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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

Tue, 07 Dec 2010 22:38:51 +0000

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/2010/Dec/07/t12917614020g7bm0u8of4tqci.htm/, Retrieved Fri, 03 May 2024 18:56:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106797, Retrieved Fri, 03 May 2024 18:56:47 +0000

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Original text written by user:

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] [] [2010-12-07 22:38:51] [391aa7ca16a929f44adfa61e9db4be9d] [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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106797&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106797&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106797&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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	8150	1316.6176362179	3141
2	9582	1964.075524685	4647
3	10087	1045.62867851515	2503
4	8370.5	1186.80986963653	2615
5	9275.75	2370.89763240283	4987
6	10122.5	942.599420043672	1992
7	8160.25	580.102505309766	1300
8	10068.25	2755.56350861308	6104
9	10508.25	1466.54955024825	3090
10	8229.75	964.975776898052	2120
11	9913.5	3198.91820255953	6571
12	9949.75	2154.93253954735	4121
13	7693	371.602834578353	863
14	9445.25	2560.96041554726	5992
15	9370	1709.90428582031	3647
16	7510.75	1605.57868591566	3548
17	9998.25	3066.17474768372	6620
18	9496.75	1678.52005747126	3444

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8150 & 1316.6176362179 & 3141 \tabularnewline
2 & 9582 & 1964.075524685 & 4647 \tabularnewline
3 & 10087 & 1045.62867851515 & 2503 \tabularnewline
4 & 8370.5 & 1186.80986963653 & 2615 \tabularnewline
5 & 9275.75 & 2370.89763240283 & 4987 \tabularnewline
6 & 10122.5 & 942.599420043672 & 1992 \tabularnewline
7 & 8160.25 & 580.102505309766 & 1300 \tabularnewline
8 & 10068.25 & 2755.56350861308 & 6104 \tabularnewline
9 & 10508.25 & 1466.54955024825 & 3090 \tabularnewline
10 & 8229.75 & 964.975776898052 & 2120 \tabularnewline
11 & 9913.5 & 3198.91820255953 & 6571 \tabularnewline
12 & 9949.75 & 2154.93253954735 & 4121 \tabularnewline
13 & 7693 & 371.602834578353 & 863 \tabularnewline
14 & 9445.25 & 2560.96041554726 & 5992 \tabularnewline
15 & 9370 & 1709.90428582031 & 3647 \tabularnewline
16 & 7510.75 & 1605.57868591566 & 3548 \tabularnewline
17 & 9998.25 & 3066.17474768372 & 6620 \tabularnewline
18 & 9496.75 & 1678.52005747126 & 3444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106797&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]8150[/C][C]1316.6176362179[/C][C]3141[/C][/ROW]
[ROW][C]2[/C][C]9582[/C][C]1964.075524685[/C][C]4647[/C][/ROW]
[ROW][C]3[/C][C]10087[/C][C]1045.62867851515[/C][C]2503[/C][/ROW]
[ROW][C]4[/C][C]8370.5[/C][C]1186.80986963653[/C][C]2615[/C][/ROW]
[ROW][C]5[/C][C]9275.75[/C][C]2370.89763240283[/C][C]4987[/C][/ROW]
[ROW][C]6[/C][C]10122.5[/C][C]942.599420043672[/C][C]1992[/C][/ROW]
[ROW][C]7[/C][C]8160.25[/C][C]580.102505309766[/C][C]1300[/C][/ROW]
[ROW][C]8[/C][C]10068.25[/C][C]2755.56350861308[/C][C]6104[/C][/ROW]
[ROW][C]9[/C][C]10508.25[/C][C]1466.54955024825[/C][C]3090[/C][/ROW]
[ROW][C]10[/C][C]8229.75[/C][C]964.975776898052[/C][C]2120[/C][/ROW]
[ROW][C]11[/C][C]9913.5[/C][C]3198.91820255953[/C][C]6571[/C][/ROW]
[ROW][C]12[/C][C]9949.75[/C][C]2154.93253954735[/C][C]4121[/C][/ROW]
[ROW][C]13[/C][C]7693[/C][C]371.602834578353[/C][C]863[/C][/ROW]
[ROW][C]14[/C][C]9445.25[/C][C]2560.96041554726[/C][C]5992[/C][/ROW]
[ROW][C]15[/C][C]9370[/C][C]1709.90428582031[/C][C]3647[/C][/ROW]
[ROW][C]16[/C][C]7510.75[/C][C]1605.57868591566[/C][C]3548[/C][/ROW]
[ROW][C]17[/C][C]9998.25[/C][C]3066.17474768372[/C][C]6620[/C][/ROW]
[ROW][C]18[/C][C]9496.75[/C][C]1678.52005747126[/C][C]3444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106797&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106797&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	8150	1316.6176362179	3141
2	9582	1964.075524685	4647
3	10087	1045.62867851515	2503
4	8370.5	1186.80986963653	2615
5	9275.75	2370.89763240283	4987
6	10122.5	942.599420043672	1992
7	8160.25	580.102505309766	1300
8	10068.25	2755.56350861308	6104
9	10508.25	1466.54955024825	3090
10	8229.75	964.975776898052	2120
11	9913.5	3198.91820255953	6571
12	9949.75	2154.93253954735	4121
13	7693	371.602834578353	863
14	9445.25	2560.96041554726	5992
15	9370	1709.90428582031	3647
16	7510.75	1605.57868591566	3548
17	9998.25	3066.17474768372	6620
18	9496.75	1678.52005747126	3444

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-2594.40436707314
beta	0.467902058855674
S.D.	0.186908757326376
T-STAT	2.50337151425513
p-value	0.0235141589754351

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2594.40436707314 \tabularnewline
beta & 0.467902058855674 \tabularnewline
S.D. & 0.186908757326376 \tabularnewline
T-STAT & 2.50337151425513 \tabularnewline
p-value & 0.0235141589754351 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106797&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2594.40436707314[/C][/ROW]
[ROW][C]beta[/C][C]0.467902058855674[/C][/ROW]
[ROW][C]S.D.[/C][C]0.186908757326376[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.50337151425513[/C][/ROW]
[ROW][C]p-value[/C][C]0.0235141589754351[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106797&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106797&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	-2594.40436707314
beta	0.467902058855674
S.D.	0.186908757326376
T-STAT	2.50337151425513
p-value	0.0235141589754351

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-21.1529693261765
beta	3.12009326932861
S.D.	1.12174284461346
T-STAT	2.7814692862193
p-value	0.0133414245607614
Lambda	-2.12009326932861

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -21.1529693261765 \tabularnewline
beta & 3.12009326932861 \tabularnewline
S.D. & 1.12174284461346 \tabularnewline
T-STAT & 2.7814692862193 \tabularnewline
p-value & 0.0133414245607614 \tabularnewline
Lambda & -2.12009326932861 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106797&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-21.1529693261765[/C][/ROW]
[ROW][C]beta[/C][C]3.12009326932861[/C][/ROW]
[ROW][C]S.D.[/C][C]1.12174284461346[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.7814692862193[/C][/ROW]
[ROW][C]p-value[/C][C]0.0133414245607614[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.12009326932861[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106797&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106797&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	-21.1529693261765
beta	3.12009326932861
S.D.	1.12174284461346
T-STAT	2.7814692862193
p-value	0.0133414245607614
Lambda	-2.12009326932861

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