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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Thu, 21 Jan 2016 14:29:07 +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/2016/Jan/21/t1453386659jkvga7xtsfslg3y.htm/, Retrieved Mon, 29 Apr 2024 02:20:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=289894, Retrieved Mon, 29 Apr 2024 02:20:44 +0000

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Original text written by user:

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No (this computation is public)

User-defined keywords

Estimated Impact

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
- RMP     [ARIMA Backward Selection] [Unemployment] [2010-11-29 17:10:28] [b98453cac15ba1066b407e146608df68]
- RMPD        [Standard Deviation-Mean Plot] [Vraag 8] [2016-01-21 14:29:07] [6fcd835d84c21d5fa75424c2b64e5f0f] [Current]
- RM D          [Central Tendency] [Vraag 6] [2016-01-21 16:54:45] [75ecf23b983ac48a160341e9388f481a] 
- RM D          [Skewness and Kurtosis Test] [Vraag 6] [2016-01-21 16:56:41] [75ecf23b983ac48a160341e9388f481a] 
- RM D          [Testing Mean with unknown Variance - Critical Value] [Vraag 6 b] [2016-01-21 16:59:04] [75ecf23b983ac48a160341e9388f481a] 

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Dataseries X:

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Histogram

Boxplots

1.4
1.5
1.8
1.8
1.8
1.7
1.5
1.1
1.3
1.6
1.9
1.9
2
2.2
2.2
2
2.3
2.6
3.2
3.2
3.1
2.8
2.3
1.9
1.9
2
2
1.8
1.6
1.4
0.2
0.3
0.4
0.7
1
1.1
0.8
0.8
1
1.1
1
0.8
1.6
1.5
1.6
1.6
1.6
1.9
2
1.9
2
2.1
2.3
2.3
2.6
2.6
2.7
2.6
2.6
2.4
2.5
2.5
2.5
2.4
2.1
2.1
2.3
2.3
2.3
2.9
2.8
2.9
3
3
2.9
2.6
2.8
2.9
3.1
2.8
2.4
1.6
1.5
1.7

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	'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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289894&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289894&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289894&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	'George Udny Yule' @ yule.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1.60833333333333	0.253908835942542	0.8
2	2.48333333333333	0.482103974702805	1.3
3	1.2	0.679572057855664	1.8
4	1.275	0.395715692247489	1.1
5	2.34166666666667	0.284312035153866	0.8
6	2.46666666666667	0.277434130866584	0.8
7	2.525	0.58949130612758	1.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.60833333333333 & 0.253908835942542 & 0.8 \tabularnewline
2 & 2.48333333333333 & 0.482103974702805 & 1.3 \tabularnewline
3 & 1.2 & 0.679572057855664 & 1.8 \tabularnewline
4 & 1.275 & 0.395715692247489 & 1.1 \tabularnewline
5 & 2.34166666666667 & 0.284312035153866 & 0.8 \tabularnewline
6 & 2.46666666666667 & 0.277434130866584 & 0.8 \tabularnewline
7 & 2.525 & 0.58949130612758 & 1.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289894&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]1.60833333333333[/C][C]0.253908835942542[/C][C]0.8[/C][/ROW]
[ROW][C]2[/C][C]2.48333333333333[/C][C]0.482103974702805[/C][C]1.3[/C][/ROW]
[ROW][C]3[/C][C]1.2[/C][C]0.679572057855664[/C][C]1.8[/C][/ROW]
[ROW][C]4[/C][C]1.275[/C][C]0.395715692247489[/C][C]1.1[/C][/ROW]
[ROW][C]5[/C][C]2.34166666666667[/C][C]0.284312035153866[/C][C]0.8[/C][/ROW]
[ROW][C]6[/C][C]2.46666666666667[/C][C]0.277434130866584[/C][C]0.8[/C][/ROW]
[ROW][C]7[/C][C]2.525[/C][C]0.58949130612758[/C][C]1.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289894&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289894&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	1.60833333333333	0.253908835942542	0.8
2	2.48333333333333	0.482103974702805	1.3
3	1.2	0.679572057855664	1.8
4	1.275	0.395715692247489	1.1
5	2.34166666666667	0.284312035153866	0.8
6	2.46666666666667	0.277434130866584	0.8
7	2.525	0.58949130612758	1.6

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.532152787257142
beta	-0.0548583797052854
S.D.	0.121791042919253
T-STAT	-0.450430330427964
p-value	0.671259143994618

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.532152787257142 \tabularnewline
beta & -0.0548583797052854 \tabularnewline
S.D. & 0.121791042919253 \tabularnewline
T-STAT & -0.450430330427964 \tabularnewline
p-value & 0.671259143994618 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289894&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.532152787257142[/C][/ROW]
[ROW][C]beta[/C][C]-0.0548583797052854[/C][/ROW]
[ROW][C]S.D.[/C][C]0.121791042919253[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.450430330427964[/C][/ROW]
[ROW][C]p-value[/C][C]0.671259143994618[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289894&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289894&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	0.532152787257142
beta	-0.0548583797052854
S.D.	0.121791042919253
T-STAT	-0.450430330427964
p-value	0.671259143994618

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-0.761283460150621
beta	-0.256811207452989
S.D.	0.515115155653749
T-STAT	-0.498551061125472
p-value	0.639249532615128
Lambda	1.25681120745299

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.761283460150621 \tabularnewline
beta & -0.256811207452989 \tabularnewline
S.D. & 0.515115155653749 \tabularnewline
T-STAT & -0.498551061125472 \tabularnewline
p-value & 0.639249532615128 \tabularnewline
Lambda & 1.25681120745299 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=289894&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.761283460150621[/C][/ROW]
[ROW][C]beta[/C][C]-0.256811207452989[/C][/ROW]
[ROW][C]S.D.[/C][C]0.515115155653749[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.498551061125472[/C][/ROW]
[ROW][C]p-value[/C][C]0.639249532615128[/C][/ROW]
[ROW][C]Lambda[/C][C]1.25681120745299[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=289894&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=289894&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	-0.761283460150621
beta	-0.256811207452989
S.D.	0.515115155653749
T-STAT	-0.498551061125472
p-value	0.639249532615128
Lambda	1.25681120745299

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