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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 computationWed, 22 Oct 2008 06:37:18 -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/22/t1224680049vxcec6uhya97nqd.htm/, Retrieved Sun, 19 May 2024 16:35:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18405, Retrieved Sun, 19 May 2024 16:35:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact198

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Percentiles] [Percentiles Q6] [2008-10-20 14:43:47] [3d2d096cc21c6f80db3dd7b8e12effce]
F    D  [Percentiles] [IA2, Q1 QQplot] [2008-10-22 12:28:45] [3d2d096cc21c6f80db3dd7b8e12effce]
F RM        [Tukey lambda PPCC Plot] [PPCC plot Q1 IA2] [2008-10-22 12:37:18] [b05bea52879de0a398b42c6968cc24b2] [Current]
Feedback Forum
2008-10-31 19:23:01 [Stéphanie Claes] [reply] 
De student maakt correct de conclusie dat de correlatie het grootst is bij de normaalverdeling en staaft dit nogmaals door het trekken van een Q-Q plot die aantoont dat er weldegelijk normaalverdeling is omwille van het feit dat de punten zeer dicht bij de rechte liggen.
We spreken van normaalverdeling als de punten onafhankelijk zijn van elkaar, dit betekent dat er geen sprake kan zijn van autocorrelatie.
2008-11-02 19:44:13 [Bernard Femont] [reply] 
Juiste gegevens worden ingevoerd, de correlatie is zoals gezegd het grootst bij de normaalverdeling. Ook wordt de normaalverdeling bij een extra plot getoond.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110.40
96.40
101.90
106.20
81.00
94.70
101.00
109.40
102.30
90.70
96.20
96.10
106.00
103.10
102.00
104.70
86.00
92.10
106.90
112.60
101.70
92.00
97.40
97.00
105.40
102.70
98.10
104.50
87.40
89.90
109.80
111.70
98.60
96.90
95.10
97.00
112.70
102.90
97.40
111.40
87.40
96.80
114.10
110.30
103.90
101.60
94.60
95.90
104.70
102.80
98.10
113.90
80.90
95.70
113.20
105.90
108.80
102.30
99.00
100.70
115.50

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18405&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]3 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=18405&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18405&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.681034394717584
Exact Logistic (lambda=0)0.984820721672163
Approx. Normal (lambda=0.14)0.989505916159088
U-shaped (lambda=0.5)0.985385537255734
Exactly Uniform (lambda=1)0.97511352322751

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.681034394717584 \tabularnewline
Exact Logistic (lambda=0) & 0.984820721672163 \tabularnewline
Approx. Normal (lambda=0.14) & 0.989505916159088 \tabularnewline
U-shaped (lambda=0.5) & 0.985385537255734 \tabularnewline
Exactly Uniform (lambda=1) & 0.97511352322751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18405&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]0.681034394717584[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.984820721672163[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.989505916159088[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.985385537255734[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.97511352322751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18405&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18405&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)0.681034394717584
Exact Logistic (lambda=0)0.984820721672163
Approx. Normal (lambda=0.14)0.989505916159088
U-shaped (lambda=0.5)0.985385537255734
Exactly Uniform (lambda=1)0.97511352322751


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')