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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_tukeylambda.wasp
Title produced by softwareTukey lambda PPCC Plot
Date of computationSun, 21 Oct 2007 09:01:20 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Oct/21/1ukb041mvmotdtx1192982274.htm/, Retrieved Thu, 09 May 2024 05:14:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=1192, Retrieved Thu, 09 May 2024 05:14:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ1 Tukey Lambda PPCC Plot
Estimated Impact538

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] [3cbd35878d9bd3c68c81c01c5c6ec146] [Current]
-    D    [Tukey lambda PPCC Plot] [Tukey Lambda paper] [2007-12-19 15:13:15] [74be16979710d4c4e7c6647856088456]
-    D      [Tukey lambda PPCC Plot] [Tukey Lambda Waarde] [2008-12-18 17:57:41] [1d635fe1113b56bab3f378c464a289bc]
- R  D      [Tukey lambda PPCC Plot] [Tukey Lambda Waarde] [2008-12-18 18:20:14] [1d635fe1113b56bab3f378c464a289bc]
-    D    [Tukey lambda PPCC Plot] [ppcc plot totale ...] [2008-10-22 11:33:24] [e43247bc0ab243a5af99ac7f55ba0b41]
F    D    [Tukey lambda PPCC Plot] [q1 ppcc plot ] [2008-10-22 11:36:35] [7173087adebe3e3a714c80ea2417b3eb]
F   P       [Tukey lambda PPCC Plot] [q1 distributions] [2008-10-27 10:22:51] [e43247bc0ab243a5af99ac7f55ba0b41]
F           [Tukey lambda PPCC Plot] [Q1 Tukey lambda P...] [2008-10-27 19:33:28] [c993f605b206b366f754f7f8c1fcc291]
- RM D    [Percentiles] [qq plot totale in...] [2008-10-22 11:50:43] [e43247bc0ab243a5af99ac7f55ba0b41]
- RM D    [Percentiles] [q1 Q-Q-plot] [2008-10-22 11:50:08] [7173087adebe3e3a714c80ea2417b3eb]
-   P       [Percentiles] [q1 qq plot] [2008-10-27 10:24:50] [e43247bc0ab243a5af99ac7f55ba0b41]
-           [Percentiles] [q1 percentiles] [2008-10-27 19:37:22] [c993f605b206b366f754f7f8c1fcc291]
F    D    [Tukey lambda PPCC Plot] [Tuley Lamba PPCC ...] [2008-10-22 12:31:50] [252acdb58d8522ab27f61fa1e87b5efe]
- R  D    [Tukey lambda PPCC Plot] [Q1 Turkey Lambda ...] [2008-10-22 12:59:07] [f9b9e85820b2a54b20380c3265aca831]
F    D    [Tukey lambda PPCC Plot] [Vraag 1: Q1 Best ...] [2008-10-22 18:03:27] [82d201ca7b4e7cd2c6f885d29b5b6937]
F    D    [Tukey lambda PPCC Plot] [] [2008-10-23 08:27:13] [2a30350413961f11db13c46be07a5f73]
F    D      [Tukey lambda PPCC Plot] [Investigating dis...] [2008-10-27 18:57:35] [090686c1af2bb318059a6f656863a319]
F R  D    [Tukey lambda PPCC Plot] [the "best" (symme...] [2008-10-23 09:03:06] [cb714085b233acee8e8acd879ea442b6]
-    D      [Tukey lambda PPCC Plot] [Q8] [2008-10-23 12:10:05] [cb714085b233acee8e8acd879ea442b6]
F R  D    [Tukey lambda PPCC Plot] [] [2008-10-23 09:32:02] [4ddbf81f78ea7c738951638c7e93f6ee]
-    D    [Tukey lambda PPCC Plot] [Tukey Lambda PPCC...] [2008-10-23 10:19:35] [adb6b6905cde49db36d59ca44433140d]
F    D    [Tukey lambda PPCC Plot] [Q1:Tukey lambda] [2008-10-23 11:12:04] [1ce0d16c8f4225c977b42c8fa93bc163]
-    D    [Tukey lambda PPCC Plot] [Q1] [2008-10-23 12:25:40] [74be16979710d4c4e7c6647856088456]
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] [529a65e524c481ca1098665a9566b89f]
-    D    [Tukey lambda PPCC Plot] [Q2 Investigating ...] [2008-10-23 12:38:00] [74be16979710d4c4e7c6647856088456]
- RMPD    [Univariate Explorative Data Analysis] [Q2 unvariate EDA] [2008-10-23 12:47:25] [529a65e524c481ca1098665a9566b89f]
F RMPD    [Univariate Explorative Data Analysis] [Q2 unvariate EDA] [2008-10-23 12:52:00] [529a65e524c481ca1098665a9566b89f]
-   P       [Univariate Explorative Data Analysis] [Herberekening] [2008-11-02 13:32:47] [79c17183721a40a589db5f9f561947d8]
F    D    [Tukey lambda PPCC Plot] [Q1: determine the...] [2008-10-23 13:22:02] [1e1d8320a8a1170c475bf6e4ce119de6]
-           [Tukey lambda PPCC Plot] [Q1: determine the...] [2008-10-27 18:42:30] [988ab43f527fc78aae41c84649095267]
-           [Tukey lambda PPCC Plot] [dd] [2008-10-27 18:42:30] [74be16979710d4c4e7c6647856088456]
F    D    [Tukey lambda PPCC Plot] [PPCC-plot] [2008-10-23 13:41:30] [bc937651ef42bf891200cf0e0edc7238]
F RMPD    [Univariate Explorative Data Analysis] [Q3 ] [2008-10-23 14:06:35] [529a65e524c481ca1098665a9566b89f]
F RMPD    [Harrell-Davis Quantiles] [Q5] [2008-10-23 14:33:18] [529a65e524c481ca1098665a9566b89f]
F RMPD    [Central Tendency] [Q6] [2008-10-23 14:54:14] [529a65e524c481ca1098665a9566b89f]
F RM D    [Percentiles] [QQ plot - Q1] [2008-10-23 15:01:52] [e5d91604aae608e98a8ea24759233f66]
F    D      [Percentiles] [QQ plot - Q2] [2008-10-23 15:26:39] [e5d91604aae608e98a8ea24759233f66]
F    D    [Tukey lambda PPCC Plot] [q1 totale productie] [2008-10-23 15:24:51] [44a98561a4b3e6ab8cd5a857b48b0914]
F    D    [Tukey lambda PPCC Plot] [Tukey Lambda PPCC...] [2008-10-23 16:11:20] [99d1f77cee9486be2a95cce072dea364]
F    D    [Tukey lambda PPCC Plot] [Vraag 1] [2008-10-24 08:24:04] [87cabf13a90315c7085b765dcebb7412]
F           [Tukey lambda PPCC Plot] [Q1] [2008-10-27 21:40:48] [d2d412c7f4d35ffbf5ee5ee89db327d4]
F    D    [Tukey lambda PPCC Plot] [Tukey lambda PPCC...] [2008-10-24 08:25:20] [58bf45a666dc5198906262e8815a9722]
-    D    [Tukey lambda PPCC Plot] [Tukey Lambda PPCC...] [2008-10-24 12:43:53] [b635de6fc42b001d22cbe6e730fec936]
-           [Tukey lambda PPCC Plot] [weibul task 2] [2008-10-27 16:55:27] [fe7291e888d31b8c4db0b24d6c0f75c6]
F    D    [Tukey lambda PPCC Plot] [Reproduce Q1 ] [2008-10-24 13:02:38] [deb3c14ac9e4607a6d84fc9d0e0e6cc2]
F    D    [Tukey lambda PPCC Plot] [herberekening vra...] [2008-10-24 12:59:52] [c45c87b96bbf32ffc2144fc37d767b2e]
F    D    [Tukey lambda PPCC Plot] [PPCC - tukey lambda] [2008-10-24 13:18:16] [1376d48f59a7212e8dd85a587491a69b]
F    D    [Tukey lambda PPCC Plot] [Q1 PPCC Plot ] [2008-10-24 13:41:50] [7d3039e6253bb5fb3b26df1537d500b4]

