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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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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(1021.3
+ ,1039.79
+ ,938.12
+ ,947.36
+ ,956.6
+ ,956.6
+ ,942.74
+ ,951.98
+ ,919.63
+ ,901.15
+ ,887.28
+ ,836.45
+ ,841.07
+ ,836.45
+ ,831.83
+ ,817.97
+ ,771.75
+ ,707.05
+ ,716.3
+ ,725.54
+ ,716.3
+ ,707.05
+ ,716.3
+ ,780.99
+ ,859.56
+ ,961.22
+ ,938.12
+ ,988.95
+ ,910.39
+ ,901.15
+ ,896.53
+ ,910.39
+ ,988.95
+ ,988.95
+ ,965.85
+ ,975.09
+ ,1002.82
+ ,1025.92
+ ,1081.38
+ ,1164.56
+ ,1201.53
+ ,1229.26
+ ,1275.47
+ ,1275.47
+ ,1307.82
+ ,1252.36
+ ,1261.61
+ ,1340.17
+ ,1414.11
+ ,1409.49
+ ,1432.59
+ ,1520.4
+ ,1529.64
+ ,1455.7
+ ,1427.97
+ ,1538.88
+ ,1612.82
+ ,1635.93
+ ,1603.58
+ ,1589.72
+ ,1557.37
+ ,1589.72
+ ,1668.28
+ ,1635.93
+ ,1615.68
+ ,1644.69
+ ,1622.71
+ ,1626.11
+ ,1705.55
+ ,1841.35
+ ,2029.03
+ ,2024.21
+ ,1952.87
+ ,2153.06
+ ,2339.29
+ ,2502.89
+ ,2515.37
+ ,2445.68
+ ,2491.11
+ ,2691.32
+ ,2651.8
+ ,2593.49
+ ,2697.23
+ ,2751.63
+ ,2713.9
+ ,2747.21
+ ,2982.32
+ ,3063.39
+ ,3058.7
+ ,3074.38
+ ,3341.06
+ ,3500.03
+ ,392.88
+ ,3071.52
+ ,2516.41
+ ,2350.7
+ ,2488.68
+ ,2872.65
+ ,3220.21
+ ,3078.04
+ ,3043.98
+ ,3134.34
+ ,3141.85
+ ,3128.01
+ ,3241.16
+ ,3389.48
+ ,3406.36
+ ,3449.84
+ ,3606.24
+ ,3653.99
+ ,3607.31
+ ,3712.52
+ ,3803.47
+ ,3806.33
+ ,3768.4
+ ,3952.06
+ ,4134.85
+ ,4060.9
+ ,3999.88
+ ,4004.03
+ ,3977.34
+ ,3650.08
+ ,3708.85
+ ,3764.78
+ ,3761.86
+ ,3802.55
+ ,3773.52
+ ,3428.7
+ ,3194.21
+ ,3095.56
+ ,3064.85
+ ,3022.98
+ ,2887.66
+ ,3178.86
+ ,3438.47
+ ,3493.87
+ ,3421.89
+ ,3390.28
+ ,3319.24
+ ,3287.84
+ ,3222.82
+ ,3182.69
+ ,3180.21
+ ,3116.34
+ ,3297.46
+ ,3357.48
+ ,3386.03
+ ,3319.45
+ ,3363.59
+ ,3303.47
+ ,3210.55
+ ,3050.27
+ ,3010.55
+ ,3011.65
+ ,3104.98
+ ,3087.85
+ ,3160.16
+ ,3319.22
+ ,3432.49
+ ,3475.68
+ ,3347.48
+ ,3388.81
+ ,3610.23
+ ,3691.45
+ ,3587.86
+ ,3704.62
+ ,3798.75
+ ,3956.54
+ ,4121.94
+ ,4148.56
+ ,4100.37
+ ,4060.71
+ ,4147.86
+ ,3926.61
+ ,3865.41
+ ,3978.57
+ ,3851.95
+ ,3701.22
+ ,3738.65
+ ,3766.9
+ ,3711.02
+ ,3675.22
+ ,3560.53
+ ,3723.8
+ ,3914.27
+ ,3870.77
+ ,3924.36
+ ,3968.89
+ ,3982.93
+ ,3917.09
+ ,3969.18
+ ,4149.81
+ ,4406.88
+ ,423.82
+ ,417.72
+ ,4527.16
+ ,4617.39
+ ,4656.23
+ ,4579.9
+ ,4652.4
+ ,4722.95
+ ,4845.81
+ ,4975.21
+ ,5083.64
+ ,5378.04
+ ,5684.44
+ ,5841.87
+ ,5857.23
+ ,6174.52
+ ,6413.17
+ ,6780.11
+ ,6524.94
+ ,6466.7
+ ,6495.61
+ ,6399.52
+ ,6729.98
+ ,7060.77
+ ,7423.27
