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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, 01 Dec 2010 13:40:04 +0000

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/Dec/01/t1291210914huwdws3kvk09lmd.htm/, Retrieved Sun, 05 May 2024 20:08:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=103987, Retrieved Sun, 05 May 2024 20:08:03 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

113

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

-       [Standard Deviation-Mean Plot] [Opgave 8; Opdrach...] [2010-12-01 13:40:04] [516d1a4ad1f0b8513272cbee80fe4619] [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	'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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103987&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103987&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103987&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	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	13.89	0.0559761854124885	0.129999999999999
2	14.01	0.0408248290463862	0.0999999999999996
3	14.1175	0.0189296944860013	0.0400000000000009
4	14.1925	0.0537742193496721	0.119999999999999
5	14.3325	0.0419324854180309	0.100000000000001
6	14.465	0.0191485421551271	0.0400000000000009
7	14.5875	0.0427200187265875	0.0899999999999999
8	14.66	0.0391578004149024	0.0899999999999999
9	14.85	0.0522812904711943	0.110000000000001
10	15.2675	0.102753750945322	0.229999999999999
11	15.42	0.0336650164612071	0.0700000000000003
12	15.5825	0.04991659710624	0.110000000000001
13	15.86	0.0804155872120987	0.190000000000000
14	15.965	0.0300000000000003	0.0600000000000005
15	16.08	0.0216024689946930	0.0500000000000007
16	16.2625	0.123389626792532	0.270000000000003
17	16.5525	0.0708872343937896	0.150000000000002
18	16.825	0.120692446601545	0.260000000000002
19	17.095	0.0994987437106624	0.210000000000001
20	17.3575	0.0689806736219164	0.16
21	17.54	0.0860232526704258	0.199999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 13.89 & 0.0559761854124885 & 0.129999999999999 \tabularnewline
2 & 14.01 & 0.0408248290463862 & 0.0999999999999996 \tabularnewline
3 & 14.1175 & 0.0189296944860013 & 0.0400000000000009 \tabularnewline
4 & 14.1925 & 0.0537742193496721 & 0.119999999999999 \tabularnewline
5 & 14.3325 & 0.0419324854180309 & 0.100000000000001 \tabularnewline
6 & 14.465 & 0.0191485421551271 & 0.0400000000000009 \tabularnewline
7 & 14.5875 & 0.0427200187265875 & 0.0899999999999999 \tabularnewline
8 & 14.66 & 0.0391578004149024 & 0.0899999999999999 \tabularnewline
9 & 14.85 & 0.0522812904711943 & 0.110000000000001 \tabularnewline
10 & 15.2675 & 0.102753750945322 & 0.229999999999999 \tabularnewline
11 & 15.42 & 0.0336650164612071 & 0.0700000000000003 \tabularnewline
12 & 15.5825 & 0.04991659710624 & 0.110000000000001 \tabularnewline
13 & 15.86 & 0.0804155872120987 & 0.190000000000000 \tabularnewline
14 & 15.965 & 0.0300000000000003 & 0.0600000000000005 \tabularnewline
15 & 16.08 & 0.0216024689946930 & 0.0500000000000007 \tabularnewline
16 & 16.2625 & 0.123389626792532 & 0.270000000000003 \tabularnewline
17 & 16.5525 & 0.0708872343937896 & 0.150000000000002 \tabularnewline
18 & 16.825 & 0.120692446601545 & 0.260000000000002 \tabularnewline
19 & 17.095 & 0.0994987437106624 & 0.210000000000001 \tabularnewline
20 & 17.3575 & 0.0689806736219164 & 0.16 \tabularnewline
21 & 17.54 & 0.0860232526704258 & 0.199999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103987&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]13.89[/C][C]0.0559761854124885[/C][C]0.129999999999999[/C][/ROW]
[ROW][C]2[/C][C]14.01[/C][C]0.0408248290463862[/C][C]0.0999999999999996[/C][/ROW]
[ROW][C]3[/C][C]14.1175[/C][C]0.0189296944860013[/C][C]0.0400000000000009[/C][/ROW]
[ROW][C]4[/C][C]14.1925[/C][C]0.0537742193496721[/C][C]0.119999999999999[/C][/ROW]
[ROW][C]5[/C][C]14.3325[/C][C]0.0419324854180309[/C][C]0.100000000000001[/C][/ROW]
[ROW][C]6[/C][C]14.465[/C][C]0.0191485421551271[/C][C]0.0400000000000009[/C][/ROW]
[ROW][C]7[/C][C]14.5875[/C][C]0.0427200187265875[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]8[/C][C]14.66[/C][C]0.0391578004149024[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]9[/C][C]14.85[/C][C]0.0522812904711943[/C][C]0.110000000000001[/C][/ROW]
[ROW][C]10[/C][C]15.2675[/C][C]0.102753750945322[/C][C]0.229999999999999[/C][/ROW]
[ROW][C]11[/C][C]15.42[/C][C]0.0336650164612071[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]12[/C][C]15.5825[/C][C]0.04991659710624[/C][C]0.110000000000001[/C][/ROW]
[ROW][C]13[/C][C]15.86[/C][C]0.0804155872120987[/C][C]0.190000000000000[/C][/ROW]
[ROW][C]14[/C][C]15.965[/C][C]0.0300000000000003[/C][C]0.0600000000000005[/C][/ROW]
[ROW][C]15[/C][C]16.08[/C][C]0.0216024689946930[/C][C]0.0500000000000007[/C][/ROW]
[ROW][C]16[/C][C]16.2625[/C][C]0.123389626792532[/C][C]0.270000000000003[/C][/ROW]
[ROW][C]17[/C][C]16.5525[/C][C]0.0708872343937896[/C][C]0.150000000000002[/C][/ROW]
[ROW][C]18[/C][C]16.825[/C][C]0.120692446601545[/C][C]0.260000000000002[/C][/ROW]
[ROW][C]19[/C][C]17.095[/C][C]0.0994987437106624[/C][C]0.210000000000001[/C][/ROW]
[ROW][C]20[/C][C]17.3575[/C][C]0.0689806736219164[/C][C]0.16[/C][/ROW]
[ROW][C]21[/C][C]17.54[/C][C]0.0860232526704258[/C][C]0.199999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103987&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103987&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	13.89	0.0559761854124885	0.129999999999999
2	14.01	0.0408248290463862	0.0999999999999996
3	14.1175	0.0189296944860013	0.0400000000000009
4	14.1925	0.0537742193496721	0.119999999999999
5	14.3325	0.0419324854180309	0.100000000000001
6	14.465	0.0191485421551271	0.0400000000000009
7	14.5875	0.0427200187265875	0.0899999999999999
8	14.66	0.0391578004149024	0.0899999999999999
9	14.85	0.0522812904711943	0.110000000000001
10	15.2675	0.102753750945322	0.229999999999999
11	15.42	0.0336650164612071	0.0700000000000003
12	15.5825	0.04991659710624	0.110000000000001
13	15.86	0.0804155872120987	0.190000000000000
14	15.965	0.0300000000000003	0.0600000000000005
15	16.08	0.0216024689946930	0.0500000000000007
16	16.2625	0.123389626792532	0.270000000000003
17	16.5525	0.0708872343937896	0.150000000000002
18	16.825	0.120692446601545	0.260000000000002
19	17.095	0.0994987437106624	0.210000000000001
20	17.3575	0.0689806736219164	0.16
21	17.54	0.0860232526704258	0.199999999999999

