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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Fri, 04 May 2012 06:22:26 -0400

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/2012/May/04/t133612718149yfolunqb1uc0h.htm/, Retrieved Fri, 03 May 2024 08:34:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166192, Retrieved Fri, 03 May 2024 08:34:47 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

164

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

-       [Standard Deviation-Mean Plot] [] [2012-05-04 10:22:26] [e9055fb3c64f4ec827f818bb591f77b7] [Current]

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Boxplots

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	'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166192&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166192&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166192&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	'AstonUniversity' @ aston.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	9500.41666666667	426.43436206703	1677
2	9774.58333333333	411.655075901113	1319
3	9968.5	374.722321435244	1369
4	10210.75	476.271336911677	1561
5	10341.25	495.905989074542	1672
6	10600.4166666667	458.828440573149	1635
7	9699.66666666667	344.354820532895	908
8	9614.33333333333	439.930641916393	1433

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9500.41666666667 & 426.43436206703 & 1677 \tabularnewline
2 & 9774.58333333333 & 411.655075901113 & 1319 \tabularnewline
3 & 9968.5 & 374.722321435244 & 1369 \tabularnewline
4 & 10210.75 & 476.271336911677 & 1561 \tabularnewline
5 & 10341.25 & 495.905989074542 & 1672 \tabularnewline
6 & 10600.4166666667 & 458.828440573149 & 1635 \tabularnewline
7 & 9699.66666666667 & 344.354820532895 & 908 \tabularnewline
8 & 9614.33333333333 & 439.930641916393 & 1433 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166192&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]9500.41666666667[/C][C]426.43436206703[/C][C]1677[/C][/ROW]
[ROW][C]2[/C][C]9774.58333333333[/C][C]411.655075901113[/C][C]1319[/C][/ROW]
[ROW][C]3[/C][C]9968.5[/C][C]374.722321435244[/C][C]1369[/C][/ROW]
[ROW][C]4[/C][C]10210.75[/C][C]476.271336911677[/C][C]1561[/C][/ROW]
[ROW][C]5[/C][C]10341.25[/C][C]495.905989074542[/C][C]1672[/C][/ROW]
[ROW][C]6[/C][C]10600.4166666667[/C][C]458.828440573149[/C][C]1635[/C][/ROW]
[ROW][C]7[/C][C]9699.66666666667[/C][C]344.354820532895[/C][C]908[/C][/ROW]
[ROW][C]8[/C][C]9614.33333333333[/C][C]439.930641916393[/C][C]1433[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166192&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166192&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	9500.41666666667	426.43436206703	1677
2	9774.58333333333	411.655075901113	1319
3	9968.5	374.722321435244	1369
4	10210.75	476.271336911677	1561
5	10341.25	495.905989074542	1672
6	10600.4166666667	458.828440573149	1635
7	9699.66666666667	344.354820532895	908
8	9614.33333333333	439.930641916393	1433

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-317.171383575838
beta	0.0748397979383838
S.D.	0.0440693395119535
T-STAT	1.69822826407653
p-value	0.140382590468228

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -317.171383575838 \tabularnewline
beta & 0.0748397979383838 \tabularnewline
S.D. & 0.0440693395119535 \tabularnewline
T-STAT & 1.69822826407653 \tabularnewline
p-value & 0.140382590468228 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166192&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-317.171383575838[/C][/ROW]
[ROW][C]beta[/C][C]0.0748397979383838[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0440693395119535[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.69822826407653[/C][/ROW]
[ROW][C]p-value[/C][C]0.140382590468228[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166192&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166192&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	-317.171383575838
beta	0.0748397979383838
S.D.	0.0440693395119535
T-STAT	1.69822826407653
p-value	0.140382590468228

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-9.88864712277934
beta	1.73174597592151
S.D.	1.08390278433417
T-STAT	1.59769492333696
p-value	0.161225510599667
Lambda	-0.731745975921507

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.88864712277934 \tabularnewline
beta & 1.73174597592151 \tabularnewline
S.D. & 1.08390278433417 \tabularnewline
T-STAT & 1.59769492333696 \tabularnewline
p-value & 0.161225510599667 \tabularnewline
Lambda & -0.731745975921507 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166192&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.88864712277934[/C][/ROW]
[ROW][C]beta[/C][C]1.73174597592151[/C][/ROW]
[ROW][C]S.D.[/C][C]1.08390278433417[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.59769492333696[/C][/ROW]
[ROW][C]p-value[/C][C]0.161225510599667[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.731745975921507[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166192&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166192&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	-9.88864712277934
beta	1.73174597592151
S.D.	1.08390278433417
T-STAT	1.59769492333696
p-value	0.161225510599667
Lambda	-0.731745975921507

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