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Description of Statistical Computation

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 computationTue, 22 Dec 2009 03:56:36 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/22/t1261479475a9pggdmgojwzn2b.htm/, Retrieved Sat, 04 May 2024 08:23:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70431, Retrieved Sat, 04 May 2024 08:23:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordspaper, TRA, inflatie4
Estimated Impact136

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2009-12-22 10:56:36] [30f5b608e5a1bbbae86b1702c0071566] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.1
1.2
1.1
1.2
1.4
1.5
1.5
1.8
1.6
1.5
1.4
1.4
1.4
1.4
1.5
1.4
1.1
1.1
0.9
0.9
0.9
0.9
1.1
1.3
1
1.1
1.4
1.4
1.3
1.4
1
1.8
1.5
1.5
1.4
1.6
1.6
1.6
1.4
1.7
1.8
1.9
2.2
2.1
2.4
2.6
2.8
2.7
2.6
2.9
2.8
2.2
2.2
2.2
2
2
1.7
1.4
1.3
1.4
1.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70431&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70431&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70431&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.150.05773502691896250.0999999999999999
21.550.1732050807568880.4
31.4750.0957427107756340.2
41.4250.050.1
510.1154700538379250.2
61.050.1914854215512680.4
71.2250.2061552812808830.4
81.3750.3304037933599830.8
91.50.08164965809277270.2
101.5750.1258305739211790.3
1120.1825741858350550.4
122.6250.1707825127659930.4
132.6250.3095695936834450.7
142.10.1154700538379250.2
151.450.1732050807568880.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.15 & 0.0577350269189625 & 0.0999999999999999 \tabularnewline
2 & 1.55 & 0.173205080756888 & 0.4 \tabularnewline
3 & 1.475 & 0.095742710775634 & 0.2 \tabularnewline
4 & 1.425 & 0.05 & 0.1 \tabularnewline
5 & 1 & 0.115470053837925 & 0.2 \tabularnewline
6 & 1.05 & 0.191485421551268 & 0.4 \tabularnewline
7 & 1.225 & 0.206155281280883 & 0.4 \tabularnewline
8 & 1.375 & 0.330403793359983 & 0.8 \tabularnewline
9 & 1.5 & 0.0816496580927727 & 0.2 \tabularnewline
10 & 1.575 & 0.125830573921179 & 0.3 \tabularnewline
11 & 2 & 0.182574185835055 & 0.4 \tabularnewline
12 & 2.625 & 0.170782512765993 & 0.4 \tabularnewline
13 & 2.625 & 0.309569593683445 & 0.7 \tabularnewline
14 & 2.1 & 0.115470053837925 & 0.2 \tabularnewline
15 & 1.45 & 0.173205080756888 & 0.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70431&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]1.15[/C][C]0.0577350269189625[/C][C]0.0999999999999999[/C][/ROW]
[ROW][C]2[/C][C]1.55[/C][C]0.173205080756888[/C][C]0.4[/C][/ROW]
[ROW][C]3[/C][C]1.475[/C][C]0.095742710775634[/C][C]0.2[/C][/ROW]
[ROW][C]4[/C][C]1.425[/C][C]0.05[/C][C]0.1[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.115470053837925[/C][C]0.2[/C][/ROW]
[ROW][C]6[/C][C]1.05[/C][C]0.191485421551268[/C][C]0.4[/C][/ROW]
[ROW][C]7[/C][C]1.225[/C][C]0.206155281280883[/C][C]0.4[/C][/ROW]
[ROW][C]8[/C][C]1.375[/C][C]0.330403793359983[/C][C]0.8[/C][/ROW]
[ROW][C]9[/C][C]1.5[/C][C]0.0816496580927727[/C][C]0.2[/C][/ROW]
[ROW][C]10[/C][C]1.575[/C][C]0.125830573921179[/C][C]0.3[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]0.182574185835055[/C][C]0.4[/C][/ROW]
[ROW][C]12[/C][C]2.625[/C][C]0.170782512765993[/C][C]0.4[/C][/ROW]
[ROW][C]13[/C][C]2.625[/C][C]0.309569593683445[/C][C]0.7[/C][/ROW]
[ROW][C]14[/C][C]2.1[/C][C]0.115470053837925[/C][C]0.2[/C][/ROW]
[ROW][C]15[/C][C]1.45[/C][C]0.173205080756888[/C][C]0.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70431&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70431&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.150.05773502691896250.0999999999999999
21.550.1732050807568880.4
31.4750.0957427107756340.2
41.4250.050.1
510.1154700538379250.2
61.050.1914854215512680.4
71.2250.2061552812808830.4
81.3750.3304037933599830.8
91.50.08164965809277270.2
101.5750.1258305739211790.3
1120.1825741858350550.4
122.6250.1707825127659930.4
132.6250.3095695936834450.7
142.10.1154700538379250.2
151.450.1732050807568880.4






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0773276720242826
beta0.0505435832957746
S.D.0.0421132044325431
T-STAT1.20018374229240
p-value0.251482873849816

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0773276720242826 \tabularnewline
beta & 0.0505435832957746 \tabularnewline
S.D. & 0.0421132044325431 \tabularnewline
T-STAT & 1.20018374229240 \tabularnewline
p-value & 0.251482873849816 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70431&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0773276720242826[/C][/ROW]
[ROW][C]beta[/C][C]0.0505435832957746[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0421132044325431[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.20018374229240[/C][/ROW]
[ROW][C]p-value[/C][C]0.251482873849816[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70431&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70431&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0773276720242826
beta0.0505435832957746
S.D.0.0421132044325431
T-STAT1.20018374229240
p-value0.251482873849816






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.20793800567404
beta0.546141832042808
S.D.0.488432442981228
T-STAT1.11815224375625
p-value0.283739406778742
Lambda0.453858167957192

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.20793800567404 \tabularnewline
beta & 0.546141832042808 \tabularnewline
S.D. & 0.488432442981228 \tabularnewline
T-STAT & 1.11815224375625 \tabularnewline
p-value & 0.283739406778742 \tabularnewline
Lambda & 0.453858167957192 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70431&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.20793800567404[/C][/ROW]
[ROW][C]beta[/C][C]0.546141832042808[/C][/ROW]
[ROW][C]S.D.[/C][C]0.488432442981228[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.11815224375625[/C][/ROW]
[ROW][C]p-value[/C][C]0.283739406778742[/C][/ROW]
[ROW][C]Lambda[/C][C]0.453858167957192[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70431&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70431&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.20793800567404
beta0.546141832042808
S.D.0.488432442981228
T-STAT1.11815224375625
p-value0.283739406778742
Lambda0.453858167957192


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')