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Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Thu, 12 Mar 2015 15:56:15 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Mar/12/t1426176132k75749gnqbwj84g.htm/, Retrieved Fri, 17 May 2024 14:01:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278301, Retrieved Fri, 17 May 2024 14:01:45 +0000

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Standard Deviation-Mean Plot] [] [2015-03-12 15:56:15] [36d9fcfacb97c24df6a506fb08c7a09a] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278301&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278301&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278301&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	603.515	8.16794232461159	18.0599999999999
2	619.84	5.0292092275571	11.12
3	631.405	5.83424451757977	12.9000000000001
4	647.8625	12.2700041675921	27.13
5	667.475	1.32966502958796	2.94000000000005
6	667.5275	4.0839711623058	9.02999999999997
7	677.06	4.9930278662078	11.0400000000001
8	687.58	4.05231247112511	8.95999999999992

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 603.515 & 8.16794232461159 & 18.0599999999999 \tabularnewline
2 & 619.84 & 5.0292092275571 & 11.12 \tabularnewline
3 & 631.405 & 5.83424451757977 & 12.9000000000001 \tabularnewline
4 & 647.8625 & 12.2700041675921 & 27.13 \tabularnewline
5 & 667.475 & 1.32966502958796 & 2.94000000000005 \tabularnewline
6 & 667.5275 & 4.0839711623058 & 9.02999999999997 \tabularnewline
7 & 677.06 & 4.9930278662078 & 11.0400000000001 \tabularnewline
8 & 687.58 & 4.05231247112511 & 8.95999999999992 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278301&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]603.515[/C][C]8.16794232461159[/C][C]18.0599999999999[/C][/ROW]
[ROW][C]2[/C][C]619.84[/C][C]5.0292092275571[/C][C]11.12[/C][/ROW]
[ROW][C]3[/C][C]631.405[/C][C]5.83424451757977[/C][C]12.9000000000001[/C][/ROW]
[ROW][C]4[/C][C]647.8625[/C][C]12.2700041675921[/C][C]27.13[/C][/ROW]
[ROW][C]5[/C][C]667.475[/C][C]1.32966502958796[/C][C]2.94000000000005[/C][/ROW]
[ROW][C]6[/C][C]667.5275[/C][C]4.0839711623058[/C][C]9.02999999999997[/C][/ROW]
[ROW][C]7[/C][C]677.06[/C][C]4.9930278662078[/C][C]11.0400000000001[/C][/ROW]
[ROW][C]8[/C][C]687.58[/C][C]4.05231247112511[/C][C]8.95999999999992[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278301&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278301&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
Section	Mean	Standard Deviation	Range
1	603.515	8.16794232461159	18.0599999999999
2	619.84	5.0292092275571	11.12
3	631.405	5.83424451757977	12.9000000000001
4	647.8625	12.2700041675921	27.13
5	667.475	1.32966502958796	2.94000000000005
6	667.5275	4.0839711623058	9.02999999999997
7	677.06	4.9930278662078	11.0400000000001
8	687.58	4.05231247112511	8.95999999999992

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	36.9667555209422
beta	-0.0480509292396621
S.D.	0.0403632853430852
T-STAT	-1.19046130242453
p-value	0.27882477015011

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 36.9667555209422 \tabularnewline
beta & -0.0480509292396621 \tabularnewline
S.D. & 0.0403632853430852 \tabularnewline
T-STAT & -1.19046130242453 \tabularnewline
p-value & 0.27882477015011 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278301&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]36.9667555209422[/C][/ROW]
[ROW][C]beta[/C][C]-0.0480509292396621[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0403632853430852[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.19046130242453[/C][/ROW]
[ROW][C]p-value[/C][C]0.27882477015011[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278301&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278301&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)
alpha	36.9667555209422
beta	-0.0480509292396621
S.D.	0.0403632853430852
T-STAT	-1.19046130242453
p-value	0.27882477015011

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	43.7240681151346
beta	-6.50636192085807
S.D.	5.05535358639867
T-STAT	-1.28702410418201
p-value	0.245504528738895
Lambda	7.50636192085807

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 43.7240681151346 \tabularnewline
beta & -6.50636192085807 \tabularnewline
S.D. & 5.05535358639867 \tabularnewline
T-STAT & -1.28702410418201 \tabularnewline
p-value & 0.245504528738895 \tabularnewline
Lambda & 7.50636192085807 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278301&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]43.7240681151346[/C][/ROW]
[ROW][C]beta[/C][C]-6.50636192085807[/C][/ROW]
[ROW][C]S.D.[/C][C]5.05535358639867[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.28702410418201[/C][/ROW]
[ROW][C]p-value[/C][C]0.245504528738895[/C][/ROW]
[ROW][C]Lambda[/C][C]7.50636192085807[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278301&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278301&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)
alpha	43.7240681151346
beta	-6.50636192085807
S.D.	5.05535358639867
T-STAT	-1.28702410418201
p-value	0.245504528738895
Lambda	7.50636192085807

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code