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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

Sun, 21 Dec 2008 05:35:26 -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/t1229864515ri0mqkl2dt6e5jx.htm/, Retrieved Fri, 17 May 2024 03:41:27 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35543, Retrieved Fri, 17 May 2024 03:41:27 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

156

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

-       [Standard Deviation-Mean Plot] [SMP Energie] [2008-12-21 12:35:26] [9c9e716fef59bf95ba5b3e37a9a90be4] [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' @ 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=35543&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=35543&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35543&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	95.95	0.737111479583204	1.80000000000001
2	96.9	1.28322510366134	2.5
3	106.1	3.33266659998666	7
4	117.55	4.0542159126848	8.8
5	116.225	3.49892840738418	7.1
6	121.05	3.18799832705937	7.2
7	132.125	4.20347078813053	10
8	137.8	3.94799527186478	8.19999999999999
9	142.75	0.932737905308877	1.79999999999998
10	136.625	3.0510927004381	6.69999999999999
11	133.325	1.21209185570511	2.5
12	136.55	1.22882057274445	3
13	144.425	6.5525440352075	15
14	161.95	4.38292140016222	10.2000000000000
15	178.4	8.00874522007038	18.1000000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 95.95 & 0.737111479583204 & 1.80000000000001 \tabularnewline
2 & 96.9 & 1.28322510366134 & 2.5 \tabularnewline
3 & 106.1 & 3.33266659998666 & 7 \tabularnewline
4 & 117.55 & 4.0542159126848 & 8.8 \tabularnewline
5 & 116.225 & 3.49892840738418 & 7.1 \tabularnewline
6 & 121.05 & 3.18799832705937 & 7.2 \tabularnewline
7 & 132.125 & 4.20347078813053 & 10 \tabularnewline
8 & 137.8 & 3.94799527186478 & 8.19999999999999 \tabularnewline
9 & 142.75 & 0.932737905308877 & 1.79999999999998 \tabularnewline
10 & 136.625 & 3.0510927004381 & 6.69999999999999 \tabularnewline
11 & 133.325 & 1.21209185570511 & 2.5 \tabularnewline
12 & 136.55 & 1.22882057274445 & 3 \tabularnewline
13 & 144.425 & 6.5525440352075 & 15 \tabularnewline
14 & 161.95 & 4.38292140016222 & 10.2000000000000 \tabularnewline
15 & 178.4 & 8.00874522007038 & 18.1000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35543&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]95.95[/C][C]0.737111479583204[/C][C]1.80000000000001[/C][/ROW]
[ROW][C]2[/C][C]96.9[/C][C]1.28322510366134[/C][C]2.5[/C][/ROW]
[ROW][C]3[/C][C]106.1[/C][C]3.33266659998666[/C][C]7[/C][/ROW]
[ROW][C]4[/C][C]117.55[/C][C]4.0542159126848[/C][C]8.8[/C][/ROW]
[ROW][C]5[/C][C]116.225[/C][C]3.49892840738418[/C][C]7.1[/C][/ROW]
[ROW][C]6[/C][C]121.05[/C][C]3.18799832705937[/C][C]7.2[/C][/ROW]
[ROW][C]7[/C][C]132.125[/C][C]4.20347078813053[/C][C]10[/C][/ROW]
[ROW][C]8[/C][C]137.8[/C][C]3.94799527186478[/C][C]8.19999999999999[/C][/ROW]
[ROW][C]9[/C][C]142.75[/C][C]0.932737905308877[/C][C]1.79999999999998[/C][/ROW]
[ROW][C]10[/C][C]136.625[/C][C]3.0510927004381[/C][C]6.69999999999999[/C][/ROW]
[ROW][C]11[/C][C]133.325[/C][C]1.21209185570511[/C][C]2.5[/C][/ROW]
[ROW][C]12[/C][C]136.55[/C][C]1.22882057274445[/C][C]3[/C][/ROW]
[ROW][C]13[/C][C]144.425[/C][C]6.5525440352075[/C][C]15[/C][/ROW]
[ROW][C]14[/C][C]161.95[/C][C]4.38292140016222[/C][C]10.2000000000000[/C][/ROW]
[ROW][C]15[/C][C]178.4[/C][C]8.00874522007038[/C][C]18.1000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35543&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35543&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	95.95	0.737111479583204	1.80000000000001
2	96.9	1.28322510366134	2.5
3	106.1	3.33266659998666	7
4	117.55	4.0542159126848	8.8
5	116.225	3.49892840738418	7.1
6	121.05	3.18799832705937	7.2
7	132.125	4.20347078813053	10
8	137.8	3.94799527186478	8.19999999999999
9	142.75	0.932737905308877	1.79999999999998
10	136.625	3.0510927004381	6.69999999999999
11	133.325	1.21209185570511	2.5
12	136.55	1.22882057274445	3
13	144.425	6.5525440352075	15
14	161.95	4.38292140016222	10.2000000000000
15	178.4	8.00874522007038	18.1000000000000

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-4.11131285550537
beta	0.0568436621142255
S.D.	0.0201333469121933
T-STAT	2.8233587968327
p-value	0.0143722856849662

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.11131285550537 \tabularnewline
beta & 0.0568436621142255 \tabularnewline
S.D. & 0.0201333469121933 \tabularnewline
T-STAT & 2.8233587968327 \tabularnewline
p-value & 0.0143722856849662 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35543&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.11131285550537[/C][/ROW]
[ROW][C]beta[/C][C]0.0568436621142255[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0201333469121933[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.8233587968327[/C][/ROW]
[ROW][C]p-value[/C][C]0.0143722856849662[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35543&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35543&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	-4.11131285550537
beta	0.0568436621142255
S.D.	0.0201333469121933
T-STAT	2.8233587968327
p-value	0.0143722856849662

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-9.42128622093374
beta	2.14063134957169
S.D.	1.00369393465465
T-STAT	2.13275309898952
p-value	0.052585033566077
Lambda	-1.14063134957169

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.42128622093374 \tabularnewline
beta & 2.14063134957169 \tabularnewline
S.D. & 1.00369393465465 \tabularnewline
T-STAT & 2.13275309898952 \tabularnewline
p-value & 0.052585033566077 \tabularnewline
Lambda & -1.14063134957169 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35543&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.42128622093374[/C][/ROW]
[ROW][C]beta[/C][C]2.14063134957169[/C][/ROW]
[ROW][C]S.D.[/C][C]1.00369393465465[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.13275309898952[/C][/ROW]
[ROW][C]p-value[/C][C]0.052585033566077[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.14063134957169[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35543&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35543&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	-9.42128622093374
beta	2.14063134957169
S.D.	1.00369393465465
T-STAT	2.13275309898952
p-value	0.052585033566077
Lambda	-1.14063134957169

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

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code