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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 computationTue, 22 Dec 2009 09:25:12 -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/Dec/22/t1261499308n9n9pfk9osqa1u4.htm/, Retrieved Sat, 04 May 2024 11:03:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70459, Retrieved Sat, 04 May 2024 11:03:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
-   PD  [Bivariate Data Series] [Reproduction Part 1] [2009-10-26 18:51:43] [96e597a9107bfe8c07649cce3d4f6fec]
- RMPD    [Bivariate Explorative Data Analysis] [JJ Workshop 4, De...] [2009-10-26 19:42:48] [96e597a9107bfe8c07649cce3d4f6fec]
-    D      [Bivariate Explorative Data Analysis] [JJ Workshop 4, de...] [2009-10-27 18:56:34] [96e597a9107bfe8c07649cce3d4f6fec]
-  M D          [Bivariate Explorative Data Analysis] [Paper, Partial Co...] [2009-12-22 16:25:12] [e31f2fa83f4a5291b9a51009566cf69b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2,26
 1,54 
14,64
 8,17 
3,20
 4,47 
-2,74
 -4,34 
19,08
 19,20 
12,03
 -3,34 
-3,50
 -3,79 
-0,85
 -3,00 
-5,80
 6,21 
-20,01
 -14,64 
3,02
 1,20 
1,31
 -5,49 
-3,80
 -9,18 
3,91
 -6,01 
-4,91
 4,36 
-18,80
 -13,29 
5,83
 7,11 
1,18
 -8,31 
1,39
 -2,15 
9,66
 -2,52 
-3,05
 2,31 
-17,62
 -10,77 
4,54
 14,93 
-0,03
 -12,31 
1,09
 0,51 
5,56
 9,18 
5,38
 11,08 
-6,34
 -7,50 
9,24
 12,07 
-2,87
 -12,65
Dataseries Y:
Download CSV
Histogram 
 -6,24 
 -4,68 
 10,70 
 0,96 
 -4,25 
 9,83 
 -14,13 
 -4,49 
 12,82 
 8,93 
 2,27 
 -0,07 
 -7,56 
 -6,49 
 1,86 
 0,17 
 -4,20 
 11,65 
 -21,36 
 -6,71 
 10,77 
 3,41 
 6,18 
 -0,74 
 -4,70 
 -3,27 
 11,52 
 -3,99 
 4,28 
 9,57 
 -20,17 
 -4,97 
 9,48 
 10,75 
 6,95 
 -4,23 
 -0,27 
 -1,27 
 11,81 
 -1,48 
 1,61 
 9,77 
 -15,08 
 -2,89 
 5,08 
 14,61 
 5,71 
 -7,58 
 1,35 
 2,43 
 -1,25 
 6,22 
 -1,98 
 4,49 
 -15,42 
 -10,25 
 7,98 
 9,70 
 -5,40 
 -9,89

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 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 & 12 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70459&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]12 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=70459&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70459&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 time12 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c0.348075723875386
b0.768238843676755

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.348075723875386 \tabularnewline
b & 0.768238843676755 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70459&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.348075723875386[/C][/ROW]
[ROW][C]b[/C][C]0.768238843676755[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70459&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70459&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]
c0.348075723875386
b0.768238843676755






Descriptive Statistics about e[t]
# observations60
minimum-12.3731012922011
Q1-4.03737840770882
median0.221791831569432
mean-3.03582029306804e-16
Q34.07778802154344
maximum8.1681103973485

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -12.3731012922011 \tabularnewline
Q1 & -4.03737840770882 \tabularnewline
median & 0.221791831569432 \tabularnewline
mean & -3.03582029306804e-16 \tabularnewline
Q3 & 4.07778802154344 \tabularnewline
maximum & 8.1681103973485 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70459&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]-12.3731012922011[/C][/ROW]
[ROW][C]Q1[/C][C]-4.03737840770882[/C][/ROW]
[ROW][C]median[/C][C]0.221791831569432[/C][/ROW]
[ROW][C]mean[/C][C]-3.03582029306804e-16[/C][/ROW]
[ROW][C]Q3[/C][C]4.07778802154344[/C][/ROW]
[ROW][C]maximum[/C][C]8.1681103973485[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70459&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70459&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]
# observations60
minimum-12.3731012922011
Q1-4.03737840770882
median0.221791831569432
mean-3.03582029306804e-16
Q34.07778802154344
maximum8.1681103973485


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')