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*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Tue, 06 Dec 2011 07:56:35 -0500

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/Dec/06/t1323176289xcrofpxa7rslbcz.htm/, Retrieved Mon, 29 Apr 2024 07:07:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151533, Retrieved Mon, 29 Apr 2024 07:07:18 +0000

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No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [opgave 8] [2011-12-06 12:56:35] [0756924702977927793c865c7c536cb0] [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	1 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
R Framework error message & Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151533&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151533&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151533&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	'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	164.95	1.76351920885483	4.29999999999998
2	169.95	1.3964240043769	3.30000000000001
3	173.875	1.59661099415815	3.90000000000001
4	176.85	1.72530190594768	3.80000000000001
5	180.625	1.28419884233972	2.80000000000001
6	184.9	1.83847763108502	4
7	189.25	1.78605710994918	3.90000000000001
8	194.875	1.10264832713487	2.69999999999999
9	198.525	2.11246301742777	5.10000000000002
10	204.725	1.29711217710729	3
11	209.025	1.01447851956887	2.19999999999999
12	213.15	1.37719521734091	3.10000000000002
13	218.225	1.70562793910825	4
14	223.3	1.6062378404209	3.69999999999999
15	227.975	1.11766124861993	2.59999999999999
16	232.15	2.69382008802864	6.09999999999999
17	239.625	1.70367250374008	3.90000000000001
18	243.9	0.605530070819506	1.30000000000001
19	246.325	1.12657297440807	2.59999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 164.95 & 1.76351920885483 & 4.29999999999998 \tabularnewline
2 & 169.95 & 1.3964240043769 & 3.30000000000001 \tabularnewline
3 & 173.875 & 1.59661099415815 & 3.90000000000001 \tabularnewline
4 & 176.85 & 1.72530190594768 & 3.80000000000001 \tabularnewline
5 & 180.625 & 1.28419884233972 & 2.80000000000001 \tabularnewline
6 & 184.9 & 1.83847763108502 & 4 \tabularnewline
7 & 189.25 & 1.78605710994918 & 3.90000000000001 \tabularnewline
8 & 194.875 & 1.10264832713487 & 2.69999999999999 \tabularnewline
9 & 198.525 & 2.11246301742777 & 5.10000000000002 \tabularnewline
10 & 204.725 & 1.29711217710729 & 3 \tabularnewline
11 & 209.025 & 1.01447851956887 & 2.19999999999999 \tabularnewline
12 & 213.15 & 1.37719521734091 & 3.10000000000002 \tabularnewline
13 & 218.225 & 1.70562793910825 & 4 \tabularnewline
14 & 223.3 & 1.6062378404209 & 3.69999999999999 \tabularnewline
15 & 227.975 & 1.11766124861993 & 2.59999999999999 \tabularnewline
16 & 232.15 & 2.69382008802864 & 6.09999999999999 \tabularnewline
17 & 239.625 & 1.70367250374008 & 3.90000000000001 \tabularnewline
18 & 243.9 & 0.605530070819506 & 1.30000000000001 \tabularnewline
19 & 246.325 & 1.12657297440807 & 2.59999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151533&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]164.95[/C][C]1.76351920885483[/C][C]4.29999999999998[/C][/ROW]
[ROW][C]2[/C][C]169.95[/C][C]1.3964240043769[/C][C]3.30000000000001[/C][/ROW]
[ROW][C]3[/C][C]173.875[/C][C]1.59661099415815[/C][C]3.90000000000001[/C][/ROW]
[ROW][C]4[/C][C]176.85[/C][C]1.72530190594768[/C][C]3.80000000000001[/C][/ROW]
[ROW][C]5[/C][C]180.625[/C][C]1.28419884233972[/C][C]2.80000000000001[/C][/ROW]
[ROW][C]6[/C][C]184.9[/C][C]1.83847763108502[/C][C]4[/C][/ROW]
[ROW][C]7[/C][C]189.25[/C][C]1.78605710994918[/C][C]3.90000000000001[/C][/ROW]
[ROW][C]8[/C][C]194.875[/C][C]1.10264832713487[/C][C]2.69999999999999[/C][/ROW]
[ROW][C]9[/C][C]198.525[/C][C]2.11246301742777[/C][C]5.10000000000002[/C][/ROW]
[ROW][C]10[/C][C]204.725[/C][C]1.29711217710729[/C][C]3[/C][/ROW]
[ROW][C]11[/C][C]209.025[/C][C]1.01447851956887[/C][C]2.19999999999999[/C][/ROW]
[ROW][C]12[/C][C]213.15[/C][C]1.37719521734091[/C][C]3.10000000000002[/C][/ROW]
[ROW][C]13[/C][C]218.225[/C][C]1.70562793910825[/C][C]4[/C][/ROW]
[ROW][C]14[/C][C]223.3[/C][C]1.6062378404209[/C][C]3.69999999999999[/C][/ROW]
[ROW][C]15[/C][C]227.975[/C][C]1.11766124861993[/C][C]2.59999999999999[/C][/ROW]
[ROW][C]16[/C][C]232.15[/C][C]2.69382008802864[/C][C]6.09999999999999[/C][/ROW]
[ROW][C]17[/C][C]239.625[/C][C]1.70367250374008[/C][C]3.90000000000001[/C][/ROW]
[ROW][C]18[/C][C]243.9[/C][C]0.605530070819506[/C][C]1.30000000000001[/C][/ROW]
[ROW][C]19[/C][C]246.325[/C][C]1.12657297440807[/C][C]2.59999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151533&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151533&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	164.95	1.76351920885483	4.29999999999998
2	169.95	1.3964240043769	3.30000000000001
3	173.875	1.59661099415815	3.90000000000001
4	176.85	1.72530190594768	3.80000000000001
5	180.625	1.28419884233972	2.80000000000001
6	184.9	1.83847763108502	4
7	189.25	1.78605710994918	3.90000000000001
8	194.875	1.10264832713487	2.69999999999999
9	198.525	2.11246301742777	5.10000000000002
10	204.725	1.29711217710729	3
11	209.025	1.01447851956887	2.19999999999999
12	213.15	1.37719521734091	3.10000000000002
13	218.225	1.70562793910825	4
14	223.3	1.6062378404209	3.69999999999999
15	227.975	1.11766124861993	2.59999999999999
16	232.15	2.69382008802864	6.09999999999999
17	239.625	1.70367250374008	3.90000000000001
18	243.9	0.605530070819506	1.30000000000001
19	246.325	1.12657297440807	2.59999999999999

