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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 09:44:17 +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/t1287481379so07ygbpvxfaqkv.htm/, Retrieved Mon, 29 Apr 2024 04:06:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=86108, Retrieved Mon, 29 Apr 2024 04:06:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
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] [Intrinsic motivat...] [2010-10-19 09:43:10] [8d09066a9d3795298da6860e7d4a4400]
F    D      [Tukey lambda PPCC Plot] [Amotivation] [2010-10-19 09:44:17] [a960f182d9e6e851e9aaba5921cd26a4] [Current]
Feedback Forum
2010-10-21 11:44:33 [] [reply
Bij de Turkey-Lambda PPCC Plot zien we dat de lambda convergeert naar 1 voor een waarde 0,14 hieruit kunnen we besluiten dat er een sterke correlatie is tussen de gegevens. We zien dus ook hier dat er een sterke samenhang is en dat de normaalverdeling telkens wordt benaderd.
2010-10-24 16:39:11 [f0479c8ad85b1406c7a3120008048c58] [reply
Hier kun je mooi zien dat het om een normaalverdeling gaat (op enkele uitzonderingen na)
2010-10-25 17:01:18 [4d4f7d38b8a37a3fb90a9939352fc7e6] [reply
Dit is geen normaal verdeling!

Post a new message
Dataseries X:
4
4
6
8
8
4
4
8
5
4
4
4
4
4
4
8
4
4
4
8
4
7
4
4
5
4
4
4
4
4
4
4
15
10
4
8
4
4
4
4
7
4
6
5
4
16
5
12
6
9
9
4
5
4
4
5
4
4
4
5
4
6
4
4
18
4
6
4
4
5
4
4
5
10
5
8
8
5
4
4
4
5
4
4
8
4
5
14
8
8
4
4
6
4
7
7
4
6
4
7
4
4
8
4
4
10
8
6
4
4
4
5
4
6
4
5
7
8
5
8
10
8
5
12
4
5
4
6
4
4
7
7
10
4
5
8
11
7
4
8
6
7
5
4
8
4
8
6
4
9
5
6
4
4
4
5
6
16
6
6
4
4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=86108&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=86108&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=86108&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.544055212766565
Exact Logistic (lambda=0)0.848360036049737
Approx. Normal (lambda=0.14)0.844664020334802
U-shaped (lambda=0.5)0.82744257428688
Exactly Uniform (lambda=1)0.812154568833411

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.544055212766565 \tabularnewline
Exact Logistic (lambda=0) & 0.848360036049737 \tabularnewline
Approx. Normal (lambda=0.14) & 0.844664020334802 \tabularnewline
U-shaped (lambda=0.5) & 0.82744257428688 \tabularnewline
Exactly Uniform (lambda=1) & 0.812154568833411 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=86108&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]0.544055212766565[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.848360036049737[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.844664020334802[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.82744257428688[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.812154568833411[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=86108&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=86108&T=1

As an alternative you can also use a QR Code:  

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

Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.544055212766565
Exact Logistic (lambda=0)0.848360036049737
Approx. Normal (lambda=0.14)0.844664020334802
U-shaped (lambda=0.5)0.82744257428688
Exactly Uniform (lambda=1)0.812154568833411



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')