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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

Fri, 27 Nov 2009 06:10:49 -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/2009/Nov/27/t1259327584fbhf1a6vvi45aat.htm/, Retrieved Sun, 28 Apr 2024 22:00:55 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60713, Retrieved Sun, 28 Apr 2024 22:00:55 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

141

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

-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Spectral Analysis] [Identifying Integ...] [2009-11-22 12:38:17] [b98453cac15ba1066b407e146608df68]
- RMPD          [Standard Deviation-Mean Plot] [WS 8 standard dev...] [2009-11-27 13:10:49] [51d49d3536f6a59f2486a67bf50b2759] [Current]
-   P             [Standard Deviation-Mean Plot] [WS 9 SD] [2009-12-01 18:18:56] [12f02da0296cb21dc23d82ae014a8b71] 

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Boxplots

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' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60713&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60713&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60713&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' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1644.5	206.619618300554	506
2	1619.75	194.373137718839	424
3	1936.25	258.03794940538	564
4	1985	23.1516738055805	54
5	1542.75	121.705587382010	287
6	1823.5	303.052800680013	730
7	2196	121.243556529821	294
8	1709.75	74.6653645719799	159
9	2017.5	329.854008110659	796
10	2553	178.779193420264	435
11	2143.25	315.078164905155	685
12	2140.25	243.996413908074	549
13	1865.25	331.285752787529	756
14	2062.5	35.4635963583316	78
15	1844.5	306.242278814231	725

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1644.5 & 206.619618300554 & 506 \tabularnewline
2 & 1619.75 & 194.373137718839 & 424 \tabularnewline
3 & 1936.25 & 258.03794940538 & 564 \tabularnewline
4 & 1985 & 23.1516738055805 & 54 \tabularnewline
5 & 1542.75 & 121.705587382010 & 287 \tabularnewline
6 & 1823.5 & 303.052800680013 & 730 \tabularnewline
7 & 2196 & 121.243556529821 & 294 \tabularnewline
8 & 1709.75 & 74.6653645719799 & 159 \tabularnewline
9 & 2017.5 & 329.854008110659 & 796 \tabularnewline
10 & 2553 & 178.779193420264 & 435 \tabularnewline
11 & 2143.25 & 315.078164905155 & 685 \tabularnewline
12 & 2140.25 & 243.996413908074 & 549 \tabularnewline
13 & 1865.25 & 331.285752787529 & 756 \tabularnewline
14 & 2062.5 & 35.4635963583316 & 78 \tabularnewline
15 & 1844.5 & 306.242278814231 & 725 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60713&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]1644.5[/C][C]206.619618300554[/C][C]506[/C][/ROW]
[ROW][C]2[/C][C]1619.75[/C][C]194.373137718839[/C][C]424[/C][/ROW]
[ROW][C]3[/C][C]1936.25[/C][C]258.03794940538[/C][C]564[/C][/ROW]
[ROW][C]4[/C][C]1985[/C][C]23.1516738055805[/C][C]54[/C][/ROW]
[ROW][C]5[/C][C]1542.75[/C][C]121.705587382010[/C][C]287[/C][/ROW]
[ROW][C]6[/C][C]1823.5[/C][C]303.052800680013[/C][C]730[/C][/ROW]
[ROW][C]7[/C][C]2196[/C][C]121.243556529821[/C][C]294[/C][/ROW]
[ROW][C]8[/C][C]1709.75[/C][C]74.6653645719799[/C][C]159[/C][/ROW]
[ROW][C]9[/C][C]2017.5[/C][C]329.854008110659[/C][C]796[/C][/ROW]
[ROW][C]10[/C][C]2553[/C][C]178.779193420264[/C][C]435[/C][/ROW]
[ROW][C]11[/C][C]2143.25[/C][C]315.078164905155[/C][C]685[/C][/ROW]
[ROW][C]12[/C][C]2140.25[/C][C]243.996413908074[/C][C]549[/C][/ROW]
[ROW][C]13[/C][C]1865.25[/C][C]331.285752787529[/C][C]756[/C][/ROW]
[ROW][C]14[/C][C]2062.5[/C][C]35.4635963583316[/C][C]78[/C][/ROW]
[ROW][C]15[/C][C]1844.5[/C][C]306.242278814231[/C][C]725[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60713&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60713&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	1644.5	206.619618300554	506
2	1619.75	194.373137718839	424
3	1936.25	258.03794940538	564
4	1985	23.1516738055805	54
5	1542.75	121.705587382010	287
6	1823.5	303.052800680013	730
7	2196	121.243556529821	294
8	1709.75	74.6653645719799	159
9	2017.5	329.854008110659	796
10	2553	178.779193420264	435
11	2143.25	315.078164905155	685
12	2140.25	243.996413908074	549
13	1865.25	331.285752787529	756
14	2062.5	35.4635963583316	78
15	1844.5	306.242278814231	725

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	185.695860374087
beta	0.00887475621565696
S.D.	0.112811706327625
T-STAT	0.0786687526016413
p-value	0.938494131704607

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 185.695860374087 \tabularnewline
beta & 0.00887475621565696 \tabularnewline
S.D. & 0.112811706327625 \tabularnewline
T-STAT & 0.0786687526016413 \tabularnewline
p-value & 0.938494131704607 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60713&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]185.695860374087[/C][/ROW]
[ROW][C]beta[/C][C]0.00887475621565696[/C][/ROW]
[ROW][C]S.D.[/C][C]0.112811706327625[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0786687526016413[/C][/ROW]
[ROW][C]p-value[/C][C]0.938494131704607[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60713&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60713&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	185.695860374087
beta	0.00887475621565696
S.D.	0.112811706327625
T-STAT	0.0786687526016413
p-value	0.938494131704607

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	5.75477265400287
beta	-0.0887730853191597
S.D.	1.71467997990388
T-STAT	-0.051772392726097
p-value	0.959497131950492
Lambda	1.08877308531916

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.75477265400287 \tabularnewline
beta & -0.0887730853191597 \tabularnewline
S.D. & 1.71467997990388 \tabularnewline
T-STAT & -0.051772392726097 \tabularnewline
p-value & 0.959497131950492 \tabularnewline
Lambda & 1.08877308531916 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60713&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.75477265400287[/C][/ROW]
[ROW][C]beta[/C][C]-0.0887730853191597[/C][/ROW]
[ROW][C]S.D.[/C][C]1.71467997990388[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.051772392726097[/C][/ROW]
[ROW][C]p-value[/C][C]0.959497131950492[/C][/ROW]
[ROW][C]Lambda[/C][C]1.08877308531916[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60713&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60713&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	5.75477265400287
beta	-0.0887730853191597
S.D.	1.71467997990388
T-STAT	-0.051772392726097
p-value	0.959497131950492
Lambda	1.08877308531916

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