[Truncated]
Feedback Forum
2008-10-29 15:56:55 [Julie Leurentop] [reply] 
Je hebt deze berekening juist gereproduceerd. De Tukey lambda PPCC Plot bewijst inderdaad dat de normaalverdeling hier van toepassing is.
2008-10-31 10:06:19 [bdd9f343cef085dc891d2c2f1ef18c37] [reply] 
testezt
2008-10-31 16:21:07 [Bob Leysen] [reply] 
De grafiek is correct.

Approx. Normal (lambda=0.14) 0.989505916159088
2008-11-02 16:45:03 [Kevin Engels] [reply] 
De oplossing van deze vraag is helemaal juist.

De maximum correlatie die de beste distributie aangeeft, vinden we inderdaad bij de approx. Normal (lambda=0.14) nl. 0,989505916159088.
2008-11-02 16:47:57 [Bernard Femont] [reply] 
De gegevens zijn juist ingevoerd, de output is juist en duidelijk geinterpreteerd en weergegeven.
2008-11-02 21:32:03 [Bernard Femont] [reply] 
Wanneer je op de link klikt zie je een kolom. Rechts vind je de grootste correlatie bij Approx. Normal (namelijk 0,9895). Dit wil zeggen dat deze datareeks normaal verdeeld is.
2008-11-03 19:51:00 [Jan Helsen] [reply] 
Je berekening klopt maar ik mis wel uitleg omtrent het belang ervan. Waarom doe je deze berekening? Waarom is het belangrijk dat het om een normaalverdeling gaat? (antwoord= zo weet je dat je steekproeven onafhankelijk van elkaar gebeurden.)
2008-11-03 22:20:13 [Bart Haemels] [reply] 
Ik vind mijn antwoord hier correct, de toevoeging van Jan kon er echter nog wel bij.
2008-11-03 22:25:27 [Toon Nauwelaerts] [reply] 
Een correct antwoord maar een uitleg van wat je juist met deze indicator door kan inderdaad geen kwaad.

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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1192&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=1192&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1192&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






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=1192&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=1192&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1192&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')