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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 22 May 2015 18:38:07 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/May/22/t14323164323umuiygikihzvs5.htm/, Retrieved Fri, 03 May 2024 12:52:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279245, Retrieved Fri, 03 May 2024 12:52:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2015-05-22 17:38:07] [70e23d918d09c907c02097a361cd6415] [Current]
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Dataseries X:
3.5
4.8
6
5.9
3.6
6.8
8.7
8.4
8.1
8.9
8.7
7.8
6.3
7.5
6.8
7
8.8
8.4
7.6
7.9
7.4
8.7
8.7
8
9.4
8.5
5.8
2.8
3.3
4.8
1.8
4.8
-0.9
-6
-9
-21.1
-20.9
-23.5
-20.8
-17.3
-16.1
-13.9
-14.6
-9.2
-9.7
-7.2
-5
-8.1
-6.2
-4.8
-3.1
-1.4
0.6
-0.8
-2
0.2
-0.1
0.3
0.2
2.6
2.5
1.5
5.7
4.3
2.7
1.7
-2.2
-3.2
-0.5
-3.1
-4.8
-1.3
-1.8
-1.7
-2.8
-3.4
-4.9
-4.8
-5.4
-4.7
-6.6
-7.6
-6.8
-5.6
-5.6
-3.7
-5.1
-5.6
-4.1
-3.8
-3.1
-1.4
-2.4
-0.3
-0.3
0.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279245&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279245&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279245&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
16.766666666666671.987384454426715.4
27.758333333333330.808430953180672.5
30.358.6542159983128830.5
4-13.85833333333336.053617751294518.5
5-1.208333333333332.47660263386378.8
60.2753.2811098454915910.5
7-4.6751.918391845459965.9
8-2.941666666666672.074721595050695.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6.76666666666667 & 1.98738445442671 & 5.4 \tabularnewline
2 & 7.75833333333333 & 0.80843095318067 & 2.5 \tabularnewline
3 & 0.35 & 8.65421599831288 & 30.5 \tabularnewline
4 & -13.8583333333333 & 6.0536177512945 & 18.5 \tabularnewline
5 & -1.20833333333333 & 2.4766026338637 & 8.8 \tabularnewline
6 & 0.275 & 3.28110984549159 & 10.5 \tabularnewline
7 & -4.675 & 1.91839184545996 & 5.9 \tabularnewline
8 & -2.94166666666667 & 2.07472159505069 & 5.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279245&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]6.76666666666667[/C][C]1.98738445442671[/C][C]5.4[/C][/ROW]
[ROW][C]2[/C][C]7.75833333333333[/C][C]0.80843095318067[/C][C]2.5[/C][/ROW]
[ROW][C]3[/C][C]0.35[/C][C]8.65421599831288[/C][C]30.5[/C][/ROW]
[ROW][C]4[/C][C]-13.8583333333333[/C][C]6.0536177512945[/C][C]18.5[/C][/ROW]
[ROW][C]5[/C][C]-1.20833333333333[/C][C]2.4766026338637[/C][C]8.8[/C][/ROW]
[ROW][C]6[/C][C]0.275[/C][C]3.28110984549159[/C][C]10.5[/C][/ROW]
[ROW][C]7[/C][C]-4.675[/C][C]1.91839184545996[/C][C]5.9[/C][/ROW]
[ROW][C]8[/C][C]-2.94166666666667[/C][C]2.07472159505069[/C][C]5.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279245&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279245&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
16.766666666666671.987384454426715.4
27.758333333333330.808430953180672.5
30.358.6542159983128830.5
4-13.85833333333336.053617751294518.5
5-1.208333333333332.47660263386378.8
60.2753.2811098454915910.5
7-4.6751.918391845459965.9
8-2.941666666666672.074721595050695.7







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.25339069437009
beta-0.162922502936282
S.D.0.142925114828687
T-STAT-1.13991514459558
p-value0.29777360366018

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.25339069437009 \tabularnewline
beta & -0.162922502936282 \tabularnewline
S.D. & 0.142925114828687 \tabularnewline
T-STAT & -1.13991514459558 \tabularnewline
p-value & 0.29777360366018 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279245&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.25339069437009[/C][/ROW]
[ROW][C]beta[/C][C]-0.162922502936282[/C][/ROW]
[ROW][C]S.D.[/C][C]0.142925114828687[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.13991514459558[/C][/ROW]
[ROW][C]p-value[/C][C]0.29777360366018[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279245&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279245&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)
alpha3.25339069437009
beta-0.162922502936282
S.D.0.142925114828687
T-STAT-1.13991514459558
p-value0.29777360366018







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.13671532607857
beta-0.448448813128776
S.D.0.21633618317776
T-STAT-2.07292560375947
p-value0.173931312851083
Lambda1.44844881312878

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.13671532607857 \tabularnewline
beta & -0.448448813128776 \tabularnewline
S.D. & 0.21633618317776 \tabularnewline
T-STAT & -2.07292560375947 \tabularnewline
p-value & 0.173931312851083 \tabularnewline
Lambda & 1.44844881312878 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279245&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.13671532607857[/C][/ROW]
[ROW][C]beta[/C][C]-0.448448813128776[/C][/ROW]
[ROW][C]S.D.[/C][C]0.21633618317776[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.07292560375947[/C][/ROW]
[ROW][C]p-value[/C][C]0.173931312851083[/C][/ROW]
[ROW][C]Lambda[/C][C]1.44844881312878[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279245&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279245&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)
alpha1.13671532607857
beta-0.448448813128776
S.D.0.21633618317776
T-STAT-2.07292560375947
p-value0.173931312851083
Lambda1.44844881312878



Parameters (Session):
par1 = 0.01 ; par2 = 0.09 ; par3 = 0.01 ;
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')