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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Sat, 13 Dec 2008 05:08:21 -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/2008/Dec/13/t12291701651agkcn308ra3dr3.htm/, Retrieved Sun, 19 May 2024 08:02:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32995, Retrieved Sun, 19 May 2024 08:02:37 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

jenske_cole@hotmail.com

Estimated Impact

216

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

F     [Bivariate Kernel Density Estimation] [Various EDA Topic...] [2008-11-12 13:37:39] [8094ad203a218aaca2d1cea2c78c2d6e]
F    D  [Bivariate Kernel Density Estimation] [opdracht3 blok8 q...] [2008-11-12 17:51:49] [975daa21de49eaf4d491226310243f5a]
- RMPD      [Standard Deviation-Mean Plot] [paper standard de...] [2008-12-13 12:08:21] [120dfa2440e51a0cfc0f5296bc5d7460] [Current]

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Dataseries X:

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Histogram

Boxplots

7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8
8.1
8.2
8.3
8.2
8
7.9
7.6
7.6
8.2
8.3
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.5
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.6
8.2
8.1
8
8.6
8.7
8.8
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.1
8.2
8.1
8.1
7.9
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8
6.9
6.8
6.7

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	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32995&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32995&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32995&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	'George Udny Yule' @ 72.249.76.132

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	7.525	0.453521574108463	1.4
2	8.15833333333333	0.320392751402892	1
3	8.4	0.700649049745371	2.1
4	8.45833333333333	0.242930342928074	0.8
5	8.25	0.306000594176488	0.799999999999999
6	7.48333333333333	0.417423554968361	1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.525 & 0.453521574108463 & 1.4 \tabularnewline
2 & 8.15833333333333 & 0.320392751402892 & 1 \tabularnewline
3 & 8.4 & 0.700649049745371 & 2.1 \tabularnewline
4 & 8.45833333333333 & 0.242930342928074 & 0.8 \tabularnewline
5 & 8.25 & 0.306000594176488 & 0.799999999999999 \tabularnewline
6 & 7.48333333333333 & 0.417423554968361 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32995&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]7.525[/C][C]0.453521574108463[/C][C]1.4[/C][/ROW]
[ROW][C]2[/C][C]8.15833333333333[/C][C]0.320392751402892[/C][C]1[/C][/ROW]
[ROW][C]3[/C][C]8.4[/C][C]0.700649049745371[/C][C]2.1[/C][/ROW]
[ROW][C]4[/C][C]8.45833333333333[/C][C]0.242930342928074[/C][C]0.8[/C][/ROW]
[ROW][C]5[/C][C]8.25[/C][C]0.306000594176488[/C][C]0.799999999999999[/C][/ROW]
[ROW][C]6[/C][C]7.48333333333333[/C][C]0.417423554968361[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32995&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32995&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	7.525	0.453521574108463	1.4
2	8.15833333333333	0.320392751402892	1
3	8.4	0.700649049745371	2.1
4	8.45833333333333	0.242930342928074	0.8
5	8.25	0.306000594176488	0.799999999999999
6	7.48333333333333	0.417423554968361	1

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.613931072357525
beta	-0.0257414514099535
S.D.	0.187962426197020
T-STAT	-0.136949984796278
p-value	0.897686879440086

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.613931072357525 \tabularnewline
beta & -0.0257414514099535 \tabularnewline
S.D. & 0.187962426197020 \tabularnewline
T-STAT & -0.136949984796278 \tabularnewline
p-value & 0.897686879440086 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32995&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.613931072357525[/C][/ROW]
[ROW][C]beta[/C][C]-0.0257414514099535[/C][/ROW]
[ROW][C]S.D.[/C][C]0.187962426197020[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.136949984796278[/C][/ROW]
[ROW][C]p-value[/C][C]0.897686879440086[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32995&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32995&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	0.613931072357525
beta	-0.0257414514099535
S.D.	0.187962426197020
T-STAT	-0.136949984796278
p-value	0.897686879440086

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	2.17282981128744
beta	-1.50312956313010
S.D.	3.31927292696197
T-STAT	-0.452849041403133
p-value	0.674133210468905
Lambda	2.5031295631301

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.17282981128744 \tabularnewline
beta & -1.50312956313010 \tabularnewline
S.D. & 3.31927292696197 \tabularnewline
T-STAT & -0.452849041403133 \tabularnewline
p-value & 0.674133210468905 \tabularnewline
Lambda & 2.5031295631301 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32995&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.17282981128744[/C][/ROW]
[ROW][C]beta[/C][C]-1.50312956313010[/C][/ROW]
[ROW][C]S.D.[/C][C]3.31927292696197[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.452849041403133[/C][/ROW]
[ROW][C]p-value[/C][C]0.674133210468905[/C][/ROW]
[ROW][C]Lambda[/C][C]2.5031295631301[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32995&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32995&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	2.17282981128744
beta	-1.50312956313010
S.D.	3.31927292696197
T-STAT	-0.452849041403133
p-value	0.674133210468905
Lambda	2.5031295631301

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

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