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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

Wed, 06 Jan 2010 03:44:26 -0700

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/2010/Jan/06/t12627747884aeaphu6os2szmr.htm/, Retrieved Sat, 04 May 2024 08:35:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71648, Retrieved Sat, 04 May 2024 08:35:47 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

138

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

-       [Standard Deviation-Mean Plot] [opgave 8 3c] [2010-01-06 10:44:26] [f8fa19533df6d92688ec2c19e4765e3f] [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	5 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71648&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71648&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71648&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	5 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	162.236666666667	0.403987698582596	1.22
2	162.040833333333	0.313062826495475	0.810000000000002
3	163.146666666667	0.463667853951381	1.28999999999999
4	164.848333333333	0.882916997368626	2.40000000000001
5	166.593333333333	0.439655512528809	1.37000000000000
6	167.434166666667	0.371396830978147	0.890000000000015
7	168.735833333333	0.575664964641023	1.59000000000000
8	171.7225	1.05872242907109	3.36000000000001
9	173.25	0.882259495943128	2.39000000000001
10	175.688333333333	0.594609624931021	1.99000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 162.236666666667 & 0.403987698582596 & 1.22 \tabularnewline
2 & 162.040833333333 & 0.313062826495475 & 0.810000000000002 \tabularnewline
3 & 163.146666666667 & 0.463667853951381 & 1.28999999999999 \tabularnewline
4 & 164.848333333333 & 0.882916997368626 & 2.40000000000001 \tabularnewline
5 & 166.593333333333 & 0.439655512528809 & 1.37000000000000 \tabularnewline
6 & 167.434166666667 & 0.371396830978147 & 0.890000000000015 \tabularnewline
7 & 168.735833333333 & 0.575664964641023 & 1.59000000000000 \tabularnewline
8 & 171.7225 & 1.05872242907109 & 3.36000000000001 \tabularnewline
9 & 173.25 & 0.882259495943128 & 2.39000000000001 \tabularnewline
10 & 175.688333333333 & 0.594609624931021 & 1.99000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71648&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]162.236666666667[/C][C]0.403987698582596[/C][C]1.22[/C][/ROW]
[ROW][C]2[/C][C]162.040833333333[/C][C]0.313062826495475[/C][C]0.810000000000002[/C][/ROW]
[ROW][C]3[/C][C]163.146666666667[/C][C]0.463667853951381[/C][C]1.28999999999999[/C][/ROW]
[ROW][C]4[/C][C]164.848333333333[/C][C]0.882916997368626[/C][C]2.40000000000001[/C][/ROW]
[ROW][C]5[/C][C]166.593333333333[/C][C]0.439655512528809[/C][C]1.37000000000000[/C][/ROW]
[ROW][C]6[/C][C]167.434166666667[/C][C]0.371396830978147[/C][C]0.890000000000015[/C][/ROW]
[ROW][C]7[/C][C]168.735833333333[/C][C]0.575664964641023[/C][C]1.59000000000000[/C][/ROW]
[ROW][C]8[/C][C]171.7225[/C][C]1.05872242907109[/C][C]3.36000000000001[/C][/ROW]
[ROW][C]9[/C][C]173.25[/C][C]0.882259495943128[/C][C]2.39000000000001[/C][/ROW]
[ROW][C]10[/C][C]175.688333333333[/C][C]0.594609624931021[/C][C]1.99000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71648&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71648&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	162.236666666667	0.403987698582596	1.22
2	162.040833333333	0.313062826495475	0.810000000000002
3	163.146666666667	0.463667853951381	1.28999999999999
4	164.848333333333	0.882916997368626	2.40000000000001
5	166.593333333333	0.439655512528809	1.37000000000000
6	167.434166666667	0.371396830978147	0.890000000000015
7	168.735833333333	0.575664964641023	1.59000000000000
8	171.7225	1.05872242907109	3.36000000000001
9	173.25	0.882259495943128	2.39000000000001
10	175.688333333333	0.594609624931021	1.99000000000001

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-4.40919826090639
beta	0.0298848400427813
S.D.	0.0157847213944875
T-STAT	1.89327637123947
p-value	0.0949458493797968

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.40919826090639 \tabularnewline
beta & 0.0298848400427813 \tabularnewline
S.D. & 0.0157847213944875 \tabularnewline
T-STAT & 1.89327637123947 \tabularnewline
p-value & 0.0949458493797968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71648&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.40919826090639[/C][/ROW]
[ROW][C]beta[/C][C]0.0298848400427813[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0157847213944875[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.89327637123947[/C][/ROW]
[ROW][C]p-value[/C][C]0.0949458493797968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71648&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71648&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	-4.40919826090639
beta	0.0298848400427813
S.D.	0.0157847213944875
T-STAT	1.89327637123947
p-value	0.0949458493797968

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-45.5906668635856
beta	8.78714895784262
S.D.	4.11894282444055
T-STAT	2.13335055434670
p-value	0.065450628047474
Lambda	-7.78714895784262

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -45.5906668635856 \tabularnewline
beta & 8.78714895784262 \tabularnewline
S.D. & 4.11894282444055 \tabularnewline
T-STAT & 2.13335055434670 \tabularnewline
p-value & 0.065450628047474 \tabularnewline
Lambda & -7.78714895784262 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71648&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-45.5906668635856[/C][/ROW]
[ROW][C]beta[/C][C]8.78714895784262[/C][/ROW]
[ROW][C]S.D.[/C][C]4.11894282444055[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.13335055434670[/C][/ROW]
[ROW][C]p-value[/C][C]0.065450628047474[/C][/ROW]
[ROW][C]Lambda[/C][C]-7.78714895784262[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71648&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71648&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	-45.5906668635856
beta	8.78714895784262
S.D.	4.11894282444055
T-STAT	2.13335055434670
p-value	0.065450628047474
Lambda	-7.78714895784262

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