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Author's title

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*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Tue, 10 May 2011 21:42:15 +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/2011/May/10/t1305063741t6saudhz0btoqvv.htm/, Retrieved Mon, 13 May 2024 16:00:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121466, Retrieved Mon, 13 May 2024 16:00:10 +0000

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No (this computation is public)

User-defined keywords

KDGP2W83

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

-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2011-05-10 21:42:15] [73460acc53c7293f330720eb944c4fbc] [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' @ www.yougetit.org

\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' @ www.yougetit.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121466&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' @ www.yougetit.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121466&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121466&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' @ www.yougetit.org

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	12.39	0.101324561023804	0.219999999999999
2	12.87	0.104243305140747	0.190000000000001
3	13.2625	0.255	0.61
4	13.9575	0.172119144780585	0.359999999999999
5	14.3675	0.219753649950727	0.49
6	14.98	0.0875595035770911	0.19
7	15.2675	0.0991211380079946	0.219999999999999
8	15.5425	0.0917877987534294	0.210000000000001
9	15.87	0.147196014438797	0.35
10	16.325	0.172916164657905	0.359999999999999
11	16.65	0.0454606056566199	0.100000000000001
12	16.79	0.049665548085838	0.109999999999999
13	16.9825	0.0550000000000003	0.120000000000001
14	17.085	0.0369684550213652	0.0800000000000018
15	17.205	0.055075705472861	0.120000000000001
16	17.3375	0.0801560977094071	0.18
17	17.505	0.0299999999999994	0.0599999999999987
18	17.65	0.0522812904711951	0.110000000000003
19	17.815	0.0556776436283001	0.129999999999999
20	18.01	0.0469041575982343	0.109999999999999
21	18.1375	0.0434932945023337	0.100000000000001
22	18.2775	0.0727438428093177	0.170000000000002

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 12.39 & 0.101324561023804 & 0.219999999999999 \tabularnewline
2 & 12.87 & 0.104243305140747 & 0.190000000000001 \tabularnewline
3 & 13.2625 & 0.255 & 0.61 \tabularnewline
4 & 13.9575 & 0.172119144780585 & 0.359999999999999 \tabularnewline
5 & 14.3675 & 0.219753649950727 & 0.49 \tabularnewline
6 & 14.98 & 0.0875595035770911 & 0.19 \tabularnewline
7 & 15.2675 & 0.0991211380079946 & 0.219999999999999 \tabularnewline
8 & 15.5425 & 0.0917877987534294 & 0.210000000000001 \tabularnewline
9 & 15.87 & 0.147196014438797 & 0.35 \tabularnewline
10 & 16.325 & 0.172916164657905 & 0.359999999999999 \tabularnewline
11 & 16.65 & 0.0454606056566199 & 0.100000000000001 \tabularnewline
12 & 16.79 & 0.049665548085838 & 0.109999999999999 \tabularnewline
13 & 16.9825 & 0.0550000000000003 & 0.120000000000001 \tabularnewline
14 & 17.085 & 0.0369684550213652 & 0.0800000000000018 \tabularnewline
15 & 17.205 & 0.055075705472861 & 0.120000000000001 \tabularnewline
16 & 17.3375 & 0.0801560977094071 & 0.18 \tabularnewline
17 & 17.505 & 0.0299999999999994 & 0.0599999999999987 \tabularnewline
18 & 17.65 & 0.0522812904711951 & 0.110000000000003 \tabularnewline
19 & 17.815 & 0.0556776436283001 & 0.129999999999999 \tabularnewline
20 & 18.01 & 0.0469041575982343 & 0.109999999999999 \tabularnewline
21 & 18.1375 & 0.0434932945023337 & 0.100000000000001 \tabularnewline
22 & 18.2775 & 0.0727438428093177 & 0.170000000000002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121466&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]12.39[/C][C]0.101324561023804[/C][C]0.219999999999999[/C][/ROW]
[ROW][C]2[/C][C]12.87[/C][C]0.104243305140747[/C][C]0.190000000000001[/C][/ROW]
[ROW][C]3[/C][C]13.2625[/C][C]0.255[/C][C]0.61[/C][/ROW]
[ROW][C]4[/C][C]13.9575[/C][C]0.172119144780585[/C][C]0.359999999999999[/C][/ROW]
[ROW][C]5[/C][C]14.3675[/C][C]0.219753649950727[/C][C]0.49[/C][/ROW]
[ROW][C]6[/C][C]14.98[/C][C]0.0875595035770911[/C][C]0.19[/C][/ROW]
[ROW][C]7[/C][C]15.2675[/C][C]0.0991211380079946[/C][C]0.219999999999999[/C][/ROW]
[ROW][C]8[/C][C]15.5425[/C][C]0.0917877987534294[/C][C]0.210000000000001[/C][/ROW]
[ROW][C]9[/C][C]15.87[/C][C]0.147196014438797[/C][C]0.35[/C][/ROW]
[ROW][C]10[/C][C]16.325[/C][C]0.172916164657905[/C][C]0.359999999999999[/C][/ROW]
[ROW][C]11[/C][C]16.65[/C][C]0.0454606056566199[/C][C]0.100000000000001[/C][/ROW]
[ROW][C]12[/C][C]16.79[/C][C]0.049665548085838[/C][C]0.109999999999999[/C][/ROW]
[ROW][C]13[/C][C]16.9825[/C][C]0.0550000000000003[/C][C]0.120000000000001[/C][/ROW]
[ROW][C]14[/C][C]17.085[/C][C]0.0369684550213652[/C][C]0.0800000000000018[/C][/ROW]
[ROW][C]15[/C][C]17.205[/C][C]0.055075705472861[/C][C]0.120000000000001[/C][/ROW]
[ROW][C]16[/C][C]17.3375[/C][C]0.0801560977094071[/C][C]0.18[/C][/ROW]
[ROW][C]17[/C][C]17.505[/C][C]0.0299999999999994[/C][C]0.0599999999999987[/C][/ROW]
[ROW][C]18[/C][C]17.65[/C][C]0.0522812904711951[/C][C]0.110000000000003[/C][/ROW]
[ROW][C]19[/C][C]17.815[/C][C]0.0556776436283001[/C][C]0.129999999999999[/C][/ROW]
[ROW][C]20[/C][C]18.01[/C][C]0.0469041575982343[/C][C]0.109999999999999[/C][/ROW]
[ROW][C]21[/C][C]18.1375[/C][C]0.0434932945023337[/C][C]0.100000000000001[/C][/ROW]
[ROW][C]22[/C][C]18.2775[/C][C]0.0727438428093177[/C][C]0.170000000000002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121466&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121466&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	12.39	0.101324561023804	0.219999999999999
2	12.87	0.104243305140747	0.190000000000001
3	13.2625	0.255	0.61
4	13.9575	0.172119144780585	0.359999999999999
5	14.3675	0.219753649950727	0.49
6	14.98	0.0875595035770911	0.19
7	15.2675	0.0991211380079946	0.219999999999999
8	15.5425	0.0917877987534294	0.210000000000001
9	15.87	0.147196014438797	0.35
10	16.325	0.172916164657905	0.359999999999999
11	16.65	0.0454606056566199	0.100000000000001
12	16.79	0.049665548085838	0.109999999999999
13	16.9825	0.0550000000000003	0.120000000000001
14	17.085	0.0369684550213652	0.0800000000000018
15	17.205	0.055075705472861	0.120000000000001
16	17.3375	0.0801560977094071	0.18
17	17.505	0.0299999999999994	0.0599999999999987
18	17.65	0.0522812904711951	0.110000000000003
19	17.815	0.0556776436283001	0.129999999999999
20	18.01	0.0469041575982343	0.109999999999999
21	18.1375	0.0434932945023337	0.100000000000001
22	18.2775	0.0727438428093177	0.170000000000002