+ ,8069.17
+ ,8650.68
+ ,8938.07
+ ,9482.08
+ ,10225.26
+ ,9390.27
+ ,8546.11
+ ,8073.77
+ ,8655.31
+ ,9150.1
+ ,9775.81
+ ,9785.14
+ ,9363.44
+ ,9304.18
+ ,9030.26
+ ,8920.8
+ ,8606.08
+ ,8353.75
+ ,8615.63
+ ,8128.64
+ ,8715.94
+ ,8500.8
+ ,8142.58
+ ,7614.66
+ ,7558.95
+ ,7820.75
+ ,7828.9
+ ,7904.59
+ ,8140.97
+ ,8483.01
+ ,8322.68
+ ,8268.01
+ ,8402.05
+ ,8177.78
+ ,7950.54
+ ,8049.94
+ ,7674.13
+ ,7666.36
+ ,7570.18
+ ,7694.45
+ ,7810.64
+ ,7748.43
+ ,7040.64
+ ,7077.26
+ ,7245.51
+ ,7289.12
+ ,7486.92
+ ,7519.88
+ ,7554.84
+ ,7780.89
+ ,7748.09
+ ,7152.25
+ ,6484.66
+ ,6254.58
+ ,5867.32
+ ,5544.16
+ ,5822.74
+ ,5690.63
+ ,5564.78
+ ,5088.39
+ ,4784.22
+ ,5332.46
+ ,5541.48
+ ,5723.92
+ ,5736.99
+ ,5992.07
+ ,6091.43
+ ,6158.17
+ ,6303.79
+ ,6349.71
+ ,6802.96
+ ,7132.68
+ ,7073.29
+ ,7264.5
+ ,7105.33
+ ,7218.71
+ ,7225.72
+ ,7354.25
+ ,7745.46
+ ,8070.26
+ ,8366.33
+ ,8667.51
+ ,8854.34
+ ,9218.1
+ ,9332.9
+ ,9358.31
+ ,9248.66
+ ,9401.2
+ ,9652.04
+ ,9957.38
+ ,10110.63
+ ,10169.26
+ ,10343.78
+ ,10750.21
+ ,11337.5
+ ,11786.96
+ ,12083.04
+ ,12007.74
+ ,11745.93
+ ,11051.51
+ ,11445.9
+ ,11924.88
+ ,12247.63
+ ,12690.91
+ ,12910.7
+ ,13202.12
+ ,13654.67
+ ,13862.82
+ ,13523.93
+ ,14211.17
+ ,14510.35
+ ,14289.23
+ ,14111.82
+ ,13086.59
+ ,13351.54
+ ,13747.69
+ ,12855.61
+ ,12926.93
+ ,12121.95
+ ,11731.65
+ ,11639.51
+ ,12163.78
+ ,12029.53
+ ,11234.18
+ ,9852.13
+ ,9709.04
+ ,9332.75
+ ,7108.6
+ ,6691.49
+ ,6143.05
+ ,6379.15
+ ,5994.58
+ ,5607.94
+ ,6046.13
+ ,6624.96
+ ,6652.54
+ ,6696
+ ,7315.16
+ ,7907.79
+ ,8066.35
+ ,7939.64
+ ,8068.48
+ ,8186.33
+ ,7975.21
+ ,8357.51
+ ,8463.38
+ ,7937.68
+ ,8034.62
+ ,8056.61
+ ,8176.95
+ ,8441.04
+ ,8697.39
+ ,8665.57
+ ,8625.77
+ ,8718.42
+ ,8822.34
+ ,8597.67
+ ,8782.05
+ ,8661.06
+ ,8265.32
+ ,8072.58
+ ,721.85
+ ,7138.6
+ ,7351.11
+ ,7077
+ ,7272.37
+ ,7577.84)
> 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] 385
> (np <- floor(n / par1))
[1] 32
> 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]
 [1,] 1021.30 841.07 859.56 1002.82 1414.11 1557.37 1952.87 2713.90 2488.68
 [2,] 1039.79 836.45 961.22 1025.92 1409.49 1589.72 2153.06 2747.21 2872.65
 [3,]  938.12 831.83 938.12 1081.38 1432.59 1668.28 2339.29 2982.32 3220.21
 [4,]  947.36 817.97 988.95 1164.56 1520.40 1635.93 2502.89 3063.39 3078.04
 [5,]  956.60 771.75 910.39 1201.53 1529.64 1615.68 2515.37 3058.70 3043.98
 [6,]  956.60 707.05 901.15 1229.26 1455.70 1644.69 2445.68 3074.38 3134.34
 [7,]  942.74 716.30 896.53 1275.47 1427.97 1622.71 2491.11 3341.06 3141.85
