Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Sun, 25 Nov 2007 02:36:37 -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/2007/Nov/25/t1195982871mgfoy1zsa3etf1s.htm/, Retrieved Sat, 04 May 2024 10:57:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6384, Retrieved Sat, 04 May 2024 10:57:29 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

256

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

-       [Standard Deviation-Mean Plot] [SDMP] [2007-11-25 09:36:37] [52b0ae29b3b0ac57b71db95ac12f6d2e] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6384&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6384&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6384&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 compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	112.416666666667	5.52331147926402	31.4
2	108.675	6.50889251856119	27.7
3	104.525	7.66172601014585	11.3
4	103.708333333333	6.07774753930394	14.3
5	101.2	5.83391339107339	9.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 112.416666666667 & 5.52331147926402 & 31.4 \tabularnewline
2 & 108.675 & 6.50889251856119 & 27.7 \tabularnewline
3 & 104.525 & 7.66172601014585 & 11.3 \tabularnewline
4 & 103.708333333333 & 6.07774753930394 & 14.3 \tabularnewline
5 & 101.2 & 5.83391339107339 & 9.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6384&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]112.416666666667[/C][C]5.52331147926402[/C][C]31.4[/C][/ROW]
[ROW][C]2[/C][C]108.675[/C][C]6.50889251856119[/C][C]27.7[/C][/ROW]
[ROW][C]3[/C][C]104.525[/C][C]7.66172601014585[/C][C]11.3[/C][/ROW]
[ROW][C]4[/C][C]103.708333333333[/C][C]6.07774753930394[/C][C]14.3[/C][/ROW]
[ROW][C]5[/C][C]101.2[/C][C]5.83391339107339[/C][C]9.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6384&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6384&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	112.416666666667	5.52331147926402	31.4
2	108.675	6.50889251856119	27.7
3	104.525	7.66172601014585	11.3
4	103.708333333333	6.07774753930394	14.3
5	101.2	5.83391339107339	9.3

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	11.3042845964807
beta	-0.0469644824354271
S.D.	0.104748334288710
T-STAT	-0.448355410654861
p-value	0.68430016434152

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 11.3042845964807 \tabularnewline
beta & -0.0469644824354271 \tabularnewline
S.D. & 0.104748334288710 \tabularnewline
T-STAT & -0.448355410654861 \tabularnewline
p-value & 0.68430016434152 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6384&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]11.3042845964807[/C][/ROW]
[ROW][C]beta[/C][C]-0.0469644824354271[/C][/ROW]
[ROW][C]S.D.[/C][C]0.104748334288710[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.448355410654861[/C][/ROW]
[ROW][C]p-value[/C][C]0.68430016434152[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6384&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6384&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	11.3042845964807
beta	-0.0469644824354271
S.D.	0.104748334288710
T-STAT	-0.448355410654861
p-value	0.68430016434152

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	5.42857142711005
beta	-0.77003284972314
S.D.	1.69905236549602
T-STAT	-0.453213135369338
p-value	0.681167926682653
Lambda	1.77003284972314

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.42857142711005 \tabularnewline
beta & -0.77003284972314 \tabularnewline
S.D. & 1.69905236549602 \tabularnewline
T-STAT & -0.453213135369338 \tabularnewline
p-value & 0.681167926682653 \tabularnewline
Lambda & 1.77003284972314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6384&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.42857142711005[/C][/ROW]
[ROW][C]beta[/C][C]-0.77003284972314[/C][/ROW]
[ROW][C]S.D.[/C][C]1.69905236549602[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.453213135369338[/C][/ROW]
[ROW][C]p-value[/C][C]0.681167926682653[/C][/ROW]
[ROW][C]Lambda[/C][C]1.77003284972314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6384&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6384&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	5.42857142711005
beta	-0.77003284972314
S.D.	1.69905236549602
T-STAT	-0.453213135369338
p-value	0.681167926682653
Lambda	1.77003284972314

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