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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

Fri, 19 Aug 2011 03:44:11 -0400

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/Aug/19/t1313739894gvhelfchvf1445k.htm/, Retrieved Tue, 14 May 2024 01:26:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=124196, Retrieved Tue, 14 May 2024 01:26:20 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

186

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

-       [Standard Deviation-Mean Plot] [Spreidings-en gem...] [2011-08-19 07:44:11] [be417f314f65e9d8a38b0902dfa3287c] [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	'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124196&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124196&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124196&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	'George Udny Yule' @ yule.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	766.666666666667	51.5810630038395	160
2	789.166666666667	47.185963500973	170
3	810	75.4381143117263	270
4	815	71.4142842854285	280
5	828.333333333333	87.7841705893529	350
6	845	84.6919551830472	350
7	875.833333333333	102.554494013789	350
8	890.833333333333	106.979890492078	370
9	901.666666666667	113.604844113535	370

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 766.666666666667 & 51.5810630038395 & 160 \tabularnewline
2 & 789.166666666667 & 47.185963500973 & 170 \tabularnewline
3 & 810 & 75.4381143117263 & 270 \tabularnewline
4 & 815 & 71.4142842854285 & 280 \tabularnewline
5 & 828.333333333333 & 87.7841705893529 & 350 \tabularnewline
6 & 845 & 84.6919551830472 & 350 \tabularnewline
7 & 875.833333333333 & 102.554494013789 & 350 \tabularnewline
8 & 890.833333333333 & 106.979890492078 & 370 \tabularnewline
9 & 901.666666666667 & 113.604844113535 & 370 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124196&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]766.666666666667[/C][C]51.5810630038395[/C][C]160[/C][/ROW]
[ROW][C]2[/C][C]789.166666666667[/C][C]47.185963500973[/C][C]170[/C][/ROW]
[ROW][C]3[/C][C]810[/C][C]75.4381143117263[/C][C]270[/C][/ROW]
[ROW][C]4[/C][C]815[/C][C]71.4142842854285[/C][C]280[/C][/ROW]
[ROW][C]5[/C][C]828.333333333333[/C][C]87.7841705893529[/C][C]350[/C][/ROW]
[ROW][C]6[/C][C]845[/C][C]84.6919551830472[/C][C]350[/C][/ROW]
[ROW][C]7[/C][C]875.833333333333[/C][C]102.554494013789[/C][C]350[/C][/ROW]
[ROW][C]8[/C][C]890.833333333333[/C][C]106.979890492078[/C][C]370[/C][/ROW]
[ROW][C]9[/C][C]901.666666666667[/C][C]113.604844113535[/C][C]370[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124196&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124196&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	766.666666666667	51.5810630038395	160
2	789.166666666667	47.185963500973	170
3	810	75.4381143117263	270
4	815	71.4142842854285	280
5	828.333333333333	87.7841705893529	350
6	845	84.6919551830472	350
7	875.833333333333	102.554494013789	350
8	890.833333333333	106.979890492078	370
9	901.666666666667	113.604844113535	370

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-325.595603061919
beta	0.488081782260025
S.D.	0.0490311588470218
T-STAT	9.954522669612
p-value	2.20466528782734e-05

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -325.595603061919 \tabularnewline
beta & 0.488081782260025 \tabularnewline
S.D. & 0.0490311588470218 \tabularnewline
T-STAT & 9.954522669612 \tabularnewline
p-value & 2.20466528782734e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124196&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-325.595603061919[/C][/ROW]
[ROW][C]beta[/C][C]0.488081782260025[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0490311588470218[/C][/ROW]
[ROW][C]T-STAT[/C][C]9.954522669612[/C][/ROW]
[ROW][C]p-value[/C][C]2.20466528782734e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124196&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124196&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	-325.595603061919
beta	0.488081782260025
S.D.	0.0490311588470218
T-STAT	9.954522669612
p-value	2.20466528782734e-05

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-31.0455616299714
beta	5.26478227782566
S.D.	0.710263153886251
T-STAT	7.412438965782
p-value	0.000147851572755447
Lambda	-4.26478227782566

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -31.0455616299714 \tabularnewline
beta & 5.26478227782566 \tabularnewline
S.D. & 0.710263153886251 \tabularnewline
T-STAT & 7.412438965782 \tabularnewline
p-value & 0.000147851572755447 \tabularnewline
Lambda & -4.26478227782566 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124196&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-31.0455616299714[/C][/ROW]
[ROW][C]beta[/C][C]5.26478227782566[/C][/ROW]
[ROW][C]S.D.[/C][C]0.710263153886251[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.412438965782[/C][/ROW]
[ROW][C]p-value[/C][C]0.000147851572755447[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.26478227782566[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124196&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124196&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	-31.0455616299714
beta	5.26478227782566
S.D.	0.710263153886251
T-STAT	7.412438965782
p-value	0.000147851572755447
Lambda	-4.26478227782566

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

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