.41
+ ,290.02
+ ,291.52
+ ,296.81
+ ,315.60
+ ,319.63
+ ,303.89
+ ,300.53
+ ,321.84
+ ,309.48
+ ,307.68
+ ,310.53
+ ,327.91
+ ,343.18
+ ,345.48
+ ,342.03
+ ,349.57
+ ,322.50
+ ,310.74
+ ,318.96
+ ,327.53
+ ,320.00
+ ,320.72
+ ,330.86
+ ,342.34
+ ,322.37
+ ,306.86
+ ,301.75
+ ,307.27
+ ,301.30
+ ,315.18
+ ,342.11
+ ,333.18
+ ,332.26
+ ,332.32
+ ,330.00
+ ,321.78
+ ,318.59
+ ,344.78
+ ,324.09
+ ,322.03
+ ,325.32
+ ,325.10
+ ,335.10
+ ,334.66
+ ,334.54
+ ,341.15
+ ,320.47
+ ,323.85
+ ,328.06
+ ,328.93
+ ,337.50
+ ,335.65
+ ,361.05
+ ,353.19
+ ,352.28
+ ,392.53
+ ,393.03
+ ,420.42
+ ,434.91
+ ,468.38
+ ,466.35
+ ,480.93
+ ,511.25
+ ,508.39
+ ,479.80
+ ,495.63
+ ,487.09
+ ,473.06
+ ,473.03
+ ,487.87
+ ,479.28
+ ,500.60
+ ,502.82
+ ,497.13
+ ,496.06
+ ,489.80
+ ,481.66
+ ,486.17
+ ,492.94
+ ,522.45
+ ,545.71
+ ,533.77
+ ,570.26
+ ,623.56
+ ,639.94
+ ,589.13
+ ,559.45
+ ,569.96
+ ,590.43
+ ,588.37
+ ,565.80
+ ,629.69
+ ,576.28
+ ,641.89
+ ,625.70
+ ,717.52
+ ,749.58
+ ,690.29
+ ,666.55
+ ,689.18
+ ,666.24
+ ,662.32
+ ,665.83
+ ,681.23
+ ,704.87
+ ,783.13
+ ,757.97
+ ,775.93
+ ,812.08
+ ,824.40
+ ,886.89
+ ,984.07
+ ,1015.59
+ ,897.30
+ ,980.37
+ ,957.37
+ ,968.96
+ ,1062.80
+ ,1047.67
+ ,967.91
+ ,1021.58
+ ,1014.02
+ ,1034.98
+ ,1068.80
+ ,1038.38
+ ,1133.26
+ ,1259.55
+ ,1207.42
+ ,1234.59
+ ,1297.03)
> par1 = '12'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 464
> (np <- floor(n / par1))
[1] 38
> 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,]  52.61  97.53 92.69  87.07 100.64 113.18 152.76 317.27 369.74 318.81
 [2,]  65.04  92.29 91.82  84.52  97.73 122.76 172.00 323.09 386.14 284.76
 [3,]  67.54  85.08 92.63  83.13  97.61 120.43 169.03 392.72 353.40 301.04
 [4,]  63.58  91.61 98.41  75.95 100.32 129.16 179.68 372.37 346.87 315.16
 [5,]  57.35  93.61 94.56  70.12 102.04 132.48 190.38 386.52 362.53 388.34
 [6,]  54.93  90.40 85.78  78.10 107.80 135.68 233.23 412.83 349.87 383.37
 [7,]  54.30  99.31 84.59  83.06 111.51 141.49 231.45 404.91 347.03 416.77
 [8,]  58.89 107.71 83.49  87.92 110.18 122.40 244.87 406.73 332.94 423.24
 [9,]  65.95 106.18 84.68  90.21 110.08 137.06 299.12 392.41 327.48 429.90
[10,]  82.65  98.80 80.12  89.95 117.40 144.84 385.01 363.31 327.92 486.07
[11,] 100.08  99.58 84.37  97.08 119.82 154.64 381.48 357.95 308.91 394.41
[12,] 100.68  98.85 85.94 102.08 118.79 148.04 321.56 375.10 285.71 410.93
       [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]  [,20]
 [1,] 430.88 425.18 417.93 329.63 371.84 345.58 321.84 280.65 282.52 257.99
 [2,] 447.29 437.24 403.43 350.96 375.90 360.76 324.56 280.21 288.89 251.28
 [3,] 431.65 431.92 404.96 336.16 373.31 364.40 330.90 265.93 308.46 243.14
 [4,] 456.53 412.65 393.64 332.15 391.91 374.62 310.91 267.80 292.89 246.81
 [5,] 452.93 419.37 399.98 349.46 374.28 369.07 318.07 278.03 280.79 224.50
 [6,] 440.90 436.40 375.93 383.64 384.69 341.80 312.36 291.86 273.61 241.25
 [7,] 416.46 421.37 366.57 369.82 372.16 337.87 315.19 262.61 276.67 254.97
 [8,] 451.49 423.66 353.90 345.50 371.97 336.58 332.89 264.80 277.92 261.39
 [9,] 432.00 402.45 347.51 337.80 351.76 332.66 310.67 265.67 250.28 266.67
[10,] 436.19 402.82 364.10 334.76 352.89 335.74 321.26 251.05 264.70 264.28
[11,] 428.55 400.46 328.64 338.02 330.48 321.64 316.15 256.11 268.95 270.45
[12,] 421.40 425.73 348.01 346.74 347.70 329.38 283.87 279.75 261.69 274.97
       [,21]  [,22]  [,23]  [,24]  [,25]  [,26]  [,27]  [,28]  [,29]  [,30]
 [1,] 281.13 317.52 291.51 308.65 300.81 284.81 270.89 301.82 296.81 342.03
 [2,] 300.65 325.31 289.94 307.01 301.56 267.29 257.55 293.56 315.60 349.57
 [3,] 321.12 317.59 287.07 298.59 296.89 272.95 253.08 300.59 319.63 322.50
