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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, 29 Nov 2013 11:57:33 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/29/t1385744294y2uan6fo3b97xl1.htm/, Retrieved Mon, 06 May 2024 01:21:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=229569, Retrieved Mon, 06 May 2024 01:21:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75

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] [] [2013-11-29 16:57:33] [ba1aac5cc07b687ee7a9bc35c791a1eb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2.7
3
-0.3
1.1
1.7
1.6
3
3.3
6.7
5.6
6
4.8
5.9
4.3
3.7
5.6
1.7
3.2
3.6
1.7
0.5
2.1
1.5
2.7
1.4
1.2
2.3
1.6
4.7
3.5
4.4
3.9
3.5
3
1.6
2.2
4.1
4.3
3.5
1.8
0.6
-0.4
-2.5
-1.6
-1.9
-1.6
-0.7
-1.1
0.3
1.3
3.3
2.4
2
3.9
4.2
4.9
5.8
4.8
4.4
5.3
2.1
2
-0.9
0.1
-0.5
-0.1
0.7
-0.4
-1.5
-0.3
1
0.4
0.3
1.8
3
2.2
3.4
3.4
3.1
4.5
4.6
5.7
4.3
4.5

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'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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229569&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229569&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229569&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'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13.266666666666672.135557552632587
23.041666666666671.665401034604165.4
32.7751.221120945539943.5
40.3752.455096739438186.8
53.551.710661753931395.5
60.2166666666666671.090315495069153.6
73.41.471548349682935.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3.26666666666667 & 2.13555755263258 & 7 \tabularnewline
2 & 3.04166666666667 & 1.66540103460416 & 5.4 \tabularnewline
3 & 2.775 & 1.22112094553994 & 3.5 \tabularnewline
4 & 0.375 & 2.45509673943818 & 6.8 \tabularnewline
5 & 3.55 & 1.71066175393139 & 5.5 \tabularnewline
6 & 0.216666666666667 & 1.09031549506915 & 3.6 \tabularnewline
7 & 3.4 & 1.47154834968293 & 5.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229569&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]3.26666666666667[/C][C]2.13555755263258[/C][C]7[/C][/ROW]
[ROW][C]2[/C][C]3.04166666666667[/C][C]1.66540103460416[/C][C]5.4[/C][/ROW]
[ROW][C]3[/C][C]2.775[/C][C]1.22112094553994[/C][C]3.5[/C][/ROW]
[ROW][C]4[/C][C]0.375[/C][C]2.45509673943818[/C][C]6.8[/C][/ROW]
[ROW][C]5[/C][C]3.55[/C][C]1.71066175393139[/C][C]5.5[/C][/ROW]
[ROW][C]6[/C][C]0.216666666666667[/C][C]1.09031549506915[/C][C]3.6[/C][/ROW]
[ROW][C]7[/C][C]3.4[/C][C]1.47154834968293[/C][C]5.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229569&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229569&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
13.266666666666672.135557552632587
23.041666666666671.665401034604165.4
32.7751.221120945539943.5
40.3752.455096739438186.8
53.551.710661753931395.5
60.2166666666666671.090315495069153.6
73.41.471548349682935.4






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.72458141523688
beta-0.0193905585419431
S.D.0.150078370438521
T-STAT-0.129202885700883
p-value0.902233632969872

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.72458141523688 \tabularnewline
beta & -0.0193905585419431 \tabularnewline
S.D. & 0.150078370438521 \tabularnewline
T-STAT & -0.129202885700883 \tabularnewline
p-value & 0.902233632969872 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229569&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.72458141523688[/C][/ROW]
[ROW][C]beta[/C][C]-0.0193905585419431[/C][/ROW]
[ROW][C]S.D.[/C][C]0.150078370438521[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.129202885700883[/C][/ROW]
[ROW][C]p-value[/C][C]0.902233632969872[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229569&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229569&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)
alpha1.72458141523688
beta-0.0193905585419431
S.D.0.150078370438521
T-STAT-0.129202885700883
p-value0.902233632969872






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.470261257763582
beta0.0256458958988231
S.D.0.107530060320866
T-STAT0.238499781570815
p-value0.820959984084633
Lambda0.974354104101177

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.470261257763582 \tabularnewline
beta & 0.0256458958988231 \tabularnewline
S.D. & 0.107530060320866 \tabularnewline
T-STAT & 0.238499781570815 \tabularnewline
p-value & 0.820959984084633 \tabularnewline
Lambda & 0.974354104101177 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229569&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.470261257763582[/C][/ROW]
[ROW][C]beta[/C][C]0.0256458958988231[/C][/ROW]
[ROW][C]S.D.[/C][C]0.107530060320866[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.238499781570815[/C][/ROW]
[ROW][C]p-value[/C][C]0.820959984084633[/C][/ROW]
[ROW][C]Lambda[/C][C]0.974354104101177[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229569&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229569&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)
alpha0.470261257763582
beta0.0256458958988231
S.D.0.107530060320866
T-STAT0.238499781570815
p-value0.820959984084633
Lambda0.974354104101177


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')