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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

Sun, 21 Dec 2008 10:46:26 -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/21/t1229881635vd4oy5wa1ne48nm.htm/, Retrieved Sun, 19 May 2024 11:15:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35708, Retrieved Sun, 19 May 2024 11:15:01 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

129

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

-       [Standard Deviation-Mean Plot] [] [2008-12-21 17:46:26] [a2d5a6282476ec2b5afae6fb53d308f8] [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	'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=35708&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=35708&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35708&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	1.0398	0.0357995344476246	0.0758999999999999
2	1.1225	0.0460487422919091	0.0855999999999999
3	1.135625	0.0243718929643692	0.0553000000000001
4	1.231175	0.0437771915499385	0.0944
5	1.2098	0.0128511996845949	0.0277000000000001
6	1.22875	0.0139917833030676	0.0314000000000001
7	1.3133	0.0191612456101720	0.0417000000000001
8	1.27495	0.0441250118035868	0.103600000000000
9	1.215	0.0144215117099422	0.0277000000000001
10	1.192075	0.0136458479643687	0.0316999999999998
11	1.242775	0.0345138015871911	0.075
12	1.270825	0.0083575813885756	0.0199999999999998
13	1.304175	0.0139086004567917	0.0331999999999999
14	1.3422	0.0128018227868794	0.0273999999999999
15	1.386525	0.0266617547559546	0.0605

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.0398 & 0.0357995344476246 & 0.0758999999999999 \tabularnewline
2 & 1.1225 & 0.0460487422919091 & 0.0855999999999999 \tabularnewline
3 & 1.135625 & 0.0243718929643692 & 0.0553000000000001 \tabularnewline
4 & 1.231175 & 0.0437771915499385 & 0.0944 \tabularnewline
5 & 1.2098 & 0.0128511996845949 & 0.0277000000000001 \tabularnewline
6 & 1.22875 & 0.0139917833030676 & 0.0314000000000001 \tabularnewline
7 & 1.3133 & 0.0191612456101720 & 0.0417000000000001 \tabularnewline
8 & 1.27495 & 0.0441250118035868 & 0.103600000000000 \tabularnewline
9 & 1.215 & 0.0144215117099422 & 0.0277000000000001 \tabularnewline
10 & 1.192075 & 0.0136458479643687 & 0.0316999999999998 \tabularnewline
11 & 1.242775 & 0.0345138015871911 & 0.075 \tabularnewline
12 & 1.270825 & 0.0083575813885756 & 0.0199999999999998 \tabularnewline
13 & 1.304175 & 0.0139086004567917 & 0.0331999999999999 \tabularnewline
14 & 1.3422 & 0.0128018227868794 & 0.0273999999999999 \tabularnewline
15 & 1.386525 & 0.0266617547559546 & 0.0605 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35708&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]1.0398[/C][C]0.0357995344476246[/C][C]0.0758999999999999[/C][/ROW]
[ROW][C]2[/C][C]1.1225[/C][C]0.0460487422919091[/C][C]0.0855999999999999[/C][/ROW]
[ROW][C]3[/C][C]1.135625[/C][C]0.0243718929643692[/C][C]0.0553000000000001[/C][/ROW]
[ROW][C]4[/C][C]1.231175[/C][C]0.0437771915499385[/C][C]0.0944[/C][/ROW]
[ROW][C]5[/C][C]1.2098[/C][C]0.0128511996845949[/C][C]0.0277000000000001[/C][/ROW]
[ROW][C]6[/C][C]1.22875[/C][C]0.0139917833030676[/C][C]0.0314000000000001[/C][/ROW]
[ROW][C]7[/C][C]1.3133[/C][C]0.0191612456101720[/C][C]0.0417000000000001[/C][/ROW]
[ROW][C]8[/C][C]1.27495[/C][C]0.0441250118035868[/C][C]0.103600000000000[/C][/ROW]
[ROW][C]9[/C][C]1.215[/C][C]0.0144215117099422[/C][C]0.0277000000000001[/C][/ROW]
[ROW][C]10[/C][C]1.192075[/C][C]0.0136458479643687[/C][C]0.0316999999999998[/C][/ROW]
[ROW][C]11[/C][C]1.242775[/C][C]0.0345138015871911[/C][C]0.075[/C][/ROW]
[ROW][C]12[/C][C]1.270825[/C][C]0.0083575813885756[/C][C]0.0199999999999998[/C][/ROW]
[ROW][C]13[/C][C]1.304175[/C][C]0.0139086004567917[/C][C]0.0331999999999999[/C][/ROW]
[ROW][C]14[/C][C]1.3422[/C][C]0.0128018227868794[/C][C]0.0273999999999999[/C][/ROW]
[ROW][C]15[/C][C]1.386525[/C][C]0.0266617547559546[/C][C]0.0605[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35708&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35708&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	1.0398	0.0357995344476246	0.0758999999999999
2	1.1225	0.0460487422919091	0.0855999999999999
3	1.135625	0.0243718929643692	0.0553000000000001
4	1.231175	0.0437771915499385	0.0944
5	1.2098	0.0128511996845949	0.0277000000000001
6	1.22875	0.0139917833030676	0.0314000000000001
7	1.3133	0.0191612456101720	0.0417000000000001
8	1.27495	0.0441250118035868	0.103600000000000
9	1.215	0.0144215117099422	0.0277000000000001
10	1.192075	0.0136458479643687	0.0316999999999998
11	1.242775	0.0345138015871911	0.075
12	1.270825	0.0083575813885756	0.0199999999999998
13	1.304175	0.0139086004567917	0.0331999999999999
14	1.3422	0.0128018227868794	0.0273999999999999
15	1.386525	0.0266617547559546	0.0605

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.0845388581533763
beta	-0.0488206904839645
S.D.	0.0388087740509309
T-STAT	-1.25798074476391
p-value	0.230525474964412

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0845388581533763 \tabularnewline
beta & -0.0488206904839645 \tabularnewline
S.D. & 0.0388087740509309 \tabularnewline
T-STAT & -1.25798074476391 \tabularnewline
p-value & 0.230525474964412 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35708&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0845388581533763[/C][/ROW]
[ROW][C]beta[/C][C]-0.0488206904839645[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0388087740509309[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.25798074476391[/C][/ROW]
[ROW][C]p-value[/C][C]0.230525474964412[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35708&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35708&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	0.0845388581533763
beta	-0.0488206904839645
S.D.	0.0388087740509309
T-STAT	-1.25798074476391
p-value	0.230525474964412

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.34629768681413
beta	-2.47060540864055
S.D.	1.96892914857714
T-STAT	-1.25479650216258
p-value	0.231642887910537
Lambda	3.47060540864055

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.34629768681413 \tabularnewline
beta & -2.47060540864055 \tabularnewline
S.D. & 1.96892914857714 \tabularnewline
T-STAT & -1.25479650216258 \tabularnewline
p-value & 0.231642887910537 \tabularnewline
Lambda & 3.47060540864055 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35708&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.34629768681413[/C][/ROW]
[ROW][C]beta[/C][C]-2.47060540864055[/C][/ROW]
[ROW][C]S.D.[/C][C]1.96892914857714[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.25479650216258[/C][/ROW]
[ROW][C]p-value[/C][C]0.231642887910537[/C][/ROW]
[ROW][C]Lambda[/C][C]3.47060540864055[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35708&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35708&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	-3.34629768681413
beta	-2.47060540864055
S.D.	1.96892914857714
T-STAT	-1.25479650216258
p-value	0.231642887910537
Lambda	3.47060540864055

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