 [4,] 354.79 313.37 280.74 293.51 305.23 262.35 238.81 298.67 303.89 310.74
 [5,] 318.97 313.00 294.95 294.90 298.45 246.34 241.22 311.55 300.53 318.96
 [6,] 298.71 314.77 288.98 296.14 298.75 251.03 280.75 310.08 321.84 327.53
 [7,] 318.85 298.37 285.63 294.25 273.02 247.54 284.56 312.06 309.48 320.00
 [8,] 327.89 311.10 294.55 291.75 266.62 254.80 289.35 309.13 307.68 320.72
 [9,] 348.19 308.79 290.67 290.49 266.06 245.08 289.56 292.31 310.53 330.86
[10,] 335.18 297.30 314.78 288.68 284.48 251.30 289.55 284.41 327.91 342.34
[11,] 332.98 293.58 306.50 310.07 275.71 261.48 305.00 290.02 343.18 322.37
[12,] 331.04 291.35 304.48 297.45 284.19 258.85 289.22 291.52 345.48 306.86
       [,31]  [,32]  [,33]  [,34]  [,35]  [,36]  [,37]   [,38]
 [1,] 301.75 324.09 337.50 511.25 496.06 559.45 666.55  886.89
 [2,] 307.27 322.03 335.65 508.39 489.80 569.96 689.18  984.07
 [3,] 301.30 325.32 361.05 479.80 481.66 590.43 666.24 1015.59
 [4,] 315.18 325.10 353.19 495.63 486.17 588.37 662.32  897.30
 [5,] 342.11 335.10 352.28 487.09 492.94 565.80 665.83  980.37
 [6,] 333.18 334.66 392.53 473.06 522.45 629.69 681.23  957.37
 [7,] 332.26 334.54 393.03 473.03 545.71 576.28 704.87  968.96
 [8,] 332.32 341.15 420.42 487.87 533.77 641.89 783.13 1062.80
 [9,] 330.00 320.47 434.91 479.28 570.26 625.70 757.97 1047.67
[10,] 321.78 323.85 468.38 500.60 623.56 717.52 775.93  967.91
[11,] 318.59 328.06 466.35 502.82 639.94 749.58 812.08 1021.58
[12,] 344.78 328.93 480.93 497.13 589.13 690.29 824.40 1014.02
> 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]  68.63333  96.74583  88.25667  85.76583 107.82667 133.51333 246.71417
 [8] 375.43417 341.54500 379.40000 437.18917 419.93750 375.38333 346.22000
[15] 366.57417 345.84167 316.55583 270.37250 277.28083 254.80833 322.45833
[22] 308.50417 294.15000 297.62417 287.64750 258.65167 274.12833 299.64333
[29] 316.88000 326.20667 323.37667 328.60833 399.68500 491.32917 539.28750
[36] 625.41333 724.14417 983.71083
> arr.sd
 [1] 16.872279  6.505326  5.527374  8.808521  8.133396 12.469350 82.111673
 [8] 30.957084 27.190291 61.390902 12.771409 12.871889 28.264815 16.053419
[15] 17.361386 17.143652 12.589637 11.783058 15.387062 14.302033 21.014599
[22] 10.793407  9.778019  7.191284 14.422103 11.951594 21.531902  9.452661
[29] 15.619636 12.944017 14.817295  6.377034 53.427382 13.262073 55.300552
[36] 63.525187 62.097865 53.706577
> arr.range
 [1]  48.07  22.63  18.29  31.96  22.21  41.46 232.25  95.56 100.43 201.31
[11]  40.07  36.78  89.29  54.01  61.43  52.98  49.02  40.81  58.18  50.47
[21]  73.66  33.96  34.04  21.39  39.17  39.73  66.19  27.65  48.67  42.71
[31]  43.48  20.68 145.28  38.22 158.28 190.13 162.08 175.91
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
     1.3296       0.0648  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -1.2169         0.7182  

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

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

Coefficients:
(Intercept)     arr.mean  
     7.4785       0.1904  

> postscript(file="/var/www/rcomp/tmp/17hdx1323853162.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/www/rcomp/tmp/2nkre1323853162.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/rcomp/tmp/3bh1j1323853162.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4ywbs1323853162.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/www/rcomp/tmp/5jd9p1323853162.tab") 
> 
> try(system("convert tmp/17hdx1323853162.ps tmp/17hdx1323853162.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nkre1323853162.ps tmp/2nkre1323853162.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.848   0.184   1.021