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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, 07 Dec 2011 10:45:34 -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/07/t1323272776wims4mlfbpfu5yp.htm/, Retrieved Wed, 15 May 2024 20:22:50 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=152516, Retrieved Wed, 15 May 2024 20:22:50 +0000

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IsPrivate?

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] [standard deviaton...] [2011-12-07 15:45:34] [659094c92b72720b61457cd096818e91] [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	2 seconds
R Server	'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152516&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152516&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152516&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	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	31.2875	0.179884222024427	0.440000000000001
2	31.1075	0.0170782512765987	0.0399999999999991
3	30.855	0.123423390543825	0.290000000000003
4	30.7075	0.0928708781050344	0.220000000000002
5	30.7075	0.00957427107756333	0.0199999999999996
6	30.775	0.0680685928555407	0.16
7	30.8675	0.04991659710624	0.120000000000001
8	30.7675	0.0350000000000001	0.0700000000000003
9	30.5825	0.0464578662158879	0.109999999999999
10	30.6	0.0294392028877597	0.0700000000000003
11	30.59	0.0424264068711922	0.0999999999999979
12	30.405	0.170782512765993	0.359999999999999
13	30.0625	0.173661548229115	0.390000000000001
14	29.9075	0.104682058316281	0.23
15	29.9575	0.0921502396451949	0.200000000000003

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 31.2875 & 0.179884222024427 & 0.440000000000001 \tabularnewline
2 & 31.1075 & 0.0170782512765987 & 0.0399999999999991 \tabularnewline
3 & 30.855 & 0.123423390543825 & 0.290000000000003 \tabularnewline
4 & 30.7075 & 0.0928708781050344 & 0.220000000000002 \tabularnewline
5 & 30.7075 & 0.00957427107756333 & 0.0199999999999996 \tabularnewline
6 & 30.775 & 0.0680685928555407 & 0.16 \tabularnewline
7 & 30.8675 & 0.04991659710624 & 0.120000000000001 \tabularnewline
8 & 30.7675 & 0.0350000000000001 & 0.0700000000000003 \tabularnewline
9 & 30.5825 & 0.0464578662158879 & 0.109999999999999 \tabularnewline
10 & 30.6 & 0.0294392028877597 & 0.0700000000000003 \tabularnewline
11 & 30.59 & 0.0424264068711922 & 0.0999999999999979 \tabularnewline
12 & 30.405 & 0.170782512765993 & 0.359999999999999 \tabularnewline
13 & 30.0625 & 0.173661548229115 & 0.390000000000001 \tabularnewline
14 & 29.9075 & 0.104682058316281 & 0.23 \tabularnewline
15 & 29.9575 & 0.0921502396451949 & 0.200000000000003 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152516&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]31.2875[/C][C]0.179884222024427[/C][C]0.440000000000001[/C][/ROW]
[ROW][C]2[/C][C]31.1075[/C][C]0.0170782512765987[/C][C]0.0399999999999991[/C][/ROW]
[ROW][C]3[/C][C]30.855[/C][C]0.123423390543825[/C][C]0.290000000000003[/C][/ROW]
[ROW][C]4[/C][C]30.7075[/C][C]0.0928708781050344[/C][C]0.220000000000002[/C][/ROW]
[ROW][C]5[/C][C]30.7075[/C][C]0.00957427107756333[/C][C]0.0199999999999996[/C][/ROW]
[ROW][C]6[/C][C]30.775[/C][C]0.0680685928555407[/C][C]0.16[/C][/ROW]
[ROW][C]7[/C][C]30.8675[/C][C]0.04991659710624[/C][C]0.120000000000001[/C][/ROW]
[ROW][C]8[/C][C]30.7675[/C][C]0.0350000000000001[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]9[/C][C]30.5825[/C][C]0.0464578662158879[/C][C]0.109999999999999[/C][/ROW]
[ROW][C]10[/C][C]30.6[/C][C]0.0294392028877597[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]11[/C][C]30.59[/C][C]0.0424264068711922[/C][C]0.0999999999999979[/C][/ROW]
[ROW][C]12[/C][C]30.405[/C][C]0.170782512765993[/C][C]0.359999999999999[/C][/ROW]
[ROW][C]13[/C][C]30.0625[/C][C]0.173661548229115[/C][C]0.390000000000001[/C][/ROW]
[ROW][C]14[/C][C]29.9075[/C][C]0.104682058316281[/C][C]0.23[/C][/ROW]
[ROW][C]15[/C][C]29.9575[/C][C]0.0921502396451949[/C][C]0.200000000000003[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152516&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152516&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	31.2875	0.179884222024427	0.440000000000001
2	31.1075	0.0170782512765987	0.0399999999999991
3	30.855	0.123423390543825	0.290000000000003
4	30.7075	0.0928708781050344	0.220000000000002
5	30.7075	0.00957427107756333	0.0199999999999996
6	30.775	0.0680685928555407	0.16
7	30.8675	0.04991659710624	0.120000000000001
8	30.7675	0.0350000000000001	0.0700000000000003
9	30.5825	0.0464578662158879	0.109999999999999
10	30.6	0.0294392028877597	0.0700000000000003
11	30.59	0.0424264068711922	0.0999999999999979
12	30.405	0.170782512765993	0.359999999999999
13	30.0625	0.173661548229115	0.390000000000001
14	29.9075	0.104682058316281	0.23
15	29.9575	0.0921502396451949	0.200000000000003

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1.04979269242018
beta	-0.0316030191828521
S.D.	0.0398135460382388
T-STAT	-0.793775544446582
p-value	0.441574936468513

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.04979269242018 \tabularnewline
beta & -0.0316030191828521 \tabularnewline
S.D. & 0.0398135460382388 \tabularnewline
T-STAT & -0.793775544446582 \tabularnewline
p-value & 0.441574936468513 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152516&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.04979269242018[/C][/ROW]
[ROW][C]beta[/C][C]-0.0316030191828521[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0398135460382388[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.793775544446582[/C][/ROW]
[ROW][C]p-value[/C][C]0.441574936468513[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152516&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152516&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	1.04979269242018
beta	-0.0316030191828521
S.D.	0.0398135460382388
T-STAT	-0.793775544446582
p-value	0.441574936468513

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	65.2735904153906
beta	-19.8940566775427
S.D.	17.9058520896496
T-STAT	-1.11103658055136
p-value	0.286679426910659
Lambda	20.8940566775427

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 65.2735904153906 \tabularnewline
beta & -19.8940566775427 \tabularnewline
S.D. & 17.9058520896496 \tabularnewline
T-STAT & -1.11103658055136 \tabularnewline
p-value & 0.286679426910659 \tabularnewline
Lambda & 20.8940566775427 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152516&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]65.2735904153906[/C][/ROW]
[ROW][C]beta[/C][C]-19.8940566775427[/C][/ROW]
[ROW][C]S.D.[/C][C]17.9058520896496[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.11103658055136[/C][/ROW]
[ROW][C]p-value[/C][C]0.286679426910659[/C][/ROW]
[ROW][C]Lambda[/C][C]20.8940566775427[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152516&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152516&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	65.2735904153906
beta	-19.8940566775427
S.D.	17.9058520896496
T-STAT	-1.11103658055136
p-value	0.286679426910659
Lambda	20.8940566775427

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