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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 17 Dec 2011 06:43:56 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/17/t1324122398a2x049mxl3i43hc.htm/, Retrieved Thu, 25 Apr 2024 14:53:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156213, Retrieved Thu, 25 Apr 2024 14:53:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [paper mean plot] [2011-12-17 11:43:56] [c897fb90cb9e1f725365d7e541ad7850] [Current]
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Dataseries X:
1954
2302
3054
2414
2226
2725
2589
3470
2400
3180
4009
3924
2072
2434
2956
2828
2687
2629
3150
4119
3030
3055
3821
4001
2529
2472
3134
2789
2758
2993
3282
3437
2804
3076
3782
3889
2271
2452
3084
2522
2769
3438
2839
3746
2632
2851
3871
3618
2389
2344
2678
2492
2858
2246
2800
3869
3007
3023
3907
4209
2353
2570
2903
2910
3782
2759
2931
3641
2794
3070
3576
4106
2452
2206
2488
2416
2534
2521
3093
3903
2907
3025
3812
4209
2138
2419
2622
2912
2708
2798
3254
2895
3263
3736
4077
4097
2175
3138
2823
2498
2822
2738
4137
3515
3785
3632
4504
4451
2550
2867
3458
2961
3163
2880
3331
3062
3534
3622
4464
5411
2564
2820
3508
3088
3299
2939
3320
3418
3604
3495
4163
4882
2211
3260
2992
2425
2707
3244
3965
3315
3333
3583
4021
4904
2252
2952
3573
3048
3059
2731
3563
3092
3478
3478
4308
5029
2075
3264
3308
3688
3136
2824
3644
4694
2914
3686
4358
5587
2265
3685
3754
3708
3210
3517
3905
3670
4221
4404
5086
5725
2367
3819
4067
4022
3937
4365
4290




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156213&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156213&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156213&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12853.91666666667674.221902820152055
23065.16666666667629.0207155619442047
33078.75453.6544790516641417
43007.75538.7187029508911600
52985.16666666667662.7431743530181963
63116.25534.827436061051753
72963.83333333333668.7299812919922003
83076.58333333333627.8871436424821959
93351.5771.1716587587532329
103441.91666666667790.3175953470552861
113425617.5747286398192318
123330739.058368958282693
133380.25728.8414374259272777
143598.16666666667931.6875045102873512
153929.16666666667880.9815634572133460

