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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_tukeylambda.wasp
Title produced by softwareTukey lambda PPCC Plot
Date of computationSat, 25 Oct 2008 07:50:13 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/25/t12249426576fn2kuro0uv5gvd.htm/, Retrieved Sun, 19 May 2024 01:59:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18734, Retrieved Sun, 19 May 2024 01:59:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Tukey lambda PPCC Plot] [Investigating dis...] [2007-10-22 19:59:15] [b9964c45117f7aac638ab9056d451faa]
F    D    [Tukey lambda PPCC Plot] [Investigating Dis...] [2008-10-25 13:50:13] [6797a1f4a60918966297e9d9220cabc2] [Current]
F           [Tukey lambda PPCC Plot] [investigation dis...] [2008-10-27 21:23:20] [631938996a408f8d8cf3d9850ca0cd03]
Feedback Forum
2008-11-02 13:39:45 [Kevin Engels] [reply] 
Zoals de student aangeeft vinden we inderdaad de grootste correlatie (0,985548358203484) niet terug bij de lambda = 0,14.
2008-11-03 19:09:18 [Nathalie Boden] [reply] 
We zien hier dat de correlatie het grootst is bij lamda=1 (0.985548358203484)
We spreken hier niet van een normale verdeling.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,4
7,2
7,1
6,9
6,8
6,8
6,8
6,9
6,7
6,6
6,5
6,4
6,3
6,3
6,3
6,5
6,6
6,5
6,4
6,5
6,7
7,1
7,1
7,2
7,2
7,3
7,3
7,3
7,3
7,4
7,6
7,6
7,6
7,7
7,8
7,9
8,1
8,1
8,1
8,2
8,2
8,2
8,2
8,2
8,2
8,3
8,3
8,4
8,4
8,4
8,3
8
8
8,2
8,6
8,7
8,7
8,5
8,4
8,4
8,4
8,5
8,5
8,5
8,5
8,5
8,4
8,4
8,4
8,5
8,6
8,6
8,6
8,6
8,5
8,4
8,4
8,3
8,2
8,1
8,2
8,1
8
7,9
7,8
7,7
7,7
7,9
7,8
7,6
7,4
7,3
7,1
7,1
7
7
7
6,9
6,8
6,7
6,6
6,6

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18734&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18734&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18734&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.488880803126401
Exact Logistic (lambda=0)0.939525424594944
Approx. Normal (lambda=0.14)0.95864184918716
U-shaped (lambda=0.5)0.979691422292327
Exactly Uniform (lambda=1)0.985548358203484

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.488880803126401 \tabularnewline
Exact Logistic (lambda=0) & 0.939525424594944 \tabularnewline
Approx. Normal (lambda=0.14) & 0.95864184918716 \tabularnewline
U-shaped (lambda=0.5) & 0.979691422292327 \tabularnewline
Exactly Uniform (lambda=1) & 0.985548358203484 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18734&T=1

[TABLE]
[ROW][C]Tukey Lambda - Key Values[/C][/ROW]
[ROW][C]Distribution (lambda)[/C][C]Correlation[/C][/ROW]
[ROW][C]Approx. Cauchy (lambda=-1)[/C][C]0.488880803126401[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.939525424594944[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.95864184918716[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.979691422292327[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.985548358203484[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18734&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18734&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.488880803126401
Exact Logistic (lambda=0)0.939525424594944
Approx. Normal (lambda=0.14)0.95864184918716
U-shaped (lambda=0.5)0.979691422292327
Exactly Uniform (lambda=1)0.985548358203484


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
gp <- function(lambda, p)
{
(p^lambda-(1-p)^lambda)/lambda
}
sortx <- sort(x)
c <- array(NA,dim=c(201))
for (i in 1:201)
{
if (i != 101) c[i] <- cor(gp(ppoints(x), lambda=(i-101)/100),sortx)
}
bitmap(file='test1.png')
plot((-100:100)/100,c[1:201],xlab='lambda',ylab='correlation',main='PPCC Plot - Tukey lambda')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Lambda - Key Values',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Distribution (lambda)',1,TRUE)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Approx. Cauchy (lambda=-1)',header=TRUE)
a<-table.element(a,c[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Exact Logistic (lambda=0)',header=TRUE)
a<-table.element(a,(c[100]+c[102])/2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Approx. Normal (lambda=0.14)',header=TRUE)
a<-table.element(a,c[115])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'U-shaped (lambda=0.5)',header=TRUE)
a<-table.element(a,c[151])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Exactly Uniform (lambda=1)',header=TRUE)
a<-table.element(a,c[201])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')