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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 21 Jan 2008 05:35:12 -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/2008/Jan/21/t1200918729rhxdsfk92m81ox8.htm/, Retrieved Wed, 15 May 2024 02:49:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=8036, Retrieved Wed, 15 May 2024 02:49:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact256
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [werkloosheid stan...] [2008-01-21 12:35:12] [3154ba3796f78378b41be206e997b36e] [Current]
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Dataseries X:
7,3
7,4
7,6
7,7
7,8
7,7
7,8
7,9
7,8
8,0
8,1
8,2
8,2
8,3
8,3
8,3
8,3
8,5
8,5
8,5
8,5
8,5
8,5
8,4
8,4
8,5
8,4
8,4
8,3
8,5
8,5
8,4
8,5
8,5
8,5
8,8
8,8
8,7
7,9
7,8
7,7
8,4
8,4
8,4
8,6
8,5
8,5
8,1
8,1
8,1
8,0
7,9
7,9
8,1
8,1
8,1
8,0
8,0
8,0
7,5
7,5




Summary of compuational 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 compuational 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=8036&T=0

[TABLE]
[ROW][C]Summary of compuational 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=8036&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8036&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 compuational 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
17.7750.2632834628649920.9
28.40.1128152149635530.300000000000001
38.4750.1215431087010990.5
48.316666666666670.3588702812826371.1
57.983333333333330.1696699112626590.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.775 & 0.263283462864992 & 0.9 \tabularnewline
2 & 8.4 & 0.112815214963553 & 0.300000000000001 \tabularnewline
3 & 8.475 & 0.121543108701099 & 0.5 \tabularnewline
4 & 8.31666666666667 & 0.358870281282637 & 1.1 \tabularnewline
5 & 7.98333333333333 & 0.169669911262659 & 0.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8036&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]7.775[/C][C]0.263283462864992[/C][C]0.9[/C][/ROW]
[ROW][C]2[/C][C]8.4[/C][C]0.112815214963553[/C][C]0.300000000000001[/C][/ROW]
[ROW][C]3[/C][C]8.475[/C][C]0.121543108701099[/C][C]0.5[/C][/ROW]
[ROW][C]4[/C][C]8.31666666666667[/C][C]0.358870281282637[/C][C]1.1[/C][/ROW]
[ROW][C]5[/C][C]7.98333333333333[/C][C]0.169669911262659[/C][C]0.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=8036&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8036&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
17.7750.2632834628649920.9
28.40.1128152149635530.300000000000001
38.4750.1215431087010990.5
48.316666666666670.3588702812826371.1
57.983333333333330.1696699112626590.6







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.13708132270947
beta-0.113778379352195
S.D.0.191431371278299
T-STAT-0.594355975159301
p-value0.594115386675623

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.13708132270947 \tabularnewline
beta & -0.113778379352195 \tabularnewline
S.D. & 0.191431371278299 \tabularnewline
T-STAT & -0.594355975159301 \tabularnewline
p-value & 0.594115386675623 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8036&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.13708132270947[/C][/ROW]
[ROW][C]beta[/C][C]-0.113778379352195[/C][/ROW]
[ROW][C]S.D.[/C][C]0.191431371278299[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.594355975159301[/C][/ROW]
[ROW][C]p-value[/C][C]0.594115386675623[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=8036&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8036&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)
alpha1.13708132270947
beta-0.113778379352195
S.D.0.191431371278299
T-STAT-0.594355975159301
p-value0.594115386675623







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha11.1006370425399
beta-6.08129789347574
S.D.6.99188734049376
T-STAT-0.869764857087397
p-value0.448428602891101
Lambda7.08129789347574

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 11.1006370425399 \tabularnewline
beta & -6.08129789347574 \tabularnewline
S.D. & 6.99188734049376 \tabularnewline
T-STAT & -0.869764857087397 \tabularnewline
p-value & 0.448428602891101 \tabularnewline
Lambda & 7.08129789347574 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8036&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]11.1006370425399[/C][/ROW]
[ROW][C]beta[/C][C]-6.08129789347574[/C][/ROW]
[ROW][C]S.D.[/C][C]6.99188734049376[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.869764857087397[/C][/ROW]
[ROW][C]p-value[/C][C]0.448428602891101[/C][/ROW]
[ROW][C]Lambda[/C][C]7.08129789347574[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=8036&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8036&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)
alpha11.1006370425399
beta-6.08129789347574
S.D.6.99188734049376
T-STAT-0.869764857087397
p-value0.448428602891101
Lambda7.08129789347574



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')