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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

Fri, 13 Jul 2012 06:24:06 -0400

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/2012/Jul/13/t13421751255b0pddbx8gd9lpi.htm/, Retrieved Sun, 28 Apr 2024 01:56:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168799, Retrieved Sun, 28 Apr 2024 01:56:12 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Margot Avonts

Estimated Impact

175

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

-       [Standard Deviation-Mean Plot] [Tijdreeks 2 - sta...] [2012-07-13 10:24:06] [f26bc165187ae19198203e315c1ca52f] [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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168799&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168799&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168799&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	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1155.83333333333	51.2495380614806	170
2	1149.16666666667	72.1687836487032	280
3	1141.66666666667	95.2349566582406	350
4	1123.33333333333	99.7572811954854	340
5	1155	90.6040336248387	300
6	1172.5	143.281350686492	480
7	1181.66666666667	161.010069325625	530
8	1204.16666666667	159.342874064551	550
9	1185	173.283792454092	590

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1155.83333333333 & 51.2495380614806 & 170 \tabularnewline
2 & 1149.16666666667 & 72.1687836487032 & 280 \tabularnewline
3 & 1141.66666666667 & 95.2349566582406 & 350 \tabularnewline
4 & 1123.33333333333 & 99.7572811954854 & 340 \tabularnewline
5 & 1155 & 90.6040336248387 & 300 \tabularnewline
6 & 1172.5 & 143.281350686492 & 480 \tabularnewline
7 & 1181.66666666667 & 161.010069325625 & 530 \tabularnewline
8 & 1204.16666666667 & 159.342874064551 & 550 \tabularnewline
9 & 1185 & 173.283792454092 & 590 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168799&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]1155.83333333333[/C][C]51.2495380614806[/C][C]170[/C][/ROW]
[ROW][C]2[/C][C]1149.16666666667[/C][C]72.1687836487032[/C][C]280[/C][/ROW]
[ROW][C]3[/C][C]1141.66666666667[/C][C]95.2349566582406[/C][C]350[/C][/ROW]
[ROW][C]4[/C][C]1123.33333333333[/C][C]99.7572811954854[/C][C]340[/C][/ROW]
[ROW][C]5[/C][C]1155[/C][C]90.6040336248387[/C][C]300[/C][/ROW]
[ROW][C]6[/C][C]1172.5[/C][C]143.281350686492[/C][C]480[/C][/ROW]
[ROW][C]7[/C][C]1181.66666666667[/C][C]161.010069325625[/C][C]530[/C][/ROW]
[ROW][C]8[/C][C]1204.16666666667[/C][C]159.342874064551[/C][C]550[/C][/ROW]
[ROW][C]9[/C][C]1185[/C][C]173.283792454092[/C][C]590[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168799&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168799&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	1155.83333333333	51.2495380614806	170
2	1149.16666666667	72.1687836487032	280
3	1141.66666666667	95.2349566582406	350
4	1123.33333333333	99.7572811954854	340
5	1155	90.6040336248387	300
6	1172.5	143.281350686492	480
7	1181.66666666667	161.010069325625	530
8	1204.16666666667	159.342874064551	550
9	1185	173.283792454092	590

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-1411.42956430004
beta	1.31337036380384
S.D.	0.44421682963962
T-STAT	2.95659749062039
p-value	0.0212072422683443

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1411.42956430004 \tabularnewline
beta & 1.31337036380384 \tabularnewline
S.D. & 0.44421682963962 \tabularnewline
T-STAT & 2.95659749062039 \tabularnewline
p-value & 0.0212072422683443 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168799&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1411.42956430004[/C][/ROW]
[ROW][C]beta[/C][C]1.31337036380384[/C][/ROW]
[ROW][C]S.D.[/C][C]0.44421682963962[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.95659749062039[/C][/ROW]
[ROW][C]p-value[/C][C]0.0212072422683443[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168799&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168799&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	-1411.42956430004
beta	1.31337036380384
S.D.	0.44421682963962
T-STAT	2.95659749062039
p-value	0.0212072422683443

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-85.6049445956681
beta	12.7911514151912
S.D.	5.54467117946559
T-STAT	2.30692695764585
p-value	0.0544326791375776
Lambda	-11.7911514151912

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -85.6049445956681 \tabularnewline
beta & 12.7911514151912 \tabularnewline
S.D. & 5.54467117946559 \tabularnewline
T-STAT & 2.30692695764585 \tabularnewline
p-value & 0.0544326791375776 \tabularnewline
Lambda & -11.7911514151912 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168799&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-85.6049445956681[/C][/ROW]
[ROW][C]beta[/C][C]12.7911514151912[/C][/ROW]
[ROW][C]S.D.[/C][C]5.54467117946559[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.30692695764585[/C][/ROW]
[ROW][C]p-value[/C][C]0.0544326791375776[/C][/ROW]
[ROW][C]Lambda[/C][C]-11.7911514151912[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168799&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168799&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	-85.6049445956681
beta	12.7911514151912
S.D.	5.54467117946559
T-STAT	2.30692695764585
p-value	0.0544326791375776
Lambda	-11.7911514151912

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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