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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 computationWed, 28 Oct 2009 13:27:43 -0600
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/Oct/28/t12567581581g7py3fgh9sgq8f.htm/, Retrieved Sun, 05 May 2024 22:59:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51769, Retrieved Sun, 05 May 2024 22:59:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsIlseWS4P2
Estimated Impact131

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]
- RMPD  [Bivariate Explorative Data Analysis] [WS4 Bivariate dat...] [2009-10-27 22:25:17] [8733f8ed033058987ec00f5e71b74854]
-    D      [Bivariate Explorative Data Analysis] [WS4 Y[t] = c + b ...] [2009-10-28 19:27:43] [c6e373ff11c42d4585d53e9e88ed5606] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.800641
0.769764
0.745823
0.762253
0.768403
0.757518
0.772917
0.787774
0.822030
0.830772
0.813537
0.815927
0.832293
0.848464
0.843455
0.826241
0.837661
0.831947
0.814930
0.783085
0.790514
0.788395
0.780579
0.785731
0.792959
0.776337
0.756830
0.769290
0.764877
0.755173
0.739864
0.740138
0.745212
0.729076
0.734107
0.719632
0.702889
0.681013
0.686342
0.679440
0.678058
0.644039
0.634880
0.642797
0.642963
0.634115
0.667780
0.695894
0.750638
0.785423
0.743550
0.755344
0.782167
0.766284
0.758150
0.732601
0.713470
0.709824
0.700869
0.700869
Dataseries Y:
Download CSV
Histogram 
2.08
2.12
2.14
2.13
2.10
2.09
2.10
2.09
2.08
2.07
2.08
2.09
2.11
2.20
2.42
2.46
2.50
2.59
2.75
2.78
2.90
3.03
3.10
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
4.30
4.36
4.61
4.71
4.68
4.91
4.75
4.77
5.18
3.42
2.71
2.29
2.00
1.64
1.30
1.08
1.00
1.00
1.00
1.00

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51769&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51769&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51769&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 time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Model: Y[t] = c + b X[t] + e[t]
c11.5358610355713
b-11.2812862617602

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 11.5358610355713 \tabularnewline
b & -11.2812862617602 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51769&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]11.5358610355713[/C][/ROW]
[ROW][C]b[/C][C]-11.2812862617602[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51769&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51769&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]
c11.5358610355713
b-11.2812862617602






Descriptive Statistics about e[t]
# observations60
minimum-2.62915721457767
Q1-0.597070575016825
median0.379161380058192
mean2.45680212285215e-17
Q30.735344338768435
maximum2.11230112138387

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -2.62915721457767 \tabularnewline
Q1 & -0.597070575016825 \tabularnewline
median & 0.379161380058192 \tabularnewline
mean & 2.45680212285215e-17 \tabularnewline
Q3 & 0.735344338768435 \tabularnewline
maximum & 2.11230112138387 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51769&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]-2.62915721457767[/C][/ROW]
[ROW][C]Q1[/C][C]-0.597070575016825[/C][/ROW]
[ROW][C]median[/C][C]0.379161380058192[/C][/ROW]
[ROW][C]mean[/C][C]2.45680212285215e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.735344338768435[/C][/ROW]
[ROW][C]maximum[/C][C]2.11230112138387[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51769&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51769&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-2.62915721457767
Q1-0.597070575016825
median0.379161380058192
mean2.45680212285215e-17
Q30.735344338768435
maximum2.11230112138387


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')