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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_boxcoxlin.wasp
Title produced by softwareBox-Cox Linearity Plot
Date of computationTue, 11 Nov 2008 09:18:23 -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/11/t1226420360gp81j6pwbie32ts.htm/, Retrieved Sun, 19 May 2024 08:55:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23653, Retrieved Sun, 19 May 2024 08:55:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178

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 Linearity Plot] [Q3] [2008-11-11 16:15:27] [299afd6311e4c20059ea2f05c8dd029d]
F    D    [Box-Cox Linearity Plot] [Q4] [2008-11-11 16:18:23] [5e2b1e7aa808f9f0d23fd35605d4968f] [Current]
F RMPD      [Maximum-likelihood Fitting - Normal Distribution] [Q5] [2008-11-11 16:26:11] [299afd6311e4c20059ea2f05c8dd029d]
-    D        [Maximum-likelihood Fitting - Normal Distribution] [Verbetering Q5] [2008-11-23 15:59:00] [299afd6311e4c20059ea2f05c8dd029d]
- RMPD      [Testing Mean with known Variance - Critical Value] [Q1] [2008-11-11 16:36:56] [299afd6311e4c20059ea2f05c8dd029d]
F RMPD      [Testing Mean with known Variance - Critical Value] [Q1] [2008-11-11 16:36:56] [299afd6311e4c20059ea2f05c8dd029d]
- RMPD      [Testing Variance - p-value (probability)] [Q2] [2008-11-11 16:43:10] [299afd6311e4c20059ea2f05c8dd029d]
- RM          [Testing Mean with known Variance - Critical Value] [Q4] [2008-11-11 17:11:47] [299afd6311e4c20059ea2f05c8dd029d]
F RMPD      [Testing Mean with known Variance - Type II Error] [Q3] [2008-11-11 17:07:30] [299afd6311e4c20059ea2f05c8dd029d]
-             [Testing Mean with known Variance - Type II Error] [Q4] [2008-11-11 17:16:18] [299afd6311e4c20059ea2f05c8dd029d]
- RM          [Testing Mean with known Variance - Critical Value] [Q5] [2008-11-11 17:18:41] [299afd6311e4c20059ea2f05c8dd029d]
F RM          [Testing Sample Mean with known Variance - Confidence Interval] [Q5] [2008-11-11 17:20:57] [299afd6311e4c20059ea2f05c8dd029d]
-   P           [Testing Sample Mean with known Variance - Confidence Interval] [Q5 - Verbetering] [2008-11-23 17:28:35] [299afd6311e4c20059ea2f05c8dd029d]
- RM          [Testing Population Mean with known Variance - Confidence Interval] [Q6] [2008-11-11 17:26:50] [299afd6311e4c20059ea2f05c8dd029d]
F RM          [Testing Sample Mean with known Variance - Confidence Interval] [Q6 - 2 ] [2008-11-11 17:28:02] [299afd6311e4c20059ea2f05c8dd029d]
-   P           [Testing Sample Mean with known Variance - Confidence Interval] [Q6 - Verbetering] [2008-11-23 17:32:27] [299afd6311e4c20059ea2f05c8dd029d]
Feedback Forum
2008-11-19 21:11:29 [Nathalie Koulouris] [reply] 
De student geeft de juiste berekeningsmethode maar licht haar antwoord niet verder toe.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3277.2
3833
2606.3
3643.8
3686.4
3281.6
3669.3
3191.5
3512.7
3970.7
3601.2
3610
4172.1
3956.2
3142.7
3884.3
3892.2
3613
3730.5
3481.3
3649.5
4215.2
4066.6
4196.8
4536.6
4441.6
3548.3
4735.9
4130.6
4356.2
4159.6
3988
4167.8
4902.2
3909.4
4697.6
4308.9
4420.4
3544.2
4433
4479.7
4533.2
4237.5
4207.4
4394
5148.4
4202.2
4682.5
4884.3
5288.9
4505.2
4611.5
5081.1
4523.1
4412.8
4647.4
4778.6
4495.3
4633.5
4360.5
4517.9
Dataseries Y:
Download CSV
Histogram 
12192.5
11268.8
9097.4
12639.8
13040.1
11687.3
11191.7
11391.9
11793.1
13933.2
12778.1
11810.3
13698.4
11956.6
10723.8
13938.9
13979.8
13807.4
12973.9
12509.8
12934.1
14908.3
13772.1
13012.6
14049.9
11816.5
11593.2
14466.2
13615.9
14733.9
13880.7
13527.5
13584
16170.2
13260.6
14741.9
15486.5
13154.5
12621.2
15031.6
15452.4
15428
13105.9
14716.8
14180
16202.2
14392.4
15140.6
15960.1
14351.3
13230.2
15202.1
17157.3
16159.1
13405.7
17224.7
17338.4
17370.6
18817.8
16593.2
17979.5

Tables (Output of Computation)





Summary of computational 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 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23653&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23653&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23653&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Box-Cox Linearity Plot
# observations x61
maximum correlation0.791437349792324
optimal lambda(x)0.17
Residual SD (orginial)1190.72180616189
Residual SD (transformed)1183.72859466254

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 61 \tabularnewline
maximum correlation & 0.791437349792324 \tabularnewline
optimal lambda(x) & 0.17 \tabularnewline
Residual SD (orginial) & 1190.72180616189 \tabularnewline
Residual SD (transformed) & 1183.72859466254 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23653&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]61[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.791437349792324[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]0.17[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]1190.72180616189[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]1183.72859466254[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23653&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23653&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 Linearity Plot
# observations x61
maximum correlation0.791437349792324
optimal lambda(x)0.17
Residual SD (orginial)1190.72180616189
Residual SD (transformed)1183.72859466254


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(x1,y)
if (mx < abs(c[i]))
{
mx <- abs(c[i])
mxli <- l[i]
}
}
c
mx
mxli
if (mxli != 0)
{
x1 <- (x^mxli - 1) / mxli
} else {
x1 <- log(x)
}
r<-lm(y~x)
se <- sqrt(var(r$residuals))
r1 <- lm(y~x1)
se1 <- sqrt(var(r1$residuals))
bitmap(file='test1.png')
plot(l,c,main='Box-Cox Linearity Plot',xlab='Lambda',ylab='correlation')
grid()
dev.off()
bitmap(file='test2.png')
plot(x,y,main='Linear Fit of Original Data',xlab='x',ylab='y')
abline(r)
grid()
mtext(paste('Residual Standard Deviation = ',se))
dev.off()
bitmap(file='test3.png')
plot(x1,y,main='Linear Fit of Transformed Data',xlab='x',ylab='y')
abline(r1)
grid()
mtext(paste('Residual Standard Deviation = ',se1))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Box-Cox Linearity 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(x)',header=TRUE)
a<-table.element(a,mxli)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Residual SD (orginial)',header=TRUE)
a<-table.element(a,se)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Residual SD (transformed)',header=TRUE)
a<-table.element(a,se1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')