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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, 15 Aug 2016 19:30:45 +0100

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/2016/Aug/15/t14712858752z79mnj90q9moi0.htm/, Retrieved Sun, 28 Apr 2024 14:30:33 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 28 Apr 2024 14:30:33 +0200

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Estimated Impact

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

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1348.33333333333	77.0871211190575	270
2	1362.5	78.2914136706284	250
3	1373.33333333333	104.562580942387	360
4	1366.66666666667	110.233911077831	330
5	1350	135.646599662505	420
6	1327.5	149.430737984343	450
7	1337.5	169.872947174699	640
8	1326.66666666667	175.878746110306	640
9	1318.33333333333	170.711523461143	630

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1348.33333333333 & 77.0871211190575 & 270 \tabularnewline
2 & 1362.5 & 78.2914136706284 & 250 \tabularnewline
3 & 1373.33333333333 & 104.562580942387 & 360 \tabularnewline
4 & 1366.66666666667 & 110.233911077831 & 330 \tabularnewline
5 & 1350 & 135.646599662505 & 420 \tabularnewline
6 & 1327.5 & 149.430737984343 & 450 \tabularnewline
7 & 1337.5 & 169.872947174699 & 640 \tabularnewline
8 & 1326.66666666667 & 175.878746110306 & 640 \tabularnewline
9 & 1318.33333333333 & 170.711523461143 & 630 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]1348.33333333333[/C][C]77.0871211190575[/C][C]270[/C][/ROW]
[ROW][C]2[/C][C]1362.5[/C][C]78.2914136706284[/C][C]250[/C][/ROW]
[ROW][C]3[/C][C]1373.33333333333[/C][C]104.562580942387[/C][C]360[/C][/ROW]
[ROW][C]4[/C][C]1366.66666666667[/C][C]110.233911077831[/C][C]330[/C][/ROW]
[ROW][C]5[/C][C]1350[/C][C]135.646599662505[/C][C]420[/C][/ROW]
[ROW][C]6[/C][C]1327.5[/C][C]149.430737984343[/C][C]450[/C][/ROW]
[ROW][C]7[/C][C]1337.5[/C][C]169.872947174699[/C][C]640[/C][/ROW]
[ROW][C]8[/C][C]1326.66666666667[/C][C]175.878746110306[/C][C]640[/C][/ROW]
[ROW][C]9[/C][C]1318.33333333333[/C][C]170.711523461143[/C][C]630[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	1348.33333333333	77.0871211190575	270
2	1362.5	78.2914136706284	250
3	1373.33333333333	104.562580942387	360
4	1366.66666666667	110.233911077831	330
5	1350	135.646599662505	420
6	1327.5	149.430737984343	450
7	1337.5	169.872947174699	640
8	1326.66666666667	175.878746110306	640
9	1318.33333333333	170.711523461143	630

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	2254.77975753173
beta	-1.5788593328218
S.D.	0.473627234679565
T-STAT	-3.3335484474198
p-value	0.0125299615141799

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2254.77975753173 \tabularnewline
beta & -1.5788593328218 \tabularnewline
S.D. & 0.473627234679565 \tabularnewline
T-STAT & -3.3335484474198 \tabularnewline
p-value & 0.0125299615141799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2254.77975753173[/C][/ROW]
[ROW][C]beta[/C][C]-1.5788593328218[/C][/ROW]
[ROW][C]S.D.[/C][C]0.473627234679565[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.3335484474198[/C][/ROW]
[ROW][C]p-value[/C][C]0.0125299615141799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	2254.77975753173
beta	-1.5788593328218
S.D.	0.473627234679565
T-STAT	-3.3335484474198
p-value	0.0125299615141799

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	124.221374905767
beta	-16.5724689666307
S.D.	5.76808645798034
T-STAT	-2.87313116531084
p-value	0.0238848635177994
Lambda	17.5724689666307

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 124.221374905767 \tabularnewline
beta & -16.5724689666307 \tabularnewline
S.D. & 5.76808645798034 \tabularnewline
T-STAT & -2.87313116531084 \tabularnewline
p-value & 0.0238848635177994 \tabularnewline
Lambda & 17.5724689666307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]124.221374905767[/C][/ROW]
[ROW][C]beta[/C][C]-16.5724689666307[/C][/ROW]
[ROW][C]S.D.[/C][C]5.76808645798034[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.87313116531084[/C][/ROW]
[ROW][C]p-value[/C][C]0.0238848635177994[/C][/ROW]
[ROW][C]Lambda[/C][C]17.5724689666307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	124.221374905767
beta	-16.5724689666307
S.D.	5.76808645798034
T-STAT	-2.87313116531084
p-value	0.0238848635177994
Lambda	17.5724689666307

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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