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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 12:33:16 -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/t1256754884t8nyuf4hlro30t6.htm/, Retrieved Mon, 06 May 2024 10:24:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51712, Retrieved Mon, 06 May 2024 10:24:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [Part 2, ln Y[t] =...] [2009-10-28 18:33:16] [026d431dc78a3ce53a040b5408fc0322] [Current]
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Dataseries X:
4.75
4.71
4.74
4.92
4.43
4.66
4.82
4.84
4.79
4.95
4.51
4.57
4.73
4.79
4.82
4.97
4.51
4.74
4.93
4.91
4.88
4.97
4.62
4.69
4.91
4.82
4.93
5.06
4.54
4.83
5.04
5.03
5.00
5.14
4.83
4.90
5.04
5.00
5.12
5.17
4.76
4.95
5.10
5.16
5.12
5.12
4.91
5.06
5.02
5.12
5.11
5.23
4.83
4.97
5.20
5.17
5.11
5.20
4.80
4.90
5.09
Dataseries Y:
4.70
4.60
4.46
4.71
4.36
4.34
4.74
4.60
4.55
5.16
4.42
4.49
4.88
4.80
4.65
4.90
4.15
4.72
4.79
4.72
4.84
5.34
4.51
4.76
4.92
4.68
4.92
5.03
4.74
4.79
4.88
4.86
5.23
5.24
4.69
5.06
5.17
4.83
5.04
5.14
4.60
4.94
5.13
4.91
5.13
5.76
5.04
5.08
5.21
5.11
5.31
5.16
4.82
5.04
5.14
5.13
5.14
5.67
4.98
4.90
5.13




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=51712&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=51712&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51712&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]
c-1.44776556151791
b1.29216030998395

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -1.44776556151791 \tabularnewline
b & 1.29216030998395 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51712&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-1.44776556151791[/C][/ROW]
[ROW][C]b[/C][C]1.29216030998395[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51712&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51712&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]
c-1.44776556151791
b1.29216030998395







Descriptive Statistics about e[t]
# observations61
minimum-0.309781637999274
Q1-0.128095225599916
median-0.0120150706079414
mean-2.79338708438562e-18
Q30.0657288208976769
maximum0.591904774400084

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -0.309781637999274 \tabularnewline
Q1 & -0.128095225599916 \tabularnewline
median & -0.0120150706079414 \tabularnewline
mean & -2.79338708438562e-18 \tabularnewline
Q3 & 0.0657288208976769 \tabularnewline
maximum & 0.591904774400084 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51712&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]-0.309781637999274[/C][/ROW]
[ROW][C]Q1[/C][C]-0.128095225599916[/C][/ROW]
[ROW][C]median[/C][C]-0.0120150706079414[/C][/ROW]
[ROW][C]mean[/C][C]-2.79338708438562e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0657288208976769[/C][/ROW]
[ROW][C]maximum[/C][C]0.591904774400084[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51712&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51712&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-0.309781637999274
Q1-0.128095225599916
median-0.0120150706079414
mean-2.79338708438562e-18
Q30.0657288208976769
maximum0.591904774400084



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')