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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

Mon, 30 Nov 2015 13:51:07 +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/Nov/30/t14488915563xnq0z6bkdhzrsj.htm/, Retrieved Tue, 14 May 2024 06:50:09 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284591, Retrieved Tue, 14 May 2024 06:50:09 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

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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] [Standaarddeviatie] [2015-11-30 13:51:07] [76c30f62b7052b57088120e90a652e05] [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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284591&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284591&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284591&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	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2043.83333333333	246.699977275797	768
2	2259.16666666667	815.140906205606	2254
3	1968.66666666667	195.328782654614	563
4	2064.41666666667	268.185640702085	838
5	1987.66666666667	161.818266939031	464
6	2116.08333333333	826.496049414012	2345

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2043.83333333333 & 246.699977275797 & 768 \tabularnewline
2 & 2259.16666666667 & 815.140906205606 & 2254 \tabularnewline
3 & 1968.66666666667 & 195.328782654614 & 563 \tabularnewline
4 & 2064.41666666667 & 268.185640702085 & 838 \tabularnewline
5 & 1987.66666666667 & 161.818266939031 & 464 \tabularnewline
6 & 2116.08333333333 & 826.496049414012 & 2345 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284591&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]2043.83333333333[/C][C]246.699977275797[/C][C]768[/C][/ROW]
[ROW][C]2[/C][C]2259.16666666667[/C][C]815.140906205606[/C][C]2254[/C][/ROW]
[ROW][C]3[/C][C]1968.66666666667[/C][C]195.328782654614[/C][C]563[/C][/ROW]
[ROW][C]4[/C][C]2064.41666666667[/C][C]268.185640702085[/C][C]838[/C][/ROW]
[ROW][C]5[/C][C]1987.66666666667[/C][C]161.818266939031[/C][C]464[/C][/ROW]
[ROW][C]6[/C][C]2116.08333333333[/C][C]826.496049414012[/C][C]2345[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284591&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284591&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	2043.83333333333	246.699977275797	768
2	2259.16666666667	815.140906205606	2254
3	1968.66666666667	195.328782654614	563
4	2064.41666666667	268.185640702085	838
5	1987.66666666667	161.818266939031	464
6	2116.08333333333	826.496049414012	2345

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-4909.51080703257
beta	2.57002916427497
S.D.	0.747589446114744
T-STAT	3.43775474310335
p-value	0.026347827308183

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4909.51080703257 \tabularnewline
beta & 2.57002916427497 \tabularnewline
S.D. & 0.747589446114744 \tabularnewline
T-STAT & 3.43775474310335 \tabularnewline
p-value & 0.026347827308183 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284591&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4909.51080703257[/C][/ROW]
[ROW][C]beta[/C][C]2.57002916427497[/C][/ROW]
[ROW][C]S.D.[/C][C]0.747589446114744[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.43775474310335[/C][/ROW]
[ROW][C]p-value[/C][C]0.026347827308183[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284591&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284591&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	-4909.51080703257
beta	2.57002916427497
S.D.	0.747589446114744
T-STAT	3.43775474310335
p-value	0.026347827308183

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-91.4273678262356
beta	12.7347956219718
S.D.	3.31572978399499
T-STAT	3.84072178723446
p-value	0.018448159383395
Lambda	-11.7347956219718

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -91.4273678262356 \tabularnewline
beta & 12.7347956219718 \tabularnewline
S.D. & 3.31572978399499 \tabularnewline
T-STAT & 3.84072178723446 \tabularnewline
p-value & 0.018448159383395 \tabularnewline
Lambda & -11.7347956219718 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284591&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-91.4273678262356[/C][/ROW]
[ROW][C]beta[/C][C]12.7347956219718[/C][/ROW]
[ROW][C]S.D.[/C][C]3.31572978399499[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.84072178723446[/C][/ROW]
[ROW][C]p-value[/C][C]0.018448159383395[/C][/ROW]
[ROW][C]Lambda[/C][C]-11.7347956219718[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284591&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284591&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	-91.4273678262356
beta	12.7347956219718
S.D.	3.31572978399499
T-STAT	3.84072178723446
p-value	0.018448159383395
Lambda	-11.7347956219718

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