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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

Thu, 22 Dec 2011 09:18:57 -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/Dec/22/t1324563564vwrg5bb7zm289a6.htm/, Retrieved Fri, 03 May 2024 14:20:04 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159494, Retrieved Fri, 03 May 2024 14:20:04 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

108

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

-       [Standard Deviation-Mean Plot] [SMP 1] [2011-12-22 14:18:57] [8ccb8599b802845e9be7b9afcc742f78] [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	0 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 & 0 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159494&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]0 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=159494&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159494&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	0 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	9402	369.34626932821	662
2	9469.75	615.153842546724	1411
3	9661.25	376.667293509803	786
4	9348	323.952671440341	702
5	9139.25	403.51156530307	927
6	9430.5	476.178187936687	1118
7	9256.5	447.117061480175	965
8	9081.25	386.892211518057	923
9	9634.25	389.218340609312	892
10	9351.75	421.869944414152	948
11	9241.5	297.687196007263	653
12	10017	238.695063487566	524
13	9649.5	268.500155183071	651
14	9677.5	471.217218134765	1141
15	10098.25	235.011169947303	540
16	9823.75	395.32802835114	846
17	9903	628.399554423776	1296
18	10424.75	209.087501619139	444

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9402 & 369.34626932821 & 662 \tabularnewline
2 & 9469.75 & 615.153842546724 & 1411 \tabularnewline
3 & 9661.25 & 376.667293509803 & 786 \tabularnewline
4 & 9348 & 323.952671440341 & 702 \tabularnewline
5 & 9139.25 & 403.51156530307 & 927 \tabularnewline
6 & 9430.5 & 476.178187936687 & 1118 \tabularnewline
7 & 9256.5 & 447.117061480175 & 965 \tabularnewline
8 & 9081.25 & 386.892211518057 & 923 \tabularnewline
9 & 9634.25 & 389.218340609312 & 892 \tabularnewline
10 & 9351.75 & 421.869944414152 & 948 \tabularnewline
11 & 9241.5 & 297.687196007263 & 653 \tabularnewline
12 & 10017 & 238.695063487566 & 524 \tabularnewline
13 & 9649.5 & 268.500155183071 & 651 \tabularnewline
14 & 9677.5 & 471.217218134765 & 1141 \tabularnewline
15 & 10098.25 & 235.011169947303 & 540 \tabularnewline
16 & 9823.75 & 395.32802835114 & 846 \tabularnewline
17 & 9903 & 628.399554423776 & 1296 \tabularnewline
18 & 10424.75 & 209.087501619139 & 444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159494&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]9402[/C][C]369.34626932821[/C][C]662[/C][/ROW]
[ROW][C]2[/C][C]9469.75[/C][C]615.153842546724[/C][C]1411[/C][/ROW]
[ROW][C]3[/C][C]9661.25[/C][C]376.667293509803[/C][C]786[/C][/ROW]
[ROW][C]4[/C][C]9348[/C][C]323.952671440341[/C][C]702[/C][/ROW]
[ROW][C]5[/C][C]9139.25[/C][C]403.51156530307[/C][C]927[/C][/ROW]
[ROW][C]6[/C][C]9430.5[/C][C]476.178187936687[/C][C]1118[/C][/ROW]
[ROW][C]7[/C][C]9256.5[/C][C]447.117061480175[/C][C]965[/C][/ROW]
[ROW][C]8[/C][C]9081.25[/C][C]386.892211518057[/C][C]923[/C][/ROW]
[ROW][C]9[/C][C]9634.25[/C][C]389.218340609312[/C][C]892[/C][/ROW]
[ROW][C]10[/C][C]9351.75[/C][C]421.869944414152[/C][C]948[/C][/ROW]
[ROW][C]11[/C][C]9241.5[/C][C]297.687196007263[/C][C]653[/C][/ROW]
[ROW][C]12[/C][C]10017[/C][C]238.695063487566[/C][C]524[/C][/ROW]
[ROW][C]13[/C][C]9649.5[/C][C]268.500155183071[/C][C]651[/C][/ROW]
[ROW][C]14[/C][C]9677.5[/C][C]471.217218134765[/C][C]1141[/C][/ROW]
[ROW][C]15[/C][C]10098.25[/C][C]235.011169947303[/C][C]540[/C][/ROW]
[ROW][C]16[/C][C]9823.75[/C][C]395.32802835114[/C][C]846[/C][/ROW]
[ROW][C]17[/C][C]9903[/C][C]628.399554423776[/C][C]1296[/C][/ROW]
[ROW][C]18[/C][C]10424.75[/C][C]209.087501619139[/C][C]444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159494&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159494&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	9402	369.34626932821	662
2	9469.75	615.153842546724	1411
3	9661.25	376.667293509803	786
4	9348	323.952671440341	702
5	9139.25	403.51156530307	927
6	9430.5	476.178187936687	1118
7	9256.5	447.117061480175	965
8	9081.25	386.892211518057	923
9	9634.25	389.218340609312	892
10	9351.75	421.869944414152	948
11	9241.5	297.687196007263	653
12	10017	238.695063487566	524
13	9649.5	268.500155183071	651
14	9677.5	471.217218134765	1141
15	10098.25	235.011169947303	540
16	9823.75	395.32802835114	846
17	9903	628.399554423776	1296
18	10424.75	209.087501619139	444

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1433.82623429448
beta	-0.109235074739753
S.D.	0.0768964203251652
T-STAT	-1.42054824239984
p-value	0.17464245335337

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1433.82623429448 \tabularnewline
beta & -0.109235074739753 \tabularnewline
S.D. & 0.0768964203251652 \tabularnewline
T-STAT & -1.42054824239984 \tabularnewline
p-value & 0.17464245335337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159494&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1433.82623429448[/C][/ROW]
[ROW][C]beta[/C][C]-0.109235074739753[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0768964203251652[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.42054824239984[/C][/ROW]
[ROW][C]p-value[/C][C]0.17464245335337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159494&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159494&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	1433.82623429448
beta	-0.109235074739753
S.D.	0.0768964203251652
T-STAT	-1.42054824239984
p-value	0.17464245335337

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	39.9658049526387
beta	-3.71445522546434
S.D.	1.86518172850041
T-STAT	-1.99147094822269
p-value	0.0637846472968771
Lambda	4.71445522546434

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 39.9658049526387 \tabularnewline
beta & -3.71445522546434 \tabularnewline
S.D. & 1.86518172850041 \tabularnewline
T-STAT & -1.99147094822269 \tabularnewline
p-value & 0.0637846472968771 \tabularnewline
Lambda & 4.71445522546434 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159494&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]39.9658049526387[/C][/ROW]
[ROW][C]beta[/C][C]-3.71445522546434[/C][/ROW]
[ROW][C]S.D.[/C][C]1.86518172850041[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.99147094822269[/C][/ROW]
[ROW][C]p-value[/C][C]0.0637846472968771[/C][/ROW]
[ROW][C]Lambda[/C][C]4.71445522546434[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159494&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159494&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	39.9658049526387
beta	-3.71445522546434
S.D.	1.86518172850041
T-STAT	-1.99147094822269
p-value	0.0637846472968771
Lambda	4.71445522546434

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