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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

Tue, 05 Jan 2016 21:21:35 +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/2016/Jan/05/t1452029516qduuss93fznhoew.htm/, Retrieved Sat, 04 May 2024 15:28:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=287335, Retrieved Sat, 04 May 2024 15:28:44 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

146

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

-       [Standard Deviation-Mean Plot] [] [2016-01-05 21:21:35] [f684f3a3d8618606ffff76ddc8e0eec7] [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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287335&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287335&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287335&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	99.9916666666667	2.95649003606191	11.9
2	117.75	3.54003081650686	12.6
3	127.308333333333	2.70234185756568	9.60000000000001
4	122.366666666667	2.76120307551662	8.59999999999999
5	113.633333333333	5.82554458372517	21.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.9916666666667 & 2.95649003606191 & 11.9 \tabularnewline
2 & 117.75 & 3.54003081650686 & 12.6 \tabularnewline
3 & 127.308333333333 & 2.70234185756568 & 9.60000000000001 \tabularnewline
4 & 122.366666666667 & 2.76120307551662 & 8.59999999999999 \tabularnewline
5 & 113.633333333333 & 5.82554458372517 & 21.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287335&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]99.9916666666667[/C][C]2.95649003606191[/C][C]11.9[/C][/ROW]
[ROW][C]2[/C][C]117.75[/C][C]3.54003081650686[/C][C]12.6[/C][/ROW]
[ROW][C]3[/C][C]127.308333333333[/C][C]2.70234185756568[/C][C]9.60000000000001[/C][/ROW]
[ROW][C]4[/C][C]122.366666666667[/C][C]2.76120307551662[/C][C]8.59999999999999[/C][/ROW]
[ROW][C]5[/C][C]113.633333333333[/C][C]5.82554458372517[/C][C]21.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287335&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287335&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	99.9916666666667	2.95649003606191	11.9
2	117.75	3.54003081650686	12.6
3	127.308333333333	2.70234185756568	9.60000000000001
4	122.366666666667	2.76120307551662	8.59999999999999
5	113.633333333333	5.82554458372517	21.2

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	6.37887884649697
beta	-0.0242815314742425
S.D.	0.0713538270251261
T-STAT	-0.340297535347224
p-value	0.756067240124609

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.37887884649697 \tabularnewline
beta & -0.0242815314742425 \tabularnewline
S.D. & 0.0713538270251261 \tabularnewline
T-STAT & -0.340297535347224 \tabularnewline
p-value & 0.756067240124609 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287335&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.37887884649697[/C][/ROW]
[ROW][C]beta[/C][C]-0.0242815314742425[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0713538270251261[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.340297535347224[/C][/ROW]
[ROW][C]p-value[/C][C]0.756067240124609[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287335&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287335&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	6.37887884649697
beta	-0.0242815314742425
S.D.	0.0713538270251261
T-STAT	-0.340297535347224
p-value	0.756067240124609

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	4.31153663248898
beta	-0.64971958678812
S.D.	1.95653149913573
T-STAT	-0.332077243364149
p-value	0.761679188235777
Lambda	1.64971958678812

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.31153663248898 \tabularnewline
beta & -0.64971958678812 \tabularnewline
S.D. & 1.95653149913573 \tabularnewline
T-STAT & -0.332077243364149 \tabularnewline
p-value & 0.761679188235777 \tabularnewline
Lambda & 1.64971958678812 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=287335&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.31153663248898[/C][/ROW]
[ROW][C]beta[/C][C]-0.64971958678812[/C][/ROW]
[ROW][C]S.D.[/C][C]1.95653149913573[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.332077243364149[/C][/ROW]
[ROW][C]p-value[/C][C]0.761679188235777[/C][/ROW]
[ROW][C]Lambda[/C][C]1.64971958678812[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=287335&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=287335&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	4.31153663248898
beta	-0.64971958678812
S.D.	1.95653149913573
T-STAT	-0.332077243364149
p-value	0.761679188235777
Lambda	1.64971958678812

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