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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Sat, 25 Dec 2010 13:42:45 +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/2010/Dec/25/t12932845399wtq7qyh0j4nbzc.htm/, Retrieved Sun, 28 Apr 2024 21:38:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115388, Retrieved Sun, 28 Apr 2024 21:38:22 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

140

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

-     [Variance Reduction Matrix] [] [2010-12-15 15:38:06] [234dae34fc2a42f724a2786a39cb083b]
- RM D    [Standard Deviation-Mean Plot] [] [2010-12-25 13:42:45] [cf84dc108eae081aed36d3d050e63ee7] [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	2 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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115388&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115388&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115388&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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	133.333333333333	16.1882860754499	45
2	126.5	14.3178210632764	39
3	110.583333333333	11.7043762859208	37
4	103.25	11.6706703087074	36
5	116.75	12.8425783307644	38

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 133.333333333333 & 16.1882860754499 & 45 \tabularnewline
2 & 126.5 & 14.3178210632764 & 39 \tabularnewline
3 & 110.583333333333 & 11.7043762859208 & 37 \tabularnewline
4 & 103.25 & 11.6706703087074 & 36 \tabularnewline
5 & 116.75 & 12.8425783307644 & 38 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115388&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]133.333333333333[/C][C]16.1882860754499[/C][C]45[/C][/ROW]
[ROW][C]2[/C][C]126.5[/C][C]14.3178210632764[/C][C]39[/C][/ROW]
[ROW][C]3[/C][C]110.583333333333[/C][C]11.7043762859208[/C][C]37[/C][/ROW]
[ROW][C]4[/C][C]103.25[/C][C]11.6706703087074[/C][C]36[/C][/ROW]
[ROW][C]5[/C][C]116.75[/C][C]12.8425783307644[/C][C]38[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115388&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115388&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	133.333333333333	16.1882860754499	45
2	126.5	14.3178210632764	39
3	110.583333333333	11.7043762859208	37
4	103.25	11.6706703087074	36
5	116.75	12.8425783307644	38

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-4.80229424979788
beta	0.153679949154171
S.D.	0.0244817535688571
T-STAT	6.27732603883672
p-value	0.00816257808420495

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.80229424979788 \tabularnewline
beta & 0.153679949154171 \tabularnewline
S.D. & 0.0244817535688571 \tabularnewline
T-STAT & 6.27732603883672 \tabularnewline
p-value & 0.00816257808420495 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115388&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.80229424979788[/C][/ROW]
[ROW][C]beta[/C][C]0.153679949154171[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0244817535688571[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.27732603883672[/C][/ROW]
[ROW][C]p-value[/C][C]0.00816257808420495[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115388&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115388&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	-4.80229424979788
beta	0.153679949154171
S.D.	0.0244817535688571
T-STAT	6.27732603883672
p-value	0.00816257808420495

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.70055513591466
beta	1.31810319270044
S.D.	0.21600033620009
T-STAT	6.10232009768459
p-value	0.00884130821888862
Lambda	-0.318103192700439

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.70055513591466 \tabularnewline
beta & 1.31810319270044 \tabularnewline
S.D. & 0.21600033620009 \tabularnewline
T-STAT & 6.10232009768459 \tabularnewline
p-value & 0.00884130821888862 \tabularnewline
Lambda & -0.318103192700439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115388&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.70055513591466[/C][/ROW]
[ROW][C]beta[/C][C]1.31810319270044[/C][/ROW]
[ROW][C]S.D.[/C][C]0.21600033620009[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.10232009768459[/C][/ROW]
[ROW][C]p-value[/C][C]0.00884130821888862[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.318103192700439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115388&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115388&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	-3.70055513591466
beta	1.31810319270044
S.D.	0.21600033620009
T-STAT	6.10232009768459
p-value	0.00884130821888862
Lambda	-0.318103192700439

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

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code