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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 computationMon, 27 Oct 2008 12:30:03 -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/27/t1225132265fjr5txlkj61gdie.htm/, Retrieved Fri, 17 May 2024 03:45:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19379, Retrieved Fri, 17 May 2024 03:45:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151

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...] [2007-10-21 16:01:20] [b9964c45117f7aac638ab9056d451faa]
F    D  [Tukey lambda PPCC Plot] [ppcc plot total p...] [2008-10-23 12:25:40] [529a65e524c481ca1098665a9566b89f]
F    D      [Tukey lambda PPCC Plot] [Q8] [2008-10-27 18:30:03] [46b5932fe641d17912b9bed340844588] [Current]
Feedback Forum
2008-11-03 10:06:08 [Lindsay Heyndrickx] [reply] 
Er is nog steeds een normaal verdeling want de correlatie bij lambda =0.14 is nog steeds hoog maar niet het hoogste. Dit wijst wil zeggen dat er wel normaalverdeling is maar niet perfect.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,472244033
0,471573636
0,473717889
0,475548837
0,476712299
0,47679046
0,476202127
0,474868726
0,469610593
0,467149091
0,467204136
0,467835322
0,462998345
0,465672109
0,466727908
0,469020842
0,470160966
0,470608869
0,471383703
0,470767778
0,465694131
0,462772359
0,463020207
0,465273975
0,470802151
0,472749595
0,473348841
0,472170918
0,475209805
0,477468916
0,479299205
0,478987386
0,473540079
0,467749251
0,464560273
0,471515496
0,473951925
0,476941786
0,477074114
0,479924221
0,481322902
0,47999052
0,481733879
0,481484743
0,472007091
0,465563002
0,462269147
0,470155467
0,475540251
0,477442208
0,480507838
0,480809484
0,48277744
0,481261495
0,483607109
0,480559574
0,47497592
0,469235151
0,465400401
0,476824759

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'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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19379&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19379&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19379&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'Gwilym Jenkins' @ 72.249.127.135






Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.61866062819422
Exact Logistic (lambda=0)0.973978265117257
Approx. Normal (lambda=0.14)0.986719383489837
U-shaped (lambda=0.5)0.997495634885401
Exactly Uniform (lambda=1)0.99670163626722

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.61866062819422 \tabularnewline
Exact Logistic (lambda=0) & 0.973978265117257 \tabularnewline
Approx. Normal (lambda=0.14) & 0.986719383489837 \tabularnewline
U-shaped (lambda=0.5) & 0.997495634885401 \tabularnewline
Exactly Uniform (lambda=1) & 0.99670163626722 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19379&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]0.61866062819422[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.973978265117257[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.986719383489837[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.997495634885401[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.99670163626722[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19379&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19379&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)0.61866062819422
Exact Logistic (lambda=0)0.973978265117257
Approx. Normal (lambda=0.14)0.986719383489837
U-shaped (lambda=0.5)0.997495634885401
Exactly Uniform (lambda=1)0.99670163626722


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')