 [8,]  951.98 725.54 910.39 1275.47 1538.88 1626.11 2691.32 3500.03 3128.01
 [9,]  919.63 716.30 988.95 1307.82 1612.82 1705.55 2651.80  392.88 3241.16
[10,]  901.15 707.05 988.95 1252.36 1635.93 1841.35 2593.49 3071.52 3389.48
[11,]  887.28 716.30 965.85 1261.61 1603.58 2029.03 2697.23 2516.41 3406.36
[12,]  836.45 780.99 975.09 1340.17 1589.72 2024.21 2751.63 2350.70 3449.84
        [,10]   [,11]   [,12]   [,13]   [,14]   [,15]   [,16]   [,17]   [,18]
 [1,] 3606.24 3977.34 2887.66 3297.46 3160.16 4121.94 3711.02 4406.88 5378.04
 [2,] 3653.99 3650.08 3178.86 3357.48 3319.22 4148.56 3675.22  423.82 5684.44
 [3,] 3607.31 3708.85 3438.47 3386.03 3432.49 4100.37 3560.53  417.72 5841.87
 [4,] 3712.52 3764.78 3493.87 3319.45 3475.68 4060.71 3723.80 4527.16 5857.23
 [5,] 3803.47 3761.86 3421.89 3363.59 3347.48 4147.86 3914.27 4617.39 6174.52
 [6,] 3806.33 3802.55 3390.28 3303.47 3388.81 3926.61 3870.77 4656.23 6413.17
 [7,] 3768.40 3773.52 3319.24 3210.55 3610.23 3865.41 3924.36 4579.90 6780.11
 [8,] 3952.06 3428.70 3287.84 3050.27 3691.45 3978.57 3968.89 4652.40 6524.94
 [9,] 4134.85 3194.21 3222.82 3010.55 3587.86 3851.95 3982.93 4722.95 6466.70
[10,] 4060.90 3095.56 3182.69 3011.65 3704.62 3701.22 3917.09 4845.81 6495.61
[11,] 3999.88 3064.85 3180.21 3104.98 3798.75 3738.65 3969.18 4975.21 6399.52
[12,] 4004.03 3022.98 3116.34 3087.85 3956.54 3766.90 4149.81 5083.64 6729.98
         [,19]   [,20]   [,21]   [,22]   [,23]   [,24]   [,25]    [,26]
 [1,]  7060.77 9775.81 8142.58 7950.54 7486.92 5564.78 6802.96  8854.34
 [2,]  7423.27 9785.14 7614.66 8049.94 7519.88 5088.39 7132.68  9218.10
 [3,]  8069.17 9363.44 7558.95 7674.13 7554.84 4784.22 7073.29  9332.90
 [4,]  8650.68 9304.18 7820.75 7666.36 7780.89 5332.46 7264.50  9358.31
 [5,]  8938.07 9030.26 7828.90 7570.18 7748.09 5541.48 7105.33  9248.66
 [6,]  9482.08 8920.80 7904.59 7694.45 7152.25 5723.92 7218.71  9401.20
 [7,] 10225.26 8606.08 8140.97 7810.64 6484.66 5736.99 7225.72  9652.04
 [8,]  9390.27 8353.75 8483.01 7748.43 6254.58 5992.07 7354.25  9957.38
 [9,]  8546.11 8615.63 8322.68 7040.64 5867.32 6091.43 7745.46 10110.63
[10,]  8073.77 8128.64 8268.01 7077.26 5544.16 6158.17 8070.26 10169.26
[11,]  8655.31 8715.94 8402.05 7245.51 5822.74 6303.79 8366.33 10343.78
[12,]  9150.10 8500.80 8177.78 7289.12 5690.63 6349.71 8667.51 10750.21
         [,27]    [,28]    [,29]   [,30]   [,31]   [,32]
 [1,] 11337.50 13654.67 12121.95 6379.15 8186.33 8718.42
 [2,] 11786.96 13862.82 11731.65 5994.58 7975.21 8822.34
 [3,] 12083.04 13523.93 11639.51 5607.94 8357.51 8597.67
