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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

Wed, 10 Aug 2016 23:28:16 +0100

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/2016/Aug/10/t1470868121qi1gudu85h3l3wx.htm/, Retrieved Tue, 30 Apr 2024 01:45:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296272, Retrieved Tue, 30 Apr 2024 01:45:23 +0000

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Estimated Impact

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

-       [Standard Deviation-Mean Plot] [] [2016-08-10 22:28:16] [3e69b53d94b342798d3f1a806941de01] [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' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296272&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' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296272&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296272&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' @ wold.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	674.166666666667	38.5435605595288	135
2	681.25	39.1457068353142	125
3	686.666666666667	52.2812904711937	180
4	683.333333333333	55.1169555389155	165
5	675	67.8232998312527	210
6	663.75	74.7153689921716	225
7	668.75	84.9364735873497	320
8	663.333333333333	87.9393730551528	320
9	659.166666666667	85.3557617305713	315

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 674.166666666667 & 38.5435605595288 & 135 \tabularnewline
2 & 681.25 & 39.1457068353142 & 125 \tabularnewline
3 & 686.666666666667 & 52.2812904711937 & 180 \tabularnewline
4 & 683.333333333333 & 55.1169555389155 & 165 \tabularnewline
5 & 675 & 67.8232998312527 & 210 \tabularnewline
6 & 663.75 & 74.7153689921716 & 225 \tabularnewline
7 & 668.75 & 84.9364735873497 & 320 \tabularnewline
8 & 663.333333333333 & 87.9393730551528 & 320 \tabularnewline
9 & 659.166666666667 & 85.3557617305713 & 315 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296272&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]674.166666666667[/C][C]38.5435605595288[/C][C]135[/C][/ROW]
[ROW][C]2[/C][C]681.25[/C][C]39.1457068353142[/C][C]125[/C][/ROW]
[ROW][C]3[/C][C]686.666666666667[/C][C]52.2812904711937[/C][C]180[/C][/ROW]
[ROW][C]4[/C][C]683.333333333333[/C][C]55.1169555389155[/C][C]165[/C][/ROW]
[ROW][C]5[/C][C]675[/C][C]67.8232998312527[/C][C]210[/C][/ROW]
[ROW][C]6[/C][C]663.75[/C][C]74.7153689921716[/C][C]225[/C][/ROW]
[ROW][C]7[/C][C]668.75[/C][C]84.9364735873497[/C][C]320[/C][/ROW]
[ROW][C]8[/C][C]663.333333333333[/C][C]87.9393730551528[/C][C]320[/C][/ROW]
[ROW][C]9[/C][C]659.166666666667[/C][C]85.3557617305713[/C][C]315[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296272&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296272&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	674.166666666667	38.5435605595288	135
2	681.25	39.1457068353142	125
3	686.666666666667	52.2812904711937	180
4	683.333333333333	55.1169555389155	165
5	675	67.8232998312527	210
6	663.75	74.7153689921716	225
7	668.75	84.9364735873497	320
8	663.333333333333	87.9393730551528	320
9	659.166666666667	85.3557617305713	315

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1127.38987876586
beta	-1.5788593328218
S.D.	0.473627234679565
T-STAT	-3.3335484474198
p-value	0.0125299615141799

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1127.38987876586 \tabularnewline
beta & -1.5788593328218 \tabularnewline
S.D. & 0.473627234679565 \tabularnewline
T-STAT & -3.3335484474198 \tabularnewline
p-value & 0.0125299615141799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296272&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1127.38987876586[/C][/ROW]
[ROW][C]beta[/C][C]-1.5788593328218[/C][/ROW]
[ROW][C]S.D.[/C][C]0.473627234679565[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.3335484474198[/C][/ROW]
[ROW][C]p-value[/C][C]0.0125299615141799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296272&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296272&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	1127.38987876586
beta	-1.5788593328218
S.D.	0.473627234679565
T-STAT	-3.3335484474198
p-value	0.0125299615141799

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	112.041067586074
beta	-16.5724689666314
S.D.	5.76808645798003
T-STAT	-2.87313116531111
p-value	0.0238848635177902
Lambda	17.5724689666314

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 112.041067586074 \tabularnewline
beta & -16.5724689666314 \tabularnewline
S.D. & 5.76808645798003 \tabularnewline
T-STAT & -2.87313116531111 \tabularnewline
p-value & 0.0238848635177902 \tabularnewline
Lambda & 17.5724689666314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296272&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]112.041067586074[/C][/ROW]
[ROW][C]beta[/C][C]-16.5724689666314[/C][/ROW]
[ROW][C]S.D.[/C][C]5.76808645798003[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.87313116531111[/C][/ROW]
[ROW][C]p-value[/C][C]0.0238848635177902[/C][/ROW]
[ROW][C]Lambda[/C][C]17.5724689666314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296272&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296272&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	112.041067586074
beta	-16.5724689666314
S.D.	5.76808645798003
T-STAT	-2.87313116531111
p-value	0.0238848635177902
Lambda	17.5724689666314

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