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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, 03 Aug 2012 12:53:13 -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/2012/Aug/03/t13440129457jovj28iu441pmh.htm/, Retrieved Mon, 29 Apr 2024 19:24:06 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169010, Retrieved Mon, 29 Apr 2024 19:24:06 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

yasmien naciri

Estimated Impact

103

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

-       [Standard Deviation-Mean Plot] [] [2012-08-03 16:53:13] [d06e8713ea83045a022ab0926c74dd0b] [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	'Gertrude Mary Cox' @ cox.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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169010&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169010&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169010&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	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	580.833333333333	72.4202800995479	270
2	565.833333333333	98.761267097926	360
3	541.666666666667	105.987420637231	350
4	546.666666666667	116.098182064957	430
5	542.5	137.187661782882	460
6	558.333333333333	138.09307357611	460
7	569.166666666667	135.20747244905	500
8	575.833333333333	145.255782756634	500
9	571.666666666667	158.448921126212	560

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 580.833333333333 & 72.4202800995479 & 270 \tabularnewline
2 & 565.833333333333 & 98.761267097926 & 360 \tabularnewline
3 & 541.666666666667 & 105.987420637231 & 350 \tabularnewline
4 & 546.666666666667 & 116.098182064957 & 430 \tabularnewline
5 & 542.5 & 137.187661782882 & 460 \tabularnewline
6 & 558.333333333333 & 138.09307357611 & 460 \tabularnewline
7 & 569.166666666667 & 135.20747244905 & 500 \tabularnewline
8 & 575.833333333333 & 145.255782756634 & 500 \tabularnewline
9 & 571.666666666667 & 158.448921126212 & 560 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169010&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]580.833333333333[/C][C]72.4202800995479[/C][C]270[/C][/ROW]
[ROW][C]2[/C][C]565.833333333333[/C][C]98.761267097926[/C][C]360[/C][/ROW]
[ROW][C]3[/C][C]541.666666666667[/C][C]105.987420637231[/C][C]350[/C][/ROW]
[ROW][C]4[/C][C]546.666666666667[/C][C]116.098182064957[/C][C]430[/C][/ROW]
[ROW][C]5[/C][C]542.5[/C][C]137.187661782882[/C][C]460[/C][/ROW]
[ROW][C]6[/C][C]558.333333333333[/C][C]138.09307357611[/C][C]460[/C][/ROW]
[ROW][C]7[/C][C]569.166666666667[/C][C]135.20747244905[/C][C]500[/C][/ROW]
[ROW][C]8[/C][C]575.833333333333[/C][C]145.255782756634[/C][C]500[/C][/ROW]
[ROW][C]9[/C][C]571.666666666667[/C][C]158.448921126212[/C][C]560[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169010&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169010&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	580.833333333333	72.4202800995479	270
2	565.833333333333	98.761267097926	360
3	541.666666666667	105.987420637231	350
4	546.666666666667	116.098182064957	430
5	542.5	137.187661782882	460
6	558.333333333333	138.09307357611	460
7	569.166666666667	135.20747244905	500
8	575.833333333333	145.255782756634	500
9	571.666666666667	158.448921126212	560

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	183.371409281723
beta	-0.107448317059862
S.D.	0.68875700161761
T-STAT	-0.156003230177712
p-value	0.880434120508983

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 183.371409281723 \tabularnewline
beta & -0.107448317059862 \tabularnewline
S.D. & 0.68875700161761 \tabularnewline
T-STAT & -0.156003230177712 \tabularnewline
p-value & 0.880434120508983 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169010&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]183.371409281723[/C][/ROW]
[ROW][C]beta[/C][C]-0.107448317059862[/C][/ROW]
[ROW][C]S.D.[/C][C]0.68875700161761[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.156003230177712[/C][/ROW]
[ROW][C]p-value[/C][C]0.880434120508983[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169010&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169010&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	183.371409281723
beta	-0.107448317059862
S.D.	0.68875700161761
T-STAT	-0.156003230177712
p-value	0.880434120508983

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	12.9940471607831
beta	-1.29633550728107
S.D.	3.45582772786274
T-STAT	-0.375115778147539
p-value	0.718681736243637
Lambda	2.29633550728107

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 12.9940471607831 \tabularnewline
beta & -1.29633550728107 \tabularnewline
S.D. & 3.45582772786274 \tabularnewline
T-STAT & -0.375115778147539 \tabularnewline
p-value & 0.718681736243637 \tabularnewline
Lambda & 2.29633550728107 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169010&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.9940471607831[/C][/ROW]
[ROW][C]beta[/C][C]-1.29633550728107[/C][/ROW]
[ROW][C]S.D.[/C][C]3.45582772786274[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.375115778147539[/C][/ROW]
[ROW][C]p-value[/C][C]0.718681736243637[/C][/ROW]
[ROW][C]Lambda[/C][C]2.29633550728107[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169010&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169010&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	12.9940471607831
beta	-1.29633550728107
S.D.	3.45582772786274
T-STAT	-0.375115778147539
p-value	0.718681736243637
Lambda	2.29633550728107

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