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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

Sat, 04 Dec 2010 19:04:13 +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/04/t1291489424gk7cm71rmx737rw.htm/, Retrieved Sun, 05 May 2024 03:40:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105252, Retrieved Sun, 05 May 2024 03:40:20 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

112

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

-       [Standard Deviation-Mean Plot] [opdracht8 oef3 C] [2010-12-04 19:04:13] [e8fe41381a545d3d3a7b09800c89aa00] [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	6 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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105252&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]6 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=105252&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105252&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	6 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	18.105	0.164215305823382	0.390000000000001
2	18.3425	0.037749172176354	0.0899999999999999
3	18.4175	0.00957427107756333	0.0199999999999996
4	18.5825	0.0873212459828645	0.180000000000000
5	18.715	0.0173205080756881	0.0399999999999991
6	18.8725	0.0434932945023336	0.0800000000000018
7	18.9975	0.0602079728939605	0.139999999999997
8	19.225	0.0310912635102960	0.0700000000000003
9	19.3325	0.0236290781312635	0.0500000000000007
10	19.56	0.208326666559998	0.450000000000003
11	20.0575	0.158403493227476	0.360000000000003
12	20.51	0.0875595035770916	0.170000000000002
13	20.9275	0.175570498660794	0.419999999999998
14	21.235	0.098488578017961	0.180000000000000
15	21.6375	0.130735101126922	0.270000000000000
16	22.07	0.264323034687988	0.560000000000002
17	22.535	0.0597215762238964	0.140000000000001
18	22.835	0.178232058470599	0.400000000000002
19	23.12	0.080415587212098	0.169999999999998
20	23.175	0.0479583152331269	0.0999999999999979
21	23.2	0.0270801280154531	0.0599999999999987

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 18.105 & 0.164215305823382 & 0.390000000000001 \tabularnewline
2 & 18.3425 & 0.037749172176354 & 0.0899999999999999 \tabularnewline
3 & 18.4175 & 0.00957427107756333 & 0.0199999999999996 \tabularnewline
4 & 18.5825 & 0.0873212459828645 & 0.180000000000000 \tabularnewline
5 & 18.715 & 0.0173205080756881 & 0.0399999999999991 \tabularnewline
6 & 18.8725 & 0.0434932945023336 & 0.0800000000000018 \tabularnewline
7 & 18.9975 & 0.0602079728939605 & 0.139999999999997 \tabularnewline
8 & 19.225 & 0.0310912635102960 & 0.0700000000000003 \tabularnewline
9 & 19.3325 & 0.0236290781312635 & 0.0500000000000007 \tabularnewline
10 & 19.56 & 0.208326666559998 & 0.450000000000003 \tabularnewline
11 & 20.0575 & 0.158403493227476 & 0.360000000000003 \tabularnewline
12 & 20.51 & 0.0875595035770916 & 0.170000000000002 \tabularnewline
13 & 20.9275 & 0.175570498660794 & 0.419999999999998 \tabularnewline
14 & 21.235 & 0.098488578017961 & 0.180000000000000 \tabularnewline
15 & 21.6375 & 0.130735101126922 & 0.270000000000000 \tabularnewline
16 & 22.07 & 0.264323034687988 & 0.560000000000002 \tabularnewline
17 & 22.535 & 0.0597215762238964 & 0.140000000000001 \tabularnewline
18 & 22.835 & 0.178232058470599 & 0.400000000000002 \tabularnewline
19 & 23.12 & 0.080415587212098 & 0.169999999999998 \tabularnewline
20 & 23.175 & 0.0479583152331269 & 0.0999999999999979 \tabularnewline
21 & 23.2 & 0.0270801280154531 & 0.0599999999999987 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105252&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]18.105[/C][C]0.164215305823382[/C][C]0.390000000000001[/C][/ROW]
[ROW][C]2[/C][C]18.3425[/C][C]0.037749172176354[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]3[/C][C]18.4175[/C][C]0.00957427107756333[/C][C]0.0199999999999996[/C][/ROW]
[ROW][C]4[/C][C]18.5825[/C][C]0.0873212459828645[/C][C]0.180000000000000[/C][/ROW]
[ROW][C]5[/C][C]18.715[/C][C]0.0173205080756881[/C][C]0.0399999999999991[/C][/ROW]
[ROW][C]6[/C][C]18.8725[/C][C]0.0434932945023336[/C][C]0.0800000000000018[/C][/ROW]
[ROW][C]7[/C][C]18.9975[/C][C]0.0602079728939605[/C][C]0.139999999999997[/C][/ROW]
[ROW][C]8[/C][C]19.225[/C][C]0.0310912635102960[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]9[/C][C]19.3325[/C][C]0.0236290781312635[/C][C]0.0500000000000007[/C][/ROW]
[ROW][C]10[/C][C]19.56[/C][C]0.208326666559998[/C][C]0.450000000000003[/C][/ROW]
[ROW][C]11[/C][C]20.0575[/C][C]0.158403493227476[/C][C]0.360000000000003[/C][/ROW]
[ROW][C]12[/C][C]20.51[/C][C]0.0875595035770916[/C][C]0.170000000000002[/C][/ROW]
[ROW][C]13[/C][C]20.9275[/C][C]0.175570498660794[/C][C]0.419999999999998[/C][/ROW]
[ROW][C]14[/C][C]21.235[/C][C]0.098488578017961[/C][C]0.180000000000000[/C][/ROW]
[ROW][C]15[/C][C]21.6375[/C][C]0.130735101126922[/C][C]0.270000000000000[/C][/ROW]
[ROW][C]16[/C][C]22.07[/C][C]0.264323034687988[/C][C]0.560000000000002[/C][/ROW]
[ROW][C]17[/C][C]22.535[/C][C]0.0597215762238964[/C][C]0.140000000000001[/C][/ROW]
[ROW][C]18[/C][C]22.835[/C][C]0.178232058470599[/C][C]0.400000000000002[/C][/ROW]
[ROW][C]19[/C][C]23.12[/C][C]0.080415587212098[/C][C]0.169999999999998[/C][/ROW]
[ROW][C]20[/C][C]23.175[/C][C]0.0479583152331269[/C][C]0.0999999999999979[/C][/ROW]
[ROW][C]21[/C][C]23.2[/C][C]0.0270801280154531[/C][C]0.0599999999999987[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105252&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105252&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	18.105	0.164215305823382	0.390000000000001
2	18.3425	0.037749172176354	0.0899999999999999
3	18.4175	0.00957427107756333	0.0199999999999996
4	18.5825	0.0873212459828645	0.180000000000000
5	18.715	0.0173205080756881	0.0399999999999991
6	18.8725	0.0434932945023336	0.0800000000000018
7	18.9975	0.0602079728939605	0.139999999999997
8	19.225	0.0310912635102960	0.0700000000000003
9	19.3325	0.0236290781312635	0.0500000000000007
10	19.56	0.208326666559998	0.450000000000003
11	20.0575	0.158403493227476	0.360000000000003
12	20.51	0.0875595035770916	0.170000000000002
13	20.9275	0.175570498660794	0.419999999999998
14	21.235	0.098488578017961	0.180000000000000
15	21.6375	0.130735101126922	0.270000000000000
16	22.07	0.264323034687988	0.560000000000002
17	22.535	0.0597215762238964	0.140000000000001
18	22.835	0.178232058470599	0.400000000000002
19	23.12	0.080415587212098	0.169999999999998
20	23.175	0.0479583152331269	0.0999999999999979
21	23.2	0.0270801280154531	0.0599999999999987

