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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, 26 Jul 2013 12:09:10 -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/2013/Jul/26/t1374855016614hrhybxv8tiso.htm/, Retrieved Sun, 28 Apr 2024 19:47:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=210853, Retrieved Sun, 28 Apr 2024 19:47:58 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Jeroen Biesemans

Estimated Impact

158

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

-       [Standard Deviation-Mean Plot] [Tijdreeks B stap 21] [2013-07-26 16:09:10] [09688f513f3d2798cb35a3603f8bd204] [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	3 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 & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210853&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]3 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=210853&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210853&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	3 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2311.66666666667	102.499076122961	340
2	2298.33333333333	144.337567297406	560
3	2283.33333333333	190.469913316481	700
4	2246.66666666667	199.514562390971	680
5	2310	181.208067249677	600
6	2345	286.562701372984	960
7	2363.33333333333	322.020138651249	1060
8	2408.33333333333	318.685748129103	1100
9	2370	346.567584908183	1180

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2311.66666666667 & 102.499076122961 & 340 \tabularnewline
2 & 2298.33333333333 & 144.337567297406 & 560 \tabularnewline
3 & 2283.33333333333 & 190.469913316481 & 700 \tabularnewline
4 & 2246.66666666667 & 199.514562390971 & 680 \tabularnewline
5 & 2310 & 181.208067249677 & 600 \tabularnewline
6 & 2345 & 286.562701372984 & 960 \tabularnewline
7 & 2363.33333333333 & 322.020138651249 & 1060 \tabularnewline
8 & 2408.33333333333 & 318.685748129103 & 1100 \tabularnewline
9 & 2370 & 346.567584908183 & 1180 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210853&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]2311.66666666667[/C][C]102.499076122961[/C][C]340[/C][/ROW]
[ROW][C]2[/C][C]2298.33333333333[/C][C]144.337567297406[/C][C]560[/C][/ROW]
[ROW][C]3[/C][C]2283.33333333333[/C][C]190.469913316481[/C][C]700[/C][/ROW]
[ROW][C]4[/C][C]2246.66666666667[/C][C]199.514562390971[/C][C]680[/C][/ROW]
[ROW][C]5[/C][C]2310[/C][C]181.208067249677[/C][C]600[/C][/ROW]
[ROW][C]6[/C][C]2345[/C][C]286.562701372984[/C][C]960[/C][/ROW]
[ROW][C]7[/C][C]2363.33333333333[/C][C]322.020138651249[/C][C]1060[/C][/ROW]
[ROW][C]8[/C][C]2408.33333333333[/C][C]318.685748129103[/C][C]1100[/C][/ROW]
[ROW][C]9[/C][C]2370[/C][C]346.567584908183[/C][C]1180[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210853&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210853&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	2311.66666666667	102.499076122961	340
2	2298.33333333333	144.337567297406	560
3	2283.33333333333	190.469913316481	700
4	2246.66666666667	199.514562390971	680
5	2310	181.208067249677	600
6	2345	286.562701372984	960
7	2363.33333333333	322.020138651249	1060
8	2408.33333333333	318.685748129103	1100
9	2370	346.567584908183	1180

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-2822.8591286001
beta	1.31337036380385
S.D.	0.444216829639617
T-STAT	2.95659749062042
p-value	0.0212072422683434

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2822.8591286001 \tabularnewline
beta & 1.31337036380385 \tabularnewline
S.D. & 0.444216829639617 \tabularnewline
T-STAT & 2.95659749062042 \tabularnewline
p-value & 0.0212072422683434 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210853&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2822.8591286001[/C][/ROW]
[ROW][C]beta[/C][C]1.31337036380385[/C][/ROW]
[ROW][C]S.D.[/C][C]0.444216829639617[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.95659749062042[/C][/ROW]
[ROW][C]p-value[/C][C]0.0212072422683434[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210853&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210853&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	-2822.8591286001
beta	1.31337036380385
S.D.	0.444216829639617
T-STAT	2.95659749062042
p-value	0.0212072422683434

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-93.7779479546656
beta	12.7911514151915
S.D.	5.54467117946547
T-STAT	2.30692695764596
p-value	0.054432679137569
Lambda	-11.7911514151915

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -93.7779479546656 \tabularnewline
beta & 12.7911514151915 \tabularnewline
S.D. & 5.54467117946547 \tabularnewline
T-STAT & 2.30692695764596 \tabularnewline
p-value & 0.054432679137569 \tabularnewline
Lambda & -11.7911514151915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210853&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-93.7779479546656[/C][/ROW]
[ROW][C]beta[/C][C]12.7911514151915[/C][/ROW]
[ROW][C]S.D.[/C][C]5.54467117946547[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.30692695764596[/C][/ROW]
[ROW][C]p-value[/C][C]0.054432679137569[/C][/ROW]
[ROW][C]Lambda[/C][C]-11.7911514151915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210853&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210853&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	-93.7779479546656
beta	12.7911514151915
S.D.	5.54467117946547
T-STAT	2.30692695764596
p-value	0.054432679137569
Lambda	-11.7911514151915

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