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.467375647259431
beta	-0.0231677606351544
S.D.	0.00573568195868822
T-STAT	-4.03923383514329
p-value	0.000641852580129238

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.467375647259431 \tabularnewline
beta & -0.0231677606351544 \tabularnewline
S.D. & 0.00573568195868822 \tabularnewline
T-STAT & -4.03923383514329 \tabularnewline
p-value & 0.000641852580129238 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121466&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.467375647259431[/C][/ROW]
[ROW][C]beta[/C][C]-0.0231677606351544[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00573568195868822[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.03923383514329[/C][/ROW]
[ROW][C]p-value[/C][C]0.000641852580129238[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121466&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121466&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	0.467375647259431
beta	-0.0231677606351544
S.D.	0.00573568195868822
T-STAT	-4.03923383514329
p-value	0.000641852580129238

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	7.38809028374048
beta	-3.58049651865793
S.D.	0.815248981505982
T-STAT	-4.39190554037099
p-value	0.000281485181460203
Lambda	4.58049651865793

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.38809028374048 \tabularnewline
beta & -3.58049651865793 \tabularnewline
S.D. & 0.815248981505982 \tabularnewline
T-STAT & -4.39190554037099 \tabularnewline
p-value & 0.000281485181460203 \tabularnewline
Lambda & 4.58049651865793 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121466&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.38809028374048[/C][/ROW]
[ROW][C]beta[/C][C]-3.58049651865793[/C][/ROW]
[ROW][C]S.D.[/C][C]0.815248981505982[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.39190554037099[/C][/ROW]
[ROW][C]p-value[/C][C]0.000281485181460203[/C][/ROW]
[ROW][C]Lambda[/C][C]4.58049651865793[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121466&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121466&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	7.38809028374048
beta	-3.58049651865793
S.D.	0.815248981505982
T-STAT	-4.39190554037099
p-value	0.000281485181460203
Lambda	4.58049651865793

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