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Description of Statistical Computation

Author's title

Vooruitzicht prijs kleding – Standard Deviation – Mean Plot - Matthias Spil...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 19 May 2008 15:50:32 -0600
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/May/19/t12112338813pwtt0sm3mi2s3l.htm/, Retrieved Mon, 13 May 2024 20:30:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12941, Retrieved Mon, 13 May 2024 20:30:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171

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] [Vooruitzicht prij...] [2008-05-19 21:50:32] [314f9a525820ae2bc37b608258bd4c0b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8
5
2
5
-4
-4
-1
5
16
5
11
16
22
12
8
4
17
5
11
9
4
7
-5
9
11
11
-4
-7
9
-3
14
11
8
-14
-8
-2
15
-8
-4
-17
-13
0
9
-7
-14
-21
-10
-1
7
-14
-12
-16
-15
-15
-24
-14
-8
-14
-13
0
-6
-37
-12
-36
-32
-18
-22
-13
-17
-18
-19
-24
-14
-3
-6
-25
-19
-11
-13
-11
-22
-10
-4
5
-8
-7
5
-13
-15
3
3
7
16
16
18
10

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12941&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12941&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12941&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
15.333333333333336.6923746747980920
28.583333333333336.8152013687762527
32.166666666666679.4660477817334428
4-5.9166666666666710.492060490358136
5-11.58.028358826967431
6-21.16666666666679.6279265523252631
7-11.08333333333338.4687482528232630
82.9166666666666711.413375991140933

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5.33333333333333 & 6.69237467479809 & 20 \tabularnewline
2 & 8.58333333333333 & 6.81520136877625 & 27 \tabularnewline
3 & 2.16666666666667 & 9.46604778173344 & 28 \tabularnewline
4 & -5.91666666666667 & 10.4920604903581 & 36 \tabularnewline
5 & -11.5 & 8.0283588269674 & 31 \tabularnewline
6 & -21.1666666666667 & 9.62792655232526 & 31 \tabularnewline
7 & -11.0833333333333 & 8.46874825282326 & 30 \tabularnewline
8 & 2.91666666666667 & 11.4133759911409 & 33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12941&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]5.33333333333333[/C][C]6.69237467479809[/C][C]20[/C][/ROW]
[ROW][C]2[/C][C]8.58333333333333[/C][C]6.81520136877625[/C][C]27[/C][/ROW]
[ROW][C]3[/C][C]2.16666666666667[/C][C]9.46604778173344[/C][C]28[/C][/ROW]
[ROW][C]4[/C][C]-5.91666666666667[/C][C]10.4920604903581[/C][C]36[/C][/ROW]
[ROW][C]5[/C][C]-11.5[/C][C]8.0283588269674[/C][C]31[/C][/ROW]
[ROW][C]6[/C][C]-21.1666666666667[/C][C]9.62792655232526[/C][C]31[/C][/ROW]
[ROW][C]7[/C][C]-11.0833333333333[/C][C]8.46874825282326[/C][C]30[/C][/ROW]
[ROW][C]8[/C][C]2.91666666666667[/C][C]11.4133759911409[/C][C]33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12941&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12941&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
15.333333333333336.6923746747980920
28.583333333333336.8152013687762527
32.166666666666679.4660477817334428
4-5.9166666666666710.492060490358136
5-11.58.028358826967431
6-21.16666666666679.6279265523252631
7-11.08333333333338.4687482528232630
82.9166666666666711.413375991140933






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.70941234775638
beta-0.04333027685451
S.D.0.064697047176601
T-STAT-0.66974118210114
p-value0.527940901715342

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.70941234775638 \tabularnewline
beta & -0.04333027685451 \tabularnewline
S.D. & 0.064697047176601 \tabularnewline
T-STAT & -0.66974118210114 \tabularnewline
p-value & 0.527940901715342 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12941&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.70941234775638[/C][/ROW]
[ROW][C]beta[/C][C]-0.04333027685451[/C][/ROW]
[ROW][C]S.D.[/C][C]0.064697047176601[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.66974118210114[/C][/ROW]
[ROW][C]p-value[/C][C]0.527940901715342[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12941&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12941&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)
alpha8.70941234775638
beta-0.04333027685451
S.D.0.064697047176601
T-STAT-0.66974118210114
p-value0.527940901715342






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.61731961052740
beta-0.347010294825143
S.D.0.171077663722388
T-STAT-2.02837873322987
p-value0.179695760256021
Lambda1.34701029482514

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.61731961052740 \tabularnewline
beta & -0.347010294825143 \tabularnewline
S.D. & 0.171077663722388 \tabularnewline
T-STAT & -2.02837873322987 \tabularnewline
p-value & 0.179695760256021 \tabularnewline
Lambda & 1.34701029482514 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12941&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.61731961052740[/C][/ROW]
[ROW][C]beta[/C][C]-0.347010294825143[/C][/ROW]
[ROW][C]S.D.[/C][C]0.171077663722388[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.02837873322987[/C][/ROW]
[ROW][C]p-value[/C][C]0.179695760256021[/C][/ROW]
[ROW][C]Lambda[/C][C]1.34701029482514[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12941&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12941&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)
alpha2.61731961052740
beta-0.347010294825143
S.D.0.171077663722388
T-STAT-2.02837873322987
p-value0.179695760256021
Lambda1.34701029482514


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')