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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationThu, 05 Nov 2009 01:48:18 -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/2009/Nov/05/t1257410950uclp9y3plsud1kl.htm/, Retrieved Fri, 03 May 2024 03:35:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53888, Retrieved Fri, 03 May 2024 03:35:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Partial Correlation] [WS5] [2009-11-04 17:31:42] [868ad9c0049635b9b2c3848f186e9622]
- RMPD    [Bivariate Explorative Data Analysis] [reeks X t.o.v Z] [2009-11-05 08:48:18] [ea241b681aafed79da4b5b99fad98471] [Current]
-    D      [Bivariate Explorative Data Analysis] [reeks Y t.o.v. Z] [2009-11-05 08:51:09] [cd6314e7e707a6546bd4604c9d1f2b69]
-    D        [Bivariate Explorative Data Analysis] [reeks e(t) t.o.v....] [2009-11-05 08:57:02] [cd6314e7e707a6546bd4604c9d1f2b69]
- RMPD          [Pearson Correlation] [check correlatie ...] [2009-11-05 08:59:04] [cd6314e7e707a6546bd4604c9d1f2b69]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,75
1,75
1,55
1,5
1,5
1,1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1,21
1,25
1,25
1,45
1,5
1,5
1,64
1,75
1,93
2
2,17
2,25
2,39
2,5
2,5
2,65
2,75
2,75
2,9
3
3
3
3
3
3
3
3
3
3
3
3
3,18
3,25
3,25
3,23
2,92
2,25
Dataseries Y:
Download CSV
Histogram 
2,93
2,76
2,51
2,51
2,48
2,24
2,12
2,1
2,13
2,12
2,14
2,13
2,13
2,04
2,02
1,92
2,03
2,05
2,08
2,08
2,08
2,08
2,12
2,14
2,13
2,1
2,09
2,1
2,09
2,08
2,07
2,08
2,09
2,11
2,2
2,42
2,46
2,5
2,59
2,75
2,78
2,9
3,03
3,1
3,23
3,36
3,51
3,61
3,67
3,74
3,82
3,89
3,98
4,08
4,14
4,33
4,57
4,63
4,57
4,71
4,54
4,3
4,36
4,61
4,71
4,68
4,91
4,75
4,77
5,18
3,42
2,71

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53888&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53888&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53888&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 time6 seconds
R Server'George Udny Yule' @ 72.249.76.132






Model: Y[t] = c + b X[t] + e[t]
c0.906561126603069
b1.16502717993857

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.906561126603069 \tabularnewline
b & 1.16502717993857 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53888&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.906561126603069[/C][/ROW]
[ROW][C]b[/C][C]1.16502717993857[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53888&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53888&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:

Model: Y[t] = c + b X[t] + e[t]
c0.906561126603069
b1.16502717993857






Descriptive Statistics about e[t]
# observations72
minimum-0.888440492023694
Q1-0.0592083545180761
median0.0184116934583619
mean4.09587487383413e-19
Q30.0785239785218524
maximum0.510401082195349

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 72 \tabularnewline
minimum & -0.888440492023694 \tabularnewline
Q1 & -0.0592083545180761 \tabularnewline
median & 0.0184116934583619 \tabularnewline
mean & 4.09587487383413e-19 \tabularnewline
Q3 & 0.0785239785218524 \tabularnewline
maximum & 0.510401082195349 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53888&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]72[/C][/ROW]
[ROW][C]minimum[/C][C]-0.888440492023694[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0592083545180761[/C][/ROW]
[ROW][C]median[/C][C]0.0184116934583619[/C][/ROW]
[ROW][C]mean[/C][C]4.09587487383413e-19[/C][/ROW]
[ROW][C]Q3[/C][C]0.0785239785218524[/C][/ROW]
[ROW][C]maximum[/C][C]0.510401082195349[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53888&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53888&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations72
minimum-0.888440492023694
Q1-0.0592083545180761
median0.0184116934583619
mean4.09587487383413e-19
Q30.0785239785218524
maximum0.510401082195349


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t]   bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')