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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 Jan 2013 10:11:27 -0500

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/2013/Jan/04/t1357312298q7vmx8jzi80nwdx.htm/, Retrieved Sat, 27 Apr 2024 16:32:21 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=205008, Retrieved Sat, 27 Apr 2024 16:32:21 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

173

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

-       [Standard Deviation-Mean Plot] [] [2013-01-04 15:11:27] [0dfc9291120e0017631158d00b067a5a] [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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205008&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205008&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205008&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	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2419.75	281.390742562722	681
2	2555.41666666667	80.2399337593007	209
3	2135.16666666667	298.162808891486	843
4	3126.58333333333	740.937055151765	1995
5	4411	197.945355177543	592
6	3902.41666666667	218.75243721586	721

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2419.75 & 281.390742562722 & 681 \tabularnewline
2 & 2555.41666666667 & 80.2399337593007 & 209 \tabularnewline
3 & 2135.16666666667 & 298.162808891486 & 843 \tabularnewline
4 & 3126.58333333333 & 740.937055151765 & 1995 \tabularnewline
5 & 4411 & 197.945355177543 & 592 \tabularnewline
6 & 3902.41666666667 & 218.75243721586 & 721 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205008&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]2419.75[/C][C]281.390742562722[/C][C]681[/C][/ROW]
[ROW][C]2[/C][C]2555.41666666667[/C][C]80.2399337593007[/C][C]209[/C][/ROW]
[ROW][C]3[/C][C]2135.16666666667[/C][C]298.162808891486[/C][C]843[/C][/ROW]
[ROW][C]4[/C][C]3126.58333333333[/C][C]740.937055151765[/C][C]1995[/C][/ROW]
[ROW][C]5[/C][C]4411[/C][C]197.945355177543[/C][C]592[/C][/ROW]
[ROW][C]6[/C][C]3902.41666666667[/C][C]218.75243721586[/C][C]721[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205008&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205008&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	2419.75	281.390742562722	681
2	2555.41666666667	80.2399337593007	209
3	2135.16666666667	298.162808891486	843
4	3126.58333333333	740.937055151765	1995
5	4411	197.945355177543	592
6	3902.41666666667	218.75243721586	721

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	343.34322811421
beta	-0.013079605178339
S.D.	0.12647728950761
T-STAT	-0.103414654356204
p-value	0.922611334456226

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 343.34322811421 \tabularnewline
beta & -0.013079605178339 \tabularnewline
S.D. & 0.12647728950761 \tabularnewline
T-STAT & -0.103414654356204 \tabularnewline
p-value & 0.922611334456226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205008&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]343.34322811421[/C][/ROW]
[ROW][C]beta[/C][C]-0.013079605178339[/C][/ROW]
[ROW][C]S.D.[/C][C]0.12647728950761[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.103414654356204[/C][/ROW]
[ROW][C]p-value[/C][C]0.922611334456226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205008&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205008&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	343.34322811421
beta	-0.013079605178339
S.D.	0.12647728950761
T-STAT	-0.103414654356204
p-value	0.922611334456226

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	5.18230642520198
beta	0.0398315082486893
S.D.	1.2604596040549
T-STAT	0.0316007812710153
p-value	0.976304343510263
Lambda	0.960168491751311

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.18230642520198 \tabularnewline
beta & 0.0398315082486893 \tabularnewline
S.D. & 1.2604596040549 \tabularnewline
T-STAT & 0.0316007812710153 \tabularnewline
p-value & 0.976304343510263 \tabularnewline
Lambda & 0.960168491751311 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205008&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.18230642520198[/C][/ROW]
[ROW][C]beta[/C][C]0.0398315082486893[/C][/ROW]
[ROW][C]S.D.[/C][C]1.2604596040549[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0316007812710153[/C][/ROW]
[ROW][C]p-value[/C][C]0.976304343510263[/C][/ROW]
[ROW][C]Lambda[/C][C]0.960168491751311[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205008&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205008&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	5.18230642520198
beta	0.0398315082486893
S.D.	1.2604596040549
T-STAT	0.0316007812710153
p-value	0.976304343510263
Lambda	0.960168491751311

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