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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

Thu, 18 Aug 2011 16:51:56 -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/2011/Aug/18/t13137007308r5ixqmbkeieizf.htm/, Retrieved Wed, 15 May 2024 09:45:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=124160, Retrieved Wed, 15 May 2024 09:45:15 +0000

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No (this computation is public)

User-defined keywords

Gregory Goris

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [Tijdreeks B - Sta...] [2011-08-18 20:51:56] [4069dbe0e58b4004934f5f5b0dc60f40] [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	0 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124160&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124160&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124160&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	0 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1319.16666666667	55.833898685514	160
2	1308.33333333333	59.9747421584261	180
3	1318.33333333333	65.8970730945179	220
4	1330.83333333333	74.034185387972	210
5	1324.16666666667	94.3357960916344	290
6	1326.66666666667	113.003083894631	460
7	1295.83333333333	129.576817043604	490
8	1294.16666666667	138.921713292928	530
9	1313.33333333333	156.282572362508	580

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1319.16666666667 & 55.833898685514 & 160 \tabularnewline
2 & 1308.33333333333 & 59.9747421584261 & 180 \tabularnewline
3 & 1318.33333333333 & 65.8970730945179 & 220 \tabularnewline
4 & 1330.83333333333 & 74.034185387972 & 210 \tabularnewline
5 & 1324.16666666667 & 94.3357960916344 & 290 \tabularnewline
6 & 1326.66666666667 & 113.003083894631 & 460 \tabularnewline
7 & 1295.83333333333 & 129.576817043604 & 490 \tabularnewline
8 & 1294.16666666667 & 138.921713292928 & 530 \tabularnewline
9 & 1313.33333333333 & 156.282572362508 & 580 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124160&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]1319.16666666667[/C][C]55.833898685514[/C][C]160[/C][/ROW]
[ROW][C]2[/C][C]1308.33333333333[/C][C]59.9747421584261[/C][C]180[/C][/ROW]
[ROW][C]3[/C][C]1318.33333333333[/C][C]65.8970730945179[/C][C]220[/C][/ROW]
[ROW][C]4[/C][C]1330.83333333333[/C][C]74.034185387972[/C][C]210[/C][/ROW]
[ROW][C]5[/C][C]1324.16666666667[/C][C]94.3357960916344[/C][C]290[/C][/ROW]
[ROW][C]6[/C][C]1326.66666666667[/C][C]113.003083894631[/C][C]460[/C][/ROW]
[ROW][C]7[/C][C]1295.83333333333[/C][C]129.576817043604[/C][C]490[/C][/ROW]
[ROW][C]8[/C][C]1294.16666666667[/C][C]138.921713292928[/C][C]530[/C][/ROW]
[ROW][C]9[/C][C]1313.33333333333[/C][C]156.282572362508[/C][C]580[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124160&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124160&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	1319.16666666667	55.833898685514	160
2	1308.33333333333	59.9747421584261	180
3	1318.33333333333	65.8970730945179	220
4	1330.83333333333	74.034185387972	210
5	1324.16666666667	94.3357960916344	290
6	1326.66666666667	113.003083894631	460
7	1295.83333333333	129.576817043604	490
8	1294.16666666667	138.921713292928	530
9	1313.33333333333	156.282572362508	580

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1875.53291689716
beta	-1.35171681651583
S.D.	0.959422774848867
T-STAT	-1.40888547984361
p-value	0.201706432704721

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1875.53291689716 \tabularnewline
beta & -1.35171681651583 \tabularnewline
S.D. & 0.959422774848867 \tabularnewline
T-STAT & -1.40888547984361 \tabularnewline
p-value & 0.201706432704721 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124160&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1875.53291689716[/C][/ROW]
[ROW][C]beta[/C][C]-1.35171681651583[/C][/ROW]
[ROW][C]S.D.[/C][C]0.959422774848867[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.40888547984361[/C][/ROW]
[ROW][C]p-value[/C][C]0.201706432704721[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124160&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124160&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	1875.53291689716
beta	-1.35171681651583
S.D.	0.959422774848867
T-STAT	-1.40888547984361
p-value	0.201706432704721

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	124.98570791827
beta	-16.7743376452963
S.D.	13.3853422562682
T-STAT	-1.25318705522387
p-value	0.250373809051612
Lambda	17.7743376452963

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 124.98570791827 \tabularnewline
beta & -16.7743376452963 \tabularnewline
S.D. & 13.3853422562682 \tabularnewline
T-STAT & -1.25318705522387 \tabularnewline
p-value & 0.250373809051612 \tabularnewline
Lambda & 17.7743376452963 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124160&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]124.98570791827[/C][/ROW]
[ROW][C]beta[/C][C]-16.7743376452963[/C][/ROW]
[ROW][C]S.D.[/C][C]13.3853422562682[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.25318705522387[/C][/ROW]
[ROW][C]p-value[/C][C]0.250373809051612[/C][/ROW]
[ROW][C]Lambda[/C][C]17.7743376452963[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124160&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124160&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	124.98570791827
beta	-16.7743376452963
S.D.	13.3853422562682
T-STAT	-1.25318705522387
p-value	0.250373809051612
Lambda	17.7743376452963

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