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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 23 Nov 2007 14:28:43 -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/2007/Nov/23/t1195852818bfuru3bkgz1k48b.htm/, Retrieved Mon, 29 Apr 2024 03:55:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6251, Retrieved Mon, 29 Apr 2024 03:55:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact204

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] [WS10Q1FINSIT] [2007-11-23 21:28:43] [e0964b90cb3acfe235da067e79729c23] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
22
27
24
24
22
23
25
23
21
21
22
20
22
22
20
21
20
21
21
21
19
21
21
22
19
24
22
22
22
24
22
23
24
21
20
22
23
23
22
20
21
21
20
20
17
18
19
19
20
21
20
21
19
22
20
18
16
17
18
19

Tables (Output of Computation)





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=6251&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=6251&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6251&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 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
122.83333333333331.946247360403818
220.91666666666670.900336637378521
322.08333333333331.564279289951034
420.251.864744681524183
519.251.764549903980153

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 22.8333333333333 & 1.94624736040381 & 8 \tabularnewline
2 & 20.9166666666667 & 0.90033663737852 & 1 \tabularnewline
3 & 22.0833333333333 & 1.56427928995103 & 4 \tabularnewline
4 & 20.25 & 1.86474468152418 & 3 \tabularnewline
5 & 19.25 & 1.76454990398015 & 3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6251&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]22.8333333333333[/C][C]1.94624736040381[/C][C]8[/C][/ROW]
[ROW][C]2[/C][C]20.9166666666667[/C][C]0.90033663737852[/C][C]1[/C][/ROW]
[ROW][C]3[/C][C]22.0833333333333[/C][C]1.56427928995103[/C][C]4[/C][/ROW]
[ROW][C]4[/C][C]20.25[/C][C]1.86474468152418[/C][C]3[/C][/ROW]
[ROW][C]5[/C][C]19.25[/C][C]1.76454990398015[/C][C]3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6251&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6251&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
122.83333333333331.946247360403818
220.91666666666670.900336637378521
322.08333333333331.564279289951034
420.251.864744681524183
519.251.764549903980153






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.18072894994567
beta0.0202833524383797
S.D.0.169766532097035
T-STAT0.119477921754249
p-value0.912448583479707

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.18072894994567 \tabularnewline
beta & 0.0202833524383797 \tabularnewline
S.D. & 0.169766532097035 \tabularnewline
T-STAT & 0.119477921754249 \tabularnewline
p-value & 0.912448583479707 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6251&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.18072894994567[/C][/ROW]
[ROW][C]beta[/C][C]0.0202833524383797[/C][/ROW]
[ROW][C]S.D.[/C][C]0.169766532097035[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.119477921754249[/C][/ROW]
[ROW][C]p-value[/C][C]0.912448583479707[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6251&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6251&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)
alpha1.18072894994567
beta0.0202833524383797
S.D.0.169766532097035
T-STAT0.119477921754249
p-value0.912448583479707






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.164958686446477
beta0.198575348127228
S.D.2.68004278574215
T-STAT0.0740940962523623
p-value0.945599384657781
Lambda0.801424651872772

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.164958686446477 \tabularnewline
beta & 0.198575348127228 \tabularnewline
S.D. & 2.68004278574215 \tabularnewline
T-STAT & 0.0740940962523623 \tabularnewline
p-value & 0.945599384657781 \tabularnewline
Lambda & 0.801424651872772 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6251&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.164958686446477[/C][/ROW]
[ROW][C]beta[/C][C]0.198575348127228[/C][/ROW]
[ROW][C]S.D.[/C][C]2.68004278574215[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0740940962523623[/C][/ROW]
[ROW][C]p-value[/C][C]0.945599384657781[/C][/ROW]
[ROW][C]Lambda[/C][C]0.801424651872772[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6251&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6251&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-0.164958686446477
beta0.198575348127228
S.D.2.68004278574215
T-STAT0.0740940962523623
p-value0.945599384657781
Lambda0.801424651872772


Figures (Output of Computation)

Input Parameters & R Code

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')