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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 computationSat, 07 Nov 2009 12:15:53 -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/07/t1257621398w178p98qfp284g0.htm/, Retrieved Mon, 06 May 2024 10:49:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54479, Retrieved Mon, 06 May 2024 10:49:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact188

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [] [2009-11-04 19:04:39] [3af9fa3d2c04a43d660a9a466bdfbaa0]
-    D  [Bivariate Explorative Data Analysis] [Workshop 5] [2009-11-07 18:22:43] [85be98bd9ebcfd4d73e77f8552419c9a]
-    D      [Bivariate Explorative Data Analysis] [Workshop 5] [2009-11-07 19:15:53] [5cd0e65b1f56b3935a0672588b930e12] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
 -0.06 
 -0.05 
 -0.05 
 -0.03 
 0.00 
 0.01 
 0.02 
 -0.00 
 -0.01 
 0.03 
 -0.00 
 -0.06 
 -0.09 
 -0.12 
 -0.11 
 -0.11 
 -0.12 
 -0.11 
 -0.07 
 -0.07 
 -0.07 
 -0.07 
 -0.05 
 -0.03 
 -0.02 
 -0.02 
 -0.00 
 -0.01 
 -0.01 
 0.01 
 0.02 
 0.02 
 0.01 
 0.03 
 0.04 
 0.04 
 0.03 
 0.04 
 0.04 
 0.03 
 0.06 
 0.08 
 0.09 
 0.08 
 0.09 
 0.10 
 0.08 
 0.06 
 0.05 
 0.07 
 0.06 
 0.03 
 0.01 
 -0.01 
 0.01 
 0.00 
 -0.01 
 0.01 
 0.04 
 0.06
Dataseries Y:
Download CSV
Histogram 
 0.33 
 0.21 
 0.02 
 -0.00 
 -0.15 
 -0.21 
 -0.17 
 -0.16 
 -0.44 
 -0.55 
 -0.67 
 -0.78 
 -0.71 
 -0.79 
 -0.78 
 -0.93 
 -1.10 
 -0.91 
 -0.92 
 -0.83 
 -0.34 
 -0.34 
 -0.20 
 -0.14 
 -0.10 
 -0.16 
 -0.21 
 -0.22 
 -0.30 
 -0.13 
 -0.19 
 -0.28 
 -0.18 
 -0.06 
 0.22 
 0.17 
 -0.13 
 0.22 
 0.08 
 0.57 
 0.72 
 0.95 
 0.59 
 0.29 
 0.47 
 1.08 
 1.27 
 1.54 
 1.99 
 1.58 
 1.03 
 0.35 
 -0.09 
 -0.25 
 -0.70 
 -0.94 
 -1.08 
 -1.43 
 -1.69 
 -1.80

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54479&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]3 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=54479&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54479&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c-0.121755437753234
b7.46737348059588

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.121755437753234 \tabularnewline
b & 7.46737348059588 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54479&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.121755437753234[/C][/ROW]
[ROW][C]b[/C][C]7.46737348059588[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54479&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54479&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]
c-0.121755437753234
b7.46737348059588






Descriptive Statistics about e[t]
# observations60
minimum-2.12628697108252
Q1-0.188623838485498
median-0.0259076948437866
mean-2.33464867808545e-17
Q30.297460979186007
maximum1.73838676372344

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -2.12628697108252 \tabularnewline
Q1 & -0.188623838485498 \tabularnewline
median & -0.0259076948437866 \tabularnewline
mean & -2.33464867808545e-17 \tabularnewline
Q3 & 0.297460979186007 \tabularnewline
maximum & 1.73838676372344 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54479&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]-2.12628697108252[/C][/ROW]
[ROW][C]Q1[/C][C]-0.188623838485498[/C][/ROW]
[ROW][C]median[/C][C]-0.0259076948437866[/C][/ROW]
[ROW][C]mean[/C][C]-2.33464867808545e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.297460979186007[/C][/ROW]
[ROW][C]maximum[/C][C]1.73838676372344[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54479&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54479&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-2.12628697108252
Q1-0.188623838485498
median-0.0259076948437866
mean-2.33464867808545e-17
Q30.297460979186007
maximum1.73838676372344


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')