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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, 27 Oct 2009 12:11:21 -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/27/t1256667160dmp3mjuoesy5ebi.htm/, Retrieved Tue, 07 May 2024 06:34:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51089, Retrieved Tue, 07 May 2024 06:34:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112
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 part2 ex3] [2009-10-27 18:11:21] [95523ebdb89b97dbf680ec91e0b4bca2] [Current]
-    D      [Bivariate Explorative Data Analysis] [Ws 4 part 2 ex 3] [2009-10-28 16:13:55] [62d3ced7fb1c10c35a82e9cb1d0d0e2b]
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Dataseries X:
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.5625
1.5625
1.5625
2.2500
2.2500
2.2500
3.0625
3.0625
4.0000
4.0000
5.0625
5.0625
6.2500
6.2500
6.2500
7.5625
7.5625
7.5625
9.0000
9.0000
9.0000
9.0000
9.0000
9.0000
9.0000
9.0000
9.0000
9.0000
9.0000
9.0000
9.0000
10.5625
10.5625
10.5625
10.5625
7.5625
4.0000
1.0000
1.0000
0.2500
0.0625
0.0625
0.0625
0.0625
0.0625
Dataseries Y:
4.2025
4.4521
4.3681
4.2025
4.3264
4.2436
4.2436
4.3264
4.2849
4.2436
4.2849
4.2436
4.3681
4.2849
4.3681
5.1984
5.4289
5.5225
6.3504
6.9169
6.6564
7.2900
7.8961
8.8209
9.2416
10.7584
11.0889
12.2500
12.6736
12.7449
13.6161
14.5924
14.3641
15.6816
16.4836
16.4025
16.2409
15.5236
16.1604
15.0544
16.1604
16.2409
16.7281
15.9201
16.0801
16.0801
17.5561
18.4900
18.2329
14.5924
9.9225
6.2001
3.2761
1.5876
1.1236
0.7056
0.6084
0.4900
0.1296
0.1225




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51089&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51089&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51089&T=0

As an alternative you can also use a 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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Model: Y[t] = c + b X[t] + e[t]
c2.26158562530901
b1.51394637469476

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 2.26158562530901 \tabularnewline
b & 1.51394637469476 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51089&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]2.26158562530901[/C][/ROW]
[ROW][C]b[/C][C]1.51394637469476[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51089&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51089&T=1

As an alternative you can also use a QR Code:  

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

Model: Y[t] = c + b X[t] + e[t]
c2.26158562530901
b1.51394637469476







Descriptive Statistics about e[t]
# observations60
minimum-3.78830508393815
Q1-0.122404562344079
median0.468067999996225
mean-1.13118426662654e-17
Q30.61069648084406
maximum1.24893503162777

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -3.78830508393815 \tabularnewline
Q1 & -0.122404562344079 \tabularnewline
median & 0.468067999996225 \tabularnewline
mean & -1.13118426662654e-17 \tabularnewline
Q3 & 0.61069648084406 \tabularnewline
maximum & 1.24893503162777 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51089&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]-3.78830508393815[/C][/ROW]
[ROW][C]Q1[/C][C]-0.122404562344079[/C][/ROW]
[ROW][C]median[/C][C]0.468067999996225[/C][/ROW]
[ROW][C]mean[/C][C]-1.13118426662654e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.61069648084406[/C][/ROW]
[ROW][C]maximum[/C][C]1.24893503162777[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51089&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51089&T=2

As an alternative you can also use a QR Code:  

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

Descriptive Statistics about e[t]
# observations60
minimum-3.78830508393815
Q1-0.122404562344079
median0.468067999996225
mean-1.13118426662654e-17
Q30.61069648084406
maximum1.24893503162777



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')