FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_boxcoxnorm.wasp
Title produced by softwareBox-Cox Normality Plot
Date of computationThu, 13 Nov 2008 03:25:01 -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/2008/Nov/13/t1226572086diyvo228g949arq.htm/, Retrieved Mon, 20 May 2024 09:26:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24554, Retrieved Mon, 20 May 2024 09:26:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Box-Cox Normality Plot] [boxcoxnormality] [2008-11-13 10:25:01] [80e37024345c6a903bf645806b7fbe14] [Current]
Feedback Forum
2008-11-15 12:42:43 [Ken Wright] [reply] 
Bij de box cox normality plot gaat men proberen door een berekening met lambda de verdeling meer normaal maken. De optimale lambda is hier 0.97. Uit de 2 histogrammen blijkt dat de data meer normaal zijn geworden. Maar uit de q-q plots blijft de puntenwolk nagenoeg onveranderd na de transformatie.
2008-11-19 15:35:30 [Glenn Maras] [reply] 
Gegevens zijn correct berekent maar er is geen conclusie.
Hij/zij had kunnen zeggen dat de box cox normality plot de lambda normaal probeert te verdelen. De optimale lambda bedraagt hier 0.97, wat dus nog geen normaalverdeling is.
De getransformeerde QQplot toont weinig verschil met de originele.
De getransformeerde histogram toont wel verschil met de originele. De getransformeerde is namelijk beter normaal verdeeld als de originele histogram.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1530,9
2220,6
2161,5
1863,6
1955,1
1907,4
1889,4
2246,3
2213
1965
2285,6
1983,8
1872,4
2371,4
2287
2198,2
2330,4
2014,4
2066,1
2355,8
2232,5
2091,7
2376,5
1931,9
2025,7
2404,9
2316,1
2368,1
2282,5
2158,6
2174,8
2594,1
2281,4
2547,9
2606,3
2190,8
2262,3
2423,8
2520,4
2482,9
2215,9
2441,9
2333,8
2670,2
2431
2559,3
2661,4
2404,6
2378,3
2489,2
2959
2713,5
2341,3
2833,2
2849,7
2871,7
3058,3
2855,1
3083,6
2828,3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24554&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24554&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24554&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 time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Box-Cox Normality Plot
# observations x60
maximum correlation0.835591257158015
optimal lambda0.97

\begin{tabular}{lllllllll}
\hline
Box-Cox Normality Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.835591257158015 \tabularnewline
optimal lambda & 0.97 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24554&T=1

[TABLE]
[ROW][C]Box-Cox Normality Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]60[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.835591257158015[/C][/ROW]
[ROW][C]optimal lambda[/C][C]0.97[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24554&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24554&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:

Box-Cox Normality Plot
# observations x60
maximum correlation0.835591257158015
optimal lambda0.97


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
n <- length(x)
c <- array(NA,dim=c(401))
l <- array(NA,dim=c(401))
mx <- 0
mxli <- -999
for (i in 1:401)
{
l[i] <- (i-201)/100
if (l[i] != 0)
{
x1 <- (x^l[i] - 1) / l[i]
} else {
x1 <- log(x)
}
c[i] <- cor(qnorm(ppoints(x), mean=0, sd=1),x1)
if (mx < c[i])
{
mx <- c[i]
mxli <- l[i]
}
}
c
mx
mxli
if (mxli != 0)
{
x1 <- (x^mxli - 1) / mxli
} else {
x1 <- log(x)
}
bitmap(file='test1.png')
plot(l,c,main='Box-Cox Normality Plot',xlab='Lambda',ylab='correlation')
mtext(paste('Optimal Lambda =',mxli))
grid()
dev.off()
bitmap(file='test2.png')
hist(x,main='Histogram of Original Data',xlab='X',ylab='frequency')
grid()
dev.off()
bitmap(file='test3.png')
hist(x1,main='Histogram of Transformed Data',xlab='X',ylab='frequency')
grid()
dev.off()
bitmap(file='test4.png')
qqnorm(x)
qqline(x)
grid()
mtext('Original Data')
dev.off()
bitmap(file='test5.png')
qqnorm(x1)
qqline(x1)
grid()
mtext('Transformed Data')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Box-Cox Normality Plot',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations x',header=TRUE)
a<-table.element(a,n)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum correlation',header=TRUE)
a<-table.element(a,mx)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'optimal lambda',header=TRUE)
a<-table.element(a,mxli)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')