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2853.91666666667 & 674.22190282015 & 2055 \tabularnewline
2 & 3065.16666666667 & 629.020715561944 & 2047 \tabularnewline
3 & 3078.75 & 453.654479051664 & 1417 \tabularnewline
4 & 3007.75 & 538.718702950891 & 1600 \tabularnewline
5 & 2985.16666666667 & 662.743174353018 & 1963 \tabularnewline
6 & 3116.25 & 534.82743606105 & 1753 \tabularnewline
7 & 2963.83333333333 & 668.729981291992 & 2003 \tabularnewline
8 & 3076.58333333333 & 627.887143642482 & 1959 \tabularnewline
9 & 3351.5 & 771.171658758753 & 2329 \tabularnewline
10 & 3441.91666666667 & 790.317595347055 & 2861 \tabularnewline
11 & 3425 & 617.574728639819 & 2318 \tabularnewline
12 & 3330 & 739.05836895828 & 2693 \tabularnewline
13 & 3380.25 & 728.841437425927 & 2777 \tabularnewline
14 & 3598.16666666667 & 931.687504510287 & 3512 \tabularnewline
15 & 3929.16666666667 & 880.981563457213 & 3460 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156213&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]2853.91666666667[/C][C]674.22190282015[/C][C]2055[/C][/ROW]
[ROW][C]2[/C][C]3065.16666666667[/C][C]629.020715561944[/C][C]2047[/C][/ROW]
[ROW][C]3[/C][C]3078.75[/C][C]453.654479051664[/C][C]1417[/C][/ROW]
[ROW][C]4[/C][C]3007.75[/C][C]538.718702950891[/C][C]1600[/C][/ROW]
[ROW][C]5[/C][C]2985.16666666667[/C][C]662.743174353018[/C][C]1963[/C][/ROW]
[ROW][C]6[/C][C]3116.25[/C][C]534.82743606105[/C][C]1753[/C][/ROW]
[ROW][C]7[/C][C]2963.83333333333[/C][C]668.729981291992[/C][C]2003[/C][/ROW]
[ROW][C]8[/C][C]3076.58333333333[/C][C]627.887143642482[/C][C]1959[/C][/ROW]
[ROW][C]9[/C][C]3351.5[/C][C]771.171658758753[/C][C]2329[/C][/ROW]
[ROW][C]10[/C][C]3441.91666666667[/C][C]790.317595347055[/C][C]2861[/C][/ROW]
[ROW][C]11[/C][C]3425[/C][C]617.574728639819[/C][C]2318[/C][/ROW]
[ROW][C]12[/C][C]3330[/C][C]739.05836895828[/C][C]2693[/C][/ROW]
[ROW][C]13[/C][C]3380.25[/C][C]728.841437425927[/C][C]2777[/C][/ROW]
[ROW][C]14[/C][C]3598.16666666667[/C][C]931.687504510287[/C][C]3512[/C][/ROW]
[ROW][C]15[/C][C]3929.16666666667[/C][C]880.981563457213[/C][C]3460[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156213&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156213&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12853.91666666667674.221902820152055
23065.16666666667629.0207155619442047
33078.75453.6544790516641417
43007.75538.7187029508911600
52985.16666666667662.7431743530181963
63116.25534.827436061051753
72963.83333333333668.7299812919922003
83076.58333333333627.8871436424821959
93351.5771.1716587587532329
103441.91666666667790.3175953470552861
113425617.5747286398192318
123330739.058368958282693
133380.25728.8414374259272777
143598.16666666667931.6875045102873512
153929.16666666667880.9815634572133460







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-366.287123813665
beta0.32392256202912
S.D.0.085373067934898
T-STAT3.79420079264494
p-value0.00223178722976884

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -366.287123813665 \tabularnewline
beta & 0.32392256202912 \tabularnewline
S.D. & 0.085373067934898 \tabularnewline
T-STAT & 3.79420079264494 \tabularnewline
p-value & 0.00223178722976884 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156213&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-366.287123813665[/C][/ROW]
[ROW][C]beta[/C][C]0.32392256202912[/C][/ROW]
[ROW][C]S.D.[/C][C]0.085373067934898[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.79420079264494[/C][/ROW]
[ROW][C]p-value[/C][C]0.00223178722976884[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156213&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156213&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-366.287123813665
beta0.32392256202912
S.D.0.085373067934898
T-STAT3.79420079264494
p-value0.00223178722976884







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.5423283089601
beta1.49166364696437
S.D.0.453771427329061
T-STAT3.28725776266794
p-value0.00589037666742168
Lambda-0.491663646964367

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.5423283089601 \tabularnewline
beta & 1.49166364696437 \tabularnewline
S.D. & 0.453771427329061 \tabularnewline
T-STAT & 3.28725776266794 \tabularnewline
p-value & 0.00589037666742168 \tabularnewline
Lambda & -0.491663646964367 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156213&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.5423283089601[/C][/ROW]
[ROW][C]beta[/C][C]1.49166364696437[/C][/ROW]
[ROW][C]S.D.[/C][C]0.453771427329061[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.28725776266794[/C][/ROW]
[ROW][C]p-value[/C][C]0.00589037666742168[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.491663646964367[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156213&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156213&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.5423283089601
beta1.49166364696437
S.D.0.453771427329061
T-STAT3.28725776266794
p-value0.00589037666742168
Lambda-0.491663646964367



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
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
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
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='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='mytable.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)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$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='mytable2.tab')