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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 25 Dec 2010 10:18:44 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/25/t1293275246eorauxh4bxsjws4.htm/, Retrieved Mon, 29 Apr 2024 04:29:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115351, Retrieved Mon, 29 Apr 2024 04:29:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
-   P     [Standard Deviation-Mean Plot] [Box-Cox] [2010-12-16 08:21:58] [6a528ed37664d761abf4790b0717b23b]
-    D        [Standard Deviation-Mean Plot] [BCT] [2010-12-25 10:18:44] [fd751bc40fbbb4c72222c10190589d42] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.8
1.7
1.4
1.2
1
1.7
2.4
2
2.1
2
1.8
2.7
2.3
1.9
2
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3
2.2
2.3
2.8
2.8
2.8
2.2
2.6
2.8
2.5
2.4
2.3
1.9
1.7
2
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2
2.9
3.1
3.5
3.6
4.4
4.1
5.1
5.8
5.9
5.4
5.5
4.8
3.2

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115351&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115351&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115351&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.816666666666670.4783177592227561.7
22.458333333333330.3553700589355821.1
32.4250.3671140521319321.1
41.658333333333330.3476108935769041
54.508333333333331.062123373533443

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.81666666666667 & 0.478317759222756 & 1.7 \tabularnewline
2 & 2.45833333333333 & 0.355370058935582 & 1.1 \tabularnewline
3 & 2.425 & 0.367114052131932 & 1.1 \tabularnewline
4 & 1.65833333333333 & 0.347610893576904 & 1 \tabularnewline
5 & 4.50833333333333 & 1.06212337353344 & 3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115351&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]1.81666666666667[/C][C]0.478317759222756[/C][C]1.7[/C][/ROW]
[ROW][C]2[/C][C]2.45833333333333[/C][C]0.355370058935582[/C][C]1.1[/C][/ROW]
[ROW][C]3[/C][C]2.425[/C][C]0.367114052131932[/C][C]1.1[/C][/ROW]
[ROW][C]4[/C][C]1.65833333333333[/C][C]0.347610893576904[/C][C]1[/C][/ROW]
[ROW][C]5[/C][C]4.50833333333333[/C][C]1.06212337353344[/C][C]3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115351&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115351&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
11.816666666666670.4783177592227561.7
22.458333333333330.3553700589355821.1
32.4250.3671140521319321.1
41.658333333333330.3476108935769041
54.508333333333331.062123373533443






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.112592142496535
beta0.246644832892484
S.D.0.062148255042303
T-STAT3.96865258283757
p-value0.0285906151475686

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.112592142496535 \tabularnewline
beta & 0.246644832892484 \tabularnewline
S.D. & 0.062148255042303 \tabularnewline
T-STAT & 3.96865258283757 \tabularnewline
p-value & 0.0285906151475686 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115351&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.112592142496535[/C][/ROW]
[ROW][C]beta[/C][C]0.246644832892484[/C][/ROW]
[ROW][C]S.D.[/C][C]0.062148255042303[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.96865258283757[/C][/ROW]
[ROW][C]p-value[/C][C]0.0285906151475686[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115351&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115351&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-0.112592142496535
beta0.246644832892484
S.D.0.062148255042303
T-STAT3.96865258283757
p-value0.0285906151475686






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.63155380849455
beta0.998441118904237
S.D.0.393764841002997
T-STAT2.53562790512482
p-value0.0850040844052694
Lambda0.00155888109576252

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.63155380849455 \tabularnewline
beta & 0.998441118904237 \tabularnewline
S.D. & 0.393764841002997 \tabularnewline
T-STAT & 2.53562790512482 \tabularnewline
p-value & 0.0850040844052694 \tabularnewline
Lambda & 0.00155888109576252 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115351&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.63155380849455[/C][/ROW]
[ROW][C]beta[/C][C]0.998441118904237[/C][/ROW]
[ROW][C]S.D.[/C][C]0.393764841002997[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.53562790512482[/C][/ROW]
[ROW][C]p-value[/C][C]0.0850040844052694[/C][/ROW]
[ROW][C]Lambda[/C][C]0.00155888109576252[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115351&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115351&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-1.63155380849455
beta0.998441118904237
S.D.0.393764841002997
T-STAT2.53562790512482
p-value0.0850040844052694
Lambda0.00155888109576252


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')