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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 computationTue, 19 Oct 2010 15:37:43 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/19/t1287502581r85e84z31qzj2y2.htm/, Retrieved Mon, 29 Apr 2024 05:30:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=86655, Retrieved Mon, 29 Apr 2024 05:30:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Tukey lambda PPCC Plot] [Intrinsic Motivat...] [2010-10-12 12:09:04] [b98453cac15ba1066b407e146608df68]
F    D    [Tukey lambda PPCC Plot] [] [2010-10-19 15:37:43] [6b31f806e9ccc1f74a26091056f791cb] [Current]
Feedback Forum
2010-10-23 07:44:48 [] [reply] 
Interpretatie: je moet kijken naar de maximul correlatie en zo kan je de juiste lambda verdeling aflezen. Het maximum is 0,99, en dit komt overeen met 0,14, dus we kunnen spreken van een normaal verdeling.
2010-10-23 10:54:34 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply] 
De student heeft hier geen eigen interpretatie van de gegevens gegeven. Men kan namelijk de grafiek beschouwen en dan ziet men dat het hoogtepunt bereikt wordt bij Lambda gelijk aan 0,14 (dit ziet men inderdaad ook in de tabel zoals hierboven reeds beschreven). Hieruit kan men besluiten dat de gegevens (bijna) normaal verdeeld zijn.
2010-10-26 09:40:27 [] [reply] 
Als we naar de tabel kijken van de Tukey Lambda dan zien we dat de hoogste waarden bij de normaal verdeling staat. Het streef getal is 1 dus we kunnen spreken van een normaal verdeling.
(Approx. Normal (lambda=0.14) 0.994220675676583)

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21
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12
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28
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12
8
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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=86655&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=86655&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=86655&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)0.56242445502817
Exact Logistic (lambda=0)0.989690695953362
Approx. Normal (lambda=0.14)0.994220675676583
U-shaped (lambda=0.5)0.987562176002712
Exactly Uniform (lambda=1)0.97581565814739

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.56242445502817 \tabularnewline
Exact Logistic (lambda=0) & 0.989690695953362 \tabularnewline
Approx. Normal (lambda=0.14) & 0.994220675676583 \tabularnewline
U-shaped (lambda=0.5) & 0.987562176002712 \tabularnewline
Exactly Uniform (lambda=1) & 0.97581565814739 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=86655&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]0.56242445502817[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.989690695953362[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.994220675676583[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.987562176002712[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.97581565814739[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=86655&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=86655&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)0.56242445502817
Exact Logistic (lambda=0)0.989690695953362
Approx. Normal (lambda=0.14)0.994220675676583
U-shaped (lambda=0.5)0.987562176002712
Exactly Uniform (lambda=1)0.97581565814739


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')