## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 27 Dec 2012 16:11:16 -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/2012/Dec/27/t1356642710ld57hl7gjj1ylug.htm/, Retrieved Tue, 07 Feb 2023 17:11:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204793, Retrieved Tue, 07 Feb 2023 17:11:35 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Autocorrelatie In...] [2012-11-12 10:59:56] [41982c7b3984978a38ca838fef047984]
- RMPD  [Bootstrap Plot - Central Tendency] [Bootstrap Plot (m...] [2012-12-27 20:12:14] [41982c7b3984978a38ca838fef047984]
- R P     [Bootstrap Plot - Central Tendency] [Bootstrap Plot (m...] [2012-12-27 20:14:03] [41982c7b3984978a38ca838fef047984]
- RMPD      [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Plot (g...] [2012-12-27 20:38:33] [41982c7b3984978a38ca838fef047984]
- R  D        [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Plot (g...] [2012-12-27 20:42:04] [41982c7b3984978a38ca838fef047984]
- RM D            [Standard Deviation-Mean Plot] [Spreidings- en ge...] [2012-12-27 21:11:16] [97ff841fcf87514e420f2e9629cfd808] [Current]
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Dataseries X:
41086
39690
43129
37863
35953
29133
24693
22205
21725
27192
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204793&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204793&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204793&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ jenkins.wessa.net

 Standard Deviation-Mean Plot Section Mean Standard Deviation Range 1 29809.3333333333 9534.14643491615 29876 2 26911.9166666667 6314.13737660229 23731 3 25653 8306.22420510394 25331 4 23293.1666666667 4863.97725086885 15966 5 23712.25 6639.82068658484 22631 6 22142.25 5608.35850437865 19045

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 29809.3333333333 & 9534.14643491615 & 29876 \tabularnewline
2 & 26911.9166666667 & 6314.13737660229 & 23731 \tabularnewline
3 & 25653 & 8306.22420510394 & 25331 \tabularnewline
4 & 23293.1666666667 & 4863.97725086885 & 15966 \tabularnewline
5 & 23712.25 & 6639.82068658484 & 22631 \tabularnewline
6 & 22142.25 & 5608.35850437865 & 19045 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204793&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]29809.3333333333[/C][C]9534.14643491615[/C][C]29876[/C][/ROW]
[ROW][C]2[/C][C]26911.9166666667[/C][C]6314.13737660229[/C][C]23731[/C][/ROW]
[ROW][C]3[/C][C]25653[/C][C]8306.22420510394[/C][C]25331[/C][/ROW]
[ROW][C]4[/C][C]23293.1666666667[/C][C]4863.97725086885[/C][C]15966[/C][/ROW]
[ROW][C]5[/C][C]23712.25[/C][C]6639.82068658484[/C][C]22631[/C][/ROW]
[ROW][C]6[/C][C]22142.25[/C][C]5608.35850437865[/C][C]19045[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204793&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204793&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 Section Mean Standard Deviation Range 1 29809.3333333333 9534.14643491615 29876 2 26911.9166666667 6314.13737660229 23731 3 25653 8306.22420510394 25331 4 23293.1666666667 4863.97725086885 15966 5 23712.25 6639.82068658484 22631 6 22142.25 5608.35850437865 19045

 Regression: S.E.(k) = alpha + beta * Mean(k) alpha -5889.43703876602 beta 0.505559118946274 S.D. 0.178206060929851 T-STAT 2.83693560313463 p-value 0.0470133361198829

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5889.43703876602 \tabularnewline
beta & 0.505559118946274 \tabularnewline
S.D. & 0.178206060929851 \tabularnewline
T-STAT & 2.83693560313463 \tabularnewline
p-value & 0.0470133361198829 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204793&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5889.43703876602[/C][/ROW]
[ROW][C]beta[/C][C]0.505559118946274[/C][/ROW]
[ROW][C]S.D.[/C][C]0.178206060929851[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.83693560313463[/C][/ROW]
[ROW][C]p-value[/C][C]0.0470133361198829[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204793&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204793&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 -5889.43703876602 beta 0.505559118946274 S.D. 0.178206060929851 T-STAT 2.83693560313463 p-value 0.0470133361198829

 Regression: ln S.E.(k) = alpha + beta * ln Mean(k) alpha -9.59236860367955 beta 1.81632201037389 S.D. 0.687487051387064 T-STAT 2.64197268400808 p-value 0.0574617220432723 Lambda -0.816322010373886

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.59236860367955 \tabularnewline
beta & 1.81632201037389 \tabularnewline
S.D. & 0.687487051387064 \tabularnewline
T-STAT & 2.64197268400808 \tabularnewline
p-value & 0.0574617220432723 \tabularnewline
Lambda & -0.816322010373886 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204793&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.59236860367955[/C][/ROW]
[ROW][C]beta[/C][C]1.81632201037389[/C][/ROW]
[ROW][C]S.D.[/C][C]0.687487051387064[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.64197268400808[/C][/ROW]
[ROW][C]p-value[/C][C]0.0574617220432723[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.816322010373886[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204793&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204793&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 -9.59236860367955 beta 1.81632201037389 S.D. 0.687487051387064 T-STAT 2.64197268400808 p-value 0.0574617220432723 Lambda -0.816322010373886

par1 <- as.numeric(par1)(n <- length(x))(np <- floor(n / par1))arr <- array(NA,dim=c(par1,np))j <- 0k <- 1for (i in 1:(np*par1)){j = j + 1arr[j,k] <- x[i]if (j == par1) {j = 0k=k+1}}arrarr.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.meanarr.sdarr.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')