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-0.0832133295094894
beta	0.00870619352055555
S.D.	0.00885092361764159
T-STAT	0.983648023264199
p-value	0.337649515434730

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0832133295094894 \tabularnewline
beta & 0.00870619352055555 \tabularnewline
S.D. & 0.00885092361764159 \tabularnewline
T-STAT & 0.983648023264199 \tabularnewline
p-value & 0.337649515434730 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105252&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0832133295094894[/C][/ROW]
[ROW][C]beta[/C][C]0.00870619352055555[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00885092361764159[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.983648023264199[/C][/ROW]
[ROW][C]p-value[/C][C]0.337649515434730[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105252&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105252&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	-0.0832133295094894
beta	0.00870619352055555
S.D.	0.00885092361764159
T-STAT	0.983648023264199
p-value	0.337649515434730

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-11.9807506572152
beta	3.08419727018867
S.D.	2.23258532083486
T-STAT	1.38144654155271
p-value	0.183172556134011
Lambda	-2.08419727018867

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -11.9807506572152 \tabularnewline
beta & 3.08419727018867 \tabularnewline
S.D. & 2.23258532083486 \tabularnewline
T-STAT & 1.38144654155271 \tabularnewline
p-value & 0.183172556134011 \tabularnewline
Lambda & -2.08419727018867 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105252&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-11.9807506572152[/C][/ROW]
[ROW][C]beta[/C][C]3.08419727018867[/C][/ROW]
[ROW][C]S.D.[/C][C]2.23258532083486[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.38144654155271[/C][/ROW]
[ROW][C]p-value[/C][C]0.183172556134011[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.08419727018867[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105252&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105252&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	-11.9807506572152
beta	3.08419727018867
S.D.	2.23258532083486
T-STAT	1.38144654155271
p-value	0.183172556134011
Lambda	-2.08419727018867

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