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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 22 Dec 2013 14:00:26 -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/2013/Dec/22/t1387738850pqu6valaovcct0u.htm/, Retrieved Sun, 05 Dec 2021 17:37:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232561, Retrieved Sun, 05 Dec 2021 17:37:50 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact72
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [werkloosheidscijf...] [2013-10-08 18:26:09] [6a1a05b03d1c87a66b915fc3d5866cc8]
- RMPD  [Harrell-Davis Quantiles] [consumtieprijs va...] [2013-12-21 15:50:38] [6a1a05b03d1c87a66b915fc3d5866cc8]
-   PD    [Harrell-Davis Quantiles] [] [2013-12-21 16:11:56] [6a1a05b03d1c87a66b915fc3d5866cc8]
- RMPD      [(Partial) Autocorrelation Function] [] [2013-12-21 18:23:11] [6a1a05b03d1c87a66b915fc3d5866cc8]
- RMPD          [Standard Deviation-Mean Plot] [] [2013-12-22 19:00:26] [4a7f7842fc88d649abcd00dd10ef7b6c] [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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232561&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232561&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232561&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
129809.33333333339534.1464349161529876
226911.91666666676314.1373766022923731
3256538306.2242051039425331
423293.16666666674863.9772508688515966
523712.256639.8206865848422631
622142.255608.3585043786519045

\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=232561&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=232561&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232561&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
129809.33333333339534.1464349161529876
226911.91666666676314.1373766022923731
3256538306.2242051039425331
423293.16666666674863.9772508688515966
523712.256639.8206865848422631
622142.255608.3585043786519045







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-5889.43703876602
beta0.505559118946274
S.D.0.178206060929851
T-STAT2.83693560313463
p-value0.0470133361198829

\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=232561&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=232561&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232561&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
beta0.505559118946274
S.D.0.178206060929851
T-STAT2.83693560313463
p-value0.0470133361198829







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-9.59236860367955
beta1.81632201037389
S.D.0.687487051387064
T-STAT2.64197268400808
p-value0.0574617220432723
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=232561&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=232561&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232561&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
beta1.81632201037389
S.D.0.687487051387064
T-STAT2.64197268400808
p-value0.0574617220432723
Lambda-0.816322010373886



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')