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	2.18680733976438
beta	-0.00326183902037063
S.D.	0.00420013170423803
T-STAT	-0.776603985317737
p-value	0.448063969903216

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.18680733976438 \tabularnewline
beta & -0.00326183902037063 \tabularnewline
S.D. & 0.00420013170423803 \tabularnewline
T-STAT & -0.776603985317737 \tabularnewline
p-value & 0.448063969903216 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151533&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.18680733976438[/C][/ROW]
[ROW][C]beta[/C][C]-0.00326183902037063[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00420013170423803[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.776603985317737[/C][/ROW]
[ROW][C]p-value[/C][C]0.448063969903216[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151533&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151533&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	2.18680733976438
beta	-0.00326183902037063
S.D.	0.00420013170423803
T-STAT	-0.776603985317737
p-value	0.448063969903216

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	4.23832102753369
beta	-0.727633992160913
S.D.	0.588803509743403
T-STAT	-1.23578406059096
p-value	0.233343660096893
Lambda	1.72763399216091

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.23832102753369 \tabularnewline
beta & -0.727633992160913 \tabularnewline
S.D. & 0.588803509743403 \tabularnewline
T-STAT & -1.23578406059096 \tabularnewline
p-value & 0.233343660096893 \tabularnewline
Lambda & 1.72763399216091 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151533&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.23832102753369[/C][/ROW]
[ROW][C]beta[/C][C]-0.727633992160913[/C][/ROW]
[ROW][C]S.D.[/C][C]0.588803509743403[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.23578406059096[/C][/ROW]
[ROW][C]p-value[/C][C]0.233343660096893[/C][/ROW]
[ROW][C]Lambda[/C][C]1.72763399216091[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151533&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151533&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	4.23832102753369
beta	-0.727633992160913
S.D.	0.588803509743403
T-STAT	-1.23578406059096
p-value	0.233343660096893
Lambda	1.72763399216091

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code