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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

Mon, 28 Nov 2011 08:45:37 -0500

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/2011/Nov/28/t1322487994fw061hbnzr4wd9e.htm/, Retrieved Tue, 30 Apr 2024 17:55:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147725, Retrieved Tue, 30 Apr 2024 17:55:10 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [] [2011-11-28 13:45:37] [c81f0c87bb000ca3e7f952ee43cfaf8d] [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	'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147725&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147725&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147725&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	100.4125	0.494663185073105	1.15000000000001
2	101.0475	0.0427200187265887	0.0900000000000034
3	101.0775	0.135984067694221	0.310000000000002
4	101.1675	0.114418821295571	0.220000000000013
5	101.6625	0.00500000000000256	0.0100000000000051
6	102.225	0.285365263010994	0.600000000000009
7	102.7	0.207364413533276	0.429999999999993
8	102.9875	0.02986078811195	0.0700000000000074
9	103.4575	0.139134227756265	0.319999999999993
10	103.58	0.107082522694725	0.219999999999999
11	103.91	0.019999999999996	0.039999999999992
12	104.5175	0.460099626892551	1
13	105.06	0.150775771705313	0.349999999999994
14	104.6975	0.0895823643358502	0.190000000000012
15	104.5675	0.136961065027012	0.299999999999997

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.4125 & 0.494663185073105 & 1.15000000000001 \tabularnewline
2 & 101.0475 & 0.0427200187265887 & 0.0900000000000034 \tabularnewline
3 & 101.0775 & 0.135984067694221 & 0.310000000000002 \tabularnewline
4 & 101.1675 & 0.114418821295571 & 0.220000000000013 \tabularnewline
5 & 101.6625 & 0.00500000000000256 & 0.0100000000000051 \tabularnewline
6 & 102.225 & 0.285365263010994 & 0.600000000000009 \tabularnewline
7 & 102.7 & 0.207364413533276 & 0.429999999999993 \tabularnewline
8 & 102.9875 & 0.02986078811195 & 0.0700000000000074 \tabularnewline
9 & 103.4575 & 0.139134227756265 & 0.319999999999993 \tabularnewline
10 & 103.58 & 0.107082522694725 & 0.219999999999999 \tabularnewline
11 & 103.91 & 0.019999999999996 & 0.039999999999992 \tabularnewline
12 & 104.5175 & 0.460099626892551 & 1 \tabularnewline
13 & 105.06 & 0.150775771705313 & 0.349999999999994 \tabularnewline
14 & 104.6975 & 0.0895823643358502 & 0.190000000000012 \tabularnewline
15 & 104.5675 & 0.136961065027012 & 0.299999999999997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147725&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]100.4125[/C][C]0.494663185073105[/C][C]1.15000000000001[/C][/ROW]
[ROW][C]2[/C][C]101.0475[/C][C]0.0427200187265887[/C][C]0.0900000000000034[/C][/ROW]
[ROW][C]3[/C][C]101.0775[/C][C]0.135984067694221[/C][C]0.310000000000002[/C][/ROW]
[ROW][C]4[/C][C]101.1675[/C][C]0.114418821295571[/C][C]0.220000000000013[/C][/ROW]
[ROW][C]5[/C][C]101.6625[/C][C]0.00500000000000256[/C][C]0.0100000000000051[/C][/ROW]
[ROW][C]6[/C][C]102.225[/C][C]0.285365263010994[/C][C]0.600000000000009[/C][/ROW]
[ROW][C]7[/C][C]102.7[/C][C]0.207364413533276[/C][C]0.429999999999993[/C][/ROW]
[ROW][C]8[/C][C]102.9875[/C][C]0.02986078811195[/C][C]0.0700000000000074[/C][/ROW]
[ROW][C]9[/C][C]103.4575[/C][C]0.139134227756265[/C][C]0.319999999999993[/C][/ROW]
[ROW][C]10[/C][C]103.58[/C][C]0.107082522694725[/C][C]0.219999999999999[/C][/ROW]
[ROW][C]11[/C][C]103.91[/C][C]0.019999999999996[/C][C]0.039999999999992[/C][/ROW]
[ROW][C]12[/C][C]104.5175[/C][C]0.460099626892551[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]105.06[/C][C]0.150775771705313[/C][C]0.349999999999994[/C][/ROW]
[ROW][C]14[/C][C]104.6975[/C][C]0.0895823643358502[/C][C]0.190000000000012[/C][/ROW]
[ROW][C]15[/C][C]104.5675[/C][C]0.136961065027012[/C][C]0.299999999999997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147725&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147725&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	100.4125	0.494663185073105	1.15000000000001
2	101.0475	0.0427200187265887	0.0900000000000034
3	101.0775	0.135984067694221	0.310000000000002
4	101.1675	0.114418821295571	0.220000000000013
5	101.6625	0.00500000000000256	0.0100000000000051
6	102.225	0.285365263010994	0.600000000000009
7	102.7	0.207364413533276	0.429999999999993
8	102.9875	0.02986078811195	0.0700000000000074
9	103.4575	0.139134227756265	0.319999999999993
10	103.58	0.107082522694725	0.219999999999999
11	103.91	0.019999999999996	0.039999999999992
12	104.5175	0.460099626892551	1
13	105.06	0.150775771705313	0.349999999999994
14	104.6975	0.0895823643358502	0.190000000000012
15	104.5675	0.136961065027012	0.299999999999997

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1.07670627156508
beta	-0.00889887168930686
S.D.	0.0265623517718798
T-STAT	-0.335018215470199
p-value	0.742955566894497

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.07670627156508 \tabularnewline
beta & -0.00889887168930686 \tabularnewline
S.D. & 0.0265623517718798 \tabularnewline
T-STAT & -0.335018215470199 \tabularnewline
p-value & 0.742955566894497 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147725&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.07670627156508[/C][/ROW]
[ROW][C]beta[/C][C]-0.00889887168930686[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0265623517718798[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.335018215470199[/C][/ROW]
[ROW][C]p-value[/C][C]0.742955566894497[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147725&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147725&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	1.07670627156508
beta	-0.00889887168930686
S.D.	0.0265623517718798
T-STAT	-0.335018215470199
p-value	0.742955566894497

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-27.9826906576591
beta	5.53802347944378
S.D.	22.5395271147487
T-STAT	0.245702735964677
p-value	0.809748808709169
Lambda	-4.53802347944378

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -27.9826906576591 \tabularnewline
beta & 5.53802347944378 \tabularnewline
S.D. & 22.5395271147487 \tabularnewline
T-STAT & 0.245702735964677 \tabularnewline
p-value & 0.809748808709169 \tabularnewline
Lambda & -4.53802347944378 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147725&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-27.9826906576591[/C][/ROW]
[ROW][C]beta[/C][C]5.53802347944378[/C][/ROW]
[ROW][C]S.D.[/C][C]22.5395271147487[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.245702735964677[/C][/ROW]
[ROW][C]p-value[/C][C]0.809748808709169[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.53802347944378[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147725&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147725&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	-27.9826906576591
beta	5.53802347944378
S.D.	22.5395271147487
T-STAT	0.245702735964677
p-value	0.809748808709169
Lambda	-4.53802347944378

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code