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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, 21 Aug 2013 07:48:23 -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/2013/Aug/21/t13770857346snzcv0hei2gajs.htm/, Retrieved Sat, 27 Apr 2024 17:40:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211332, Retrieved Sat, 27 Apr 2024 17:40:51 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Joris Claus

Estimated Impact

105

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

-       [Standard Deviation-Mean Plot] [Tijdreeks B - Sta...] [2013-08-21 11:48:23] [5b48cba8ffed7710e2defc0d8d22bd89] [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=211332&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=211332&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211332&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	577.5	31.442588373675	110
2	580.833333333333	43.1083905212585	150
3	587.083333333333	48.9182218017215	170
4	594.166666666667	43.161079549506	155
5	590.416666666667	56.4663348349879	200
6	587.916666666667	47.6472995196491	160
7	592.916666666667	47.5995766469587	160
8	599.166666666667	48.8891758485609	145
9	602.083333333333	53.9131596911068	195

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 577.5 & 31.442588373675 & 110 \tabularnewline
2 & 580.833333333333 & 43.1083905212585 & 150 \tabularnewline
3 & 587.083333333333 & 48.9182218017215 & 170 \tabularnewline
4 & 594.166666666667 & 43.161079549506 & 155 \tabularnewline
5 & 590.416666666667 & 56.4663348349879 & 200 \tabularnewline
6 & 587.916666666667 & 47.6472995196491 & 160 \tabularnewline
7 & 592.916666666667 & 47.5995766469587 & 160 \tabularnewline
8 & 599.166666666667 & 48.8891758485609 & 145 \tabularnewline
9 & 602.083333333333 & 53.9131596911068 & 195 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211332&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]577.5[/C][C]31.442588373675[/C][C]110[/C][/ROW]
[ROW][C]2[/C][C]580.833333333333[/C][C]43.1083905212585[/C][C]150[/C][/ROW]
[ROW][C]3[/C][C]587.083333333333[/C][C]48.9182218017215[/C][C]170[/C][/ROW]
[ROW][C]4[/C][C]594.166666666667[/C][C]43.161079549506[/C][C]155[/C][/ROW]
[ROW][C]5[/C][C]590.416666666667[/C][C]56.4663348349879[/C][C]200[/C][/ROW]
[ROW][C]6[/C][C]587.916666666667[/C][C]47.6472995196491[/C][C]160[/C][/ROW]
[ROW][C]7[/C][C]592.916666666667[/C][C]47.5995766469587[/C][C]160[/C][/ROW]
[ROW][C]8[/C][C]599.166666666667[/C][C]48.8891758485609[/C][C]145[/C][/ROW]
[ROW][C]9[/C][C]602.083333333333[/C][C]53.9131596911068[/C][C]195[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211332&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211332&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	577.5	31.442588373675	110
2	580.833333333333	43.1083905212585	150
3	587.083333333333	48.9182218017215	170
4	594.166666666667	43.161079549506	155
5	590.416666666667	56.4663348349879	200
6	587.916666666667	47.6472995196491	160
7	592.916666666667	47.5995766469587	160
8	599.166666666667	48.8891758485609	145
9	602.083333333333	53.9131596911068	195

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-317.722162120284
beta	0.617581668059296
S.D.	0.250207491918768
T-STAT	2.46827808121668
p-value	0.0429411900044206

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -317.722162120284 \tabularnewline
beta & 0.617581668059296 \tabularnewline
S.D. & 0.250207491918768 \tabularnewline
T-STAT & 2.46827808121668 \tabularnewline
p-value & 0.0429411900044206 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211332&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-317.722162120284[/C][/ROW]
[ROW][C]beta[/C][C]0.617581668059296[/C][/ROW]
[ROW][C]S.D.[/C][C]0.250207491918768[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.46827808121668[/C][/ROW]
[ROW][C]p-value[/C][C]0.0429411900044206[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211332&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211332&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	-317.722162120284
beta	0.617581668059296
S.D.	0.250207491918768
T-STAT	2.46827808121668
p-value	0.0429411900044206

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-51.7395704127026
beta	8.70996762455394
S.D.	3.40782890293445
T-STAT	2.55586999014354
p-value	0.0377785747196776
Lambda	-7.70996762455394

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -51.7395704127026 \tabularnewline
beta & 8.70996762455394 \tabularnewline
S.D. & 3.40782890293445 \tabularnewline
T-STAT & 2.55586999014354 \tabularnewline
p-value & 0.0377785747196776 \tabularnewline
Lambda & -7.70996762455394 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211332&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-51.7395704127026[/C][/ROW]
[ROW][C]beta[/C][C]8.70996762455394[/C][/ROW]
[ROW][C]S.D.[/C][C]3.40782890293445[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.55586999014354[/C][/ROW]
[ROW][C]p-value[/C][C]0.0377785747196776[/C][/ROW]
[ROW][C]Lambda[/C][C]-7.70996762455394[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211332&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211332&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	-51.7395704127026
beta	8.70996762455394
S.D.	3.40782890293445
T-STAT	2.55586999014354
p-value	0.0377785747196776
Lambda	-7.70996762455394

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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