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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 computationTue, 26 Apr 2016 16:54:21 +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/2016/Apr/26/t1461686127x52o067pfcu5ase.htm/, Retrieved Fri, 03 May 2024 19:04:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294906, Retrieved Fri, 03 May 2024 19:04:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59

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] [] [2016-04-26 15:54:21] [808bf237864283e5d6c581b9d5be65c1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4
7
9
6
9
13
18
8
15
4
8
14
8
3
5
6
12
7
3
11
6
9
6
10
10
6
13
10
9
15
8
12
13
9
6
7
8
7
6
8
3
7
8
8
7
12
7
5
9
9
8
11
9
8
9
11
8
9
9
5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294906&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294906&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294906&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
19.583333333333334.4611114255883814
27.166666666666672.918073253904289
39.833333333333332.918073253904289
47.166666666666672.124888588879789
58.751.544785951633316

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9.58333333333333 & 4.46111142558838 & 14 \tabularnewline
2 & 7.16666666666667 & 2.91807325390428 & 9 \tabularnewline
3 & 9.83333333333333 & 2.91807325390428 & 9 \tabularnewline
4 & 7.16666666666667 & 2.12488858887978 & 9 \tabularnewline
5 & 8.75 & 1.54478595163331 & 6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294906&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]9.58333333333333[/C][C]4.46111142558838[/C][C]14[/C][/ROW]
[ROW][C]2[/C][C]7.16666666666667[/C][C]2.91807325390428[/C][C]9[/C][/ROW]
[ROW][C]3[/C][C]9.83333333333333[/C][C]2.91807325390428[/C][C]9[/C][/ROW]
[ROW][C]4[/C][C]7.16666666666667[/C][C]2.12488858887978[/C][C]9[/C][/ROW]
[ROW][C]5[/C][C]8.75[/C][C]1.54478595163331[/C][C]6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294906&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294906&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
19.583333333333334.4611114255883814
27.166666666666672.918073253904289
39.833333333333332.918073253904289
47.166666666666672.124888588879789
58.751.544785951633316






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.2936326114317
beta0.363178718378083
S.D.0.447787574407772
T-STAT0.811051353665655
p-value0.476707458249204

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.2936326114317 \tabularnewline
beta & 0.363178718378083 \tabularnewline
S.D. & 0.447787574407772 \tabularnewline
T-STAT & 0.811051353665655 \tabularnewline
p-value & 0.476707458249204 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294906&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.2936326114317[/C][/ROW]
[ROW][C]beta[/C][C]0.363178718378083[/C][/ROW]
[ROW][C]S.D.[/C][C]0.447787574407772[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.811051353665655[/C][/ROW]
[ROW][C]p-value[/C][C]0.476707458249204[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294906&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294906&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)
alpha-0.2936326114317
beta0.363178718378083
S.D.0.447787574407772
T-STAT0.811051353665655
p-value0.476707458249204






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.881277654313456
beta0.866572620461687
S.D.1.40557956651085
T-STAT0.616523348167921
p-value0.58117549695128
Lambda0.133427379538313

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.881277654313456 \tabularnewline
beta & 0.866572620461687 \tabularnewline
S.D. & 1.40557956651085 \tabularnewline
T-STAT & 0.616523348167921 \tabularnewline
p-value & 0.58117549695128 \tabularnewline
Lambda & 0.133427379538313 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294906&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.881277654313456[/C][/ROW]
[ROW][C]beta[/C][C]0.866572620461687[/C][/ROW]
[ROW][C]S.D.[/C][C]1.40557956651085[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.616523348167921[/C][/ROW]
[ROW][C]p-value[/C][C]0.58117549695128[/C][/ROW]
[ROW][C]Lambda[/C][C]0.133427379538313[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294906&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294906&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-0.881277654313456
beta0.866572620461687
S.D.1.40557956651085
T-STAT0.616523348167921
p-value0.58117549695128
Lambda0.133427379538313


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')