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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 computationWed, 28 Oct 2009 11:06:24 -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/t1256749737vemdbn69ehipjrg.htm/, Retrieved Mon, 06 May 2024 04:45:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51593, Retrieved Mon, 06 May 2024 04:45:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [EDA bivariate par...] [2009-10-28 17:06:24] [9a3898f49d4e2f0208d1968305d88f0a] [Current]
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Dataseries X:
8.29
8.29
8.33
8.36
8.38
8.28
8.33
8.35
8.42
8.35
8.41
8.54
8.34
8.39
8.41
8.36
8.50
8.46
8.45
8.35
8.57
8.32
8.44
8.46
8.34
8.37
8.39
8.53
8.53
8.40
8.50
8.40
8.53
8.47
8.55
8.52
8.56
8.48
8.49
8.68
8.65
8.47
8.73
8.44
8.62
8.76
8.68
8.76
8.80
8.68
8.83
8.79
8.61
8.60
8.57
8.45
8.50
8.35
8.33
8.41
8.32
Dataseries Y:
8.28
8.05
8.26
8.27
8.19
8.22
8.16
8.20
8.35
8.31
8.34
8.42
8.40
8.17
8.46
8.33
8.38
8.33
8.29
8.34
8.50
8.27
8.45
8.37
8.39
8.17
8.40
8.41
8.42
8.35
8.34
8.39
8.55
8.34
8.45
8.49
8.57
8.41
8.44
8.54
8.43
8.42
8.41
8.43
8.48
8.59
8.56
8.60
8.70
8.35
8.64
8.55
8.28
8.30
8.10
8.25
8.33
8.24
8.26
8.36
8.34




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=51593&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=51593&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51593&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]
c2.80231361950952
b0.656422341797436

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 2.80231361950952 \tabularnewline
b & 0.656422341797436 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51593&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]2.80231361950952[/C][/ROW]
[ROW][C]b[/C][C]0.656422341797436[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51593&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51593&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]
c2.80231361950952
b0.656422341797436







Descriptive Statistics about e[t]
# observations61
minimum-0.327853088713548
Q1-0.0434401735181112
median0.0184038049583501
mean-1.53365729439906e-18
Q30.0577891454661955
maximum0.148711134704427

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -0.327853088713548 \tabularnewline
Q1 & -0.0434401735181112 \tabularnewline
median & 0.0184038049583501 \tabularnewline
mean & -1.53365729439906e-18 \tabularnewline
Q3 & 0.0577891454661955 \tabularnewline
maximum & 0.148711134704427 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51593&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-0.327853088713548[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0434401735181112[/C][/ROW]
[ROW][C]median[/C][C]0.0184038049583501[/C][/ROW]
[ROW][C]mean[/C][C]-1.53365729439906e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0577891454661955[/C][/ROW]
[ROW][C]maximum[/C][C]0.148711134704427[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51593&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51593&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]
# observations61
minimum-0.327853088713548
Q1-0.0434401735181112
median0.0184038049583501
mean-1.53365729439906e-18
Q30.0577891454661955
maximum0.148711134704427



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')