 [4,] 12007.74 14211.17 12163.78 6046.13 8463.38 8782.05
 [5,] 11745.93 14510.35 12029.53 6624.96 7937.68 8661.06
 [6,] 11051.51 14289.23 11234.18 6652.54 8034.62 8265.32
 [7,] 11445.90 14111.82  9852.13 6696.00 8056.61 8072.58
 [8,] 11924.88 13086.59  9709.04 7315.16 8176.95  721.85
 [9,] 12247.63 13351.54  9332.75 7907.79 8441.04 7138.60
[10,] 12690.91 13747.69  7108.60 8066.35 8697.39 7351.11
[11,] 12910.70 12855.61  6691.49 7939.64 8665.57 7077.00
[12,] 13202.12 12926.93  6143.05 8068.48 8625.77 7272.37
> 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]   941.5833   764.0500   940.4292  1201.5308  1514.2358  1713.3858
 [7]  2482.1450  2734.3750  3132.8833  3842.4983  3520.4400  3260.0142
[13]  3208.6108  3539.4408  3950.7292  3863.9892  3992.4258  6228.8442
[19]  8638.7383  8925.0392  8055.4108  7568.1000  6742.2467  5722.2842
[25]  7502.2500  9699.7342 12036.2350 13677.6958  9979.8050  6941.5600
[31]  8301.5050  7456.6975
> arr.sd
 [1]   54.54253   55.46727   43.86188  110.59445   84.00342  162.49531
 [7]  236.56621  805.45734  261.84309  182.88527  340.19748  168.84555
[13]  146.24253  226.90669  165.47947  164.51639 1678.78835  441.54588
[19]  892.60131  538.71988  304.41874  331.34339  880.83801  488.25547
[25]  579.08117  561.38073  644.23958  547.63524 2240.99735  886.35738
[31]  276.67565 2228.89340
> arr.range
 [1]  203.34  134.02  129.39  337.35  226.44  471.66  798.76 3107.15  961.16
[10]  528.61  954.36  606.21  375.48  796.38  447.34  589.28 4665.92 1402.07
[19] 3164.49 1656.50  924.06 1009.30 2236.73 1565.49 1864.55 1895.87 2150.61
[28] 1654.74 6020.73 2460.54  759.71 8100.49
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  115.34518      0.07578  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -2.666          1.013  

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

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

Coefficients:
(Intercept)     arr.mean  
   390.6918       0.2307  

> postscript(file="/var/wessaorg/rcomp/tmp/1j8ya1355694625.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/2p1vb1355694625.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/3q6rp1355694625.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4u8s21355694625.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5vegt1355694625.tab") 
> 
> try(system("convert tmp/1j8ya1355694625.ps tmp/1j8ya1355694625.png",intern=TRUE))
character(0)
> try(system("convert tmp/2p1vb1355694625.ps tmp/2p1vb1355694625.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.274   0.569   2.883