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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

Sat, 28 Nov 2009 07:57:59 -0700

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/2009/Nov/28/t1259420408h66f6bmh5x9zged.htm/, Retrieved Fri, 03 May 2024 03:51:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61485, Retrieved Fri, 03 May 2024 03:51:37 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

132

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

-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
F    D          [Standard Deviation-Mean Plot] [WS8 SMP heteroske...] [2009-11-28 14:57:59] [85defb7a20869746625978e6577e6e44] [Current]

Feedback Forum

2009-12-05 15:30:43 [f1e24346ff4ab8a20729561498ad5c34] [reply] 
Bij deze calculator worden de gegevens opgedeeld in ‘stukken’ van 12 gegevens/maanden. Je hebt dus 7 punten omdat je 7 keer 12 gegevens hebt.  
De Standard Deviation is een maatstaf voor de spreading. Mean is een maatstaf voor niveau.  
 
Bij het regressiemodel is de p-waarde 0,001. Dit is een zeer kleine p-waarde waardoor je de nulhypothese gaat verwerpen. Uit de grafiek en de cijfers leid je af dat er een zeer groot verband is tussen gemiddelde en standard deviation. Het is dus nodig om een λ-waarde te berekenen en te transformeren.  

Post a new message

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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	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61485&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61485&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61485&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	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2005.75	1335.62951620030	3745
2	1863.41666666667	1179.05011523787	3512
3	1862.83333333333	1116.1978346425	2951
4	1866	1060.59374451724	2939
5	1810.08333333333	1063.80333609121	2888
6	1955.91666666667	1233.96990226544	3165
7	2093.75	1379.93314231985	4690

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2005.75 & 1335.62951620030 & 3745 \tabularnewline
2 & 1863.41666666667 & 1179.05011523787 & 3512 \tabularnewline
3 & 1862.83333333333 & 1116.1978346425 & 2951 \tabularnewline
4 & 1866 & 1060.59374451724 & 2939 \tabularnewline
5 & 1810.08333333333 & 1063.80333609121 & 2888 \tabularnewline
6 & 1955.91666666667 & 1233.96990226544 & 3165 \tabularnewline
7 & 2093.75 & 1379.93314231985 & 4690 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61485&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]2005.75[/C][C]1335.62951620030[/C][C]3745[/C][/ROW]
[ROW][C]2[/C][C]1863.41666666667[/C][C]1179.05011523787[/C][C]3512[/C][/ROW]
[ROW][C]3[/C][C]1862.83333333333[/C][C]1116.1978346425[/C][C]2951[/C][/ROW]
[ROW][C]4[/C][C]1866[/C][C]1060.59374451724[/C][C]2939[/C][/ROW]
[ROW][C]5[/C][C]1810.08333333333[/C][C]1063.80333609121[/C][C]2888[/C][/ROW]
[ROW][C]6[/C][C]1955.91666666667[/C][C]1233.96990226544[/C][C]3165[/C][/ROW]
[ROW][C]7[/C][C]2093.75[/C][C]1379.93314231985[/C][C]4690[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61485&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61485&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	2005.75	1335.62951620030	3745
2	1863.41666666667	1179.05011523787	3512
3	1862.83333333333	1116.1978346425	2951
4	1866	1060.59374451724	2939
5	1810.08333333333	1063.80333609121	2888
6	1955.91666666667	1233.96990226544	3165
7	2093.75	1379.93314231985	4690

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-1122.95760518331
beta	1.20598768943973
S.D.	0.178510533326095
T-STAT	6.75583489091195
p-value	0.00107895869811286

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1122.95760518331 \tabularnewline
beta & 1.20598768943973 \tabularnewline
S.D. & 0.178510533326095 \tabularnewline
T-STAT & 6.75583489091195 \tabularnewline
p-value & 0.00107895869811286 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61485&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1122.95760518331[/C][/ROW]
[ROW][C]beta[/C][C]1.20598768943973[/C][/ROW]
[ROW][C]S.D.[/C][C]0.178510533326095[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.75583489091195[/C][/ROW]
[ROW][C]p-value[/C][C]0.00107895869811286[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61485&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61485&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	-1122.95760518331
beta	1.20598768943973
S.D.	0.178510533326095
T-STAT	6.75583489091195
p-value	0.00107895869811286

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-7.53351421022425
beta	1.93315184724258
S.D.	0.304013726760719
T-STAT	6.35876500656864
p-value	0.00142146257220765
Lambda	-0.933151847242577

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.53351421022425 \tabularnewline
beta & 1.93315184724258 \tabularnewline
S.D. & 0.304013726760719 \tabularnewline
T-STAT & 6.35876500656864 \tabularnewline
p-value & 0.00142146257220765 \tabularnewline
Lambda & -0.933151847242577 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61485&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.53351421022425[/C][/ROW]
[ROW][C]beta[/C][C]1.93315184724258[/C][/ROW]
[ROW][C]S.D.[/C][C]0.304013726760719[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.35876500656864[/C][/ROW]
[ROW][C]p-value[/C][C]0.00142146257220765[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.933151847242577[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61485&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61485&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	-7.53351421022425
beta	1.93315184724258
S.D.	0.304013726760719
T-STAT	6.35876500656864
p-value	0.00142146257220765
Lambda	-0.933151847242577

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