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-0.189206785723441
beta	0.0160840625220116
S.D.	0.00509951143936573
T-STAT	3.1540398944594
p-value	0.00522512499433106

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.189206785723441 \tabularnewline
beta & 0.0160840625220116 \tabularnewline
S.D. & 0.00509951143936573 \tabularnewline
T-STAT & 3.1540398944594 \tabularnewline
p-value & 0.00522512499433106 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103987&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.189206785723441[/C][/ROW]
[ROW][C]beta[/C][C]0.0160840625220116[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00509951143936573[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.1540398944594[/C][/ROW]
[ROW][C]p-value[/C][C]0.00522512499433106[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103987&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103987&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	-0.189206785723441
beta	0.0160840625220116
S.D.	0.00509951143936573
T-STAT	3.1540398944594
p-value	0.00522512499433106

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-14.2690822788746
beta	4.13120437272260
S.D.	1.46484807740262
T-STAT	2.82022718700481
p-value	0.0109307969432783
Lambda	-3.13120437272260

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -14.2690822788746 \tabularnewline
beta & 4.13120437272260 \tabularnewline
S.D. & 1.46484807740262 \tabularnewline
T-STAT & 2.82022718700481 \tabularnewline
p-value & 0.0109307969432783 \tabularnewline
Lambda & -3.13120437272260 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103987&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-14.2690822788746[/C][/ROW]
[ROW][C]beta[/C][C]4.13120437272260[/C][/ROW]
[ROW][C]S.D.[/C][C]1.46484807740262[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.82022718700481[/C][/ROW]
[ROW][C]p-value[/C][C]0.0109307969432783[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.13120437272260[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103987&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103987&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	-14.2690822788746
beta	4.13120437272260
S.D.	1.46484807740262
T-STAT	2.82022718700481
p-value	0.0109307969432783
Lambda	-3.13120437272260

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

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