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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 computationThu, 12 Nov 2009 03:31:41 -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/12/t1258021994l0lpg1j8dheqac6.htm/, Retrieved Sat, 04 May 2024 01:13:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55923, Retrieved Sat, 04 May 2024 01:13:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139

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] [3/11/2009] [2009-11-02 22:01:32] [b98453cac15ba1066b407e146608df68]
-   PD    [Bivariate Explorative Data Analysis] [bivariate] [2009-11-12 10:31:41] [21abcd6b6f55e53f03dbc7aec5059429] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
24
23
24
24
27
28
25
19
19
19
20
16
22
21
25
29
28
25
26
24
28
28
28
28
32
31
22
29
31
29
32
32
31
29
28
28
29
22
26
24
27
27
23
21
19
17
19
21
13
8
5
10
6
6
8
11
12
13
19
19
Dataseries Y:
Download CSV
Histogram 
22,9
22,6
22,3
22,3
22,6
23,1
22,8
22,5
22,9
23,1
23,1
23,2
22,5
22,6
22,9
22,6
22,4
21,7
22
22,2
21,9
21,6
21,6
21,2
21,2
21,5
21,6
21,7
21,8
21,8
21,8
21,3
21,3
21,4
21,1
21,5
22,2
22,9
23,1
23,5
23,6
24,4
24,2
25,2
25,8
25,9
25,4
25,5
24,7
23,1
22,6
22,3
21,9
20,6
20,6
19,6
18,9
18,3
19,2
18,8

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'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=55923&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=55923&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55923&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Model: Y[t] = c + b X[t] + e[t]
c22.1190662932851
b0.0087797030641483

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 22.1190662932851 \tabularnewline
b & 0.0087797030641483 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55923&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]22.1190662932851[/C][/ROW]
[ROW][C]b[/C][C]0.0087797030641483[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55923&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55923&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]
c22.1190662932851
b0.0087797030641483






Descriptive Statistics about e[t]
# observations60
minimum-3.93320243311902
Q1-0.789897979081242
median0.00266142704705364
mean3.26778534787131e-17
Q30.739491872450833
maximum3.63167875462439

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -3.93320243311902 \tabularnewline
Q1 & -0.789897979081242 \tabularnewline
median & 0.00266142704705364 \tabularnewline
mean & 3.26778534787131e-17 \tabularnewline
Q3 & 0.739491872450833 \tabularnewline
maximum & 3.63167875462439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55923&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]-3.93320243311902[/C][/ROW]
[ROW][C]Q1[/C][C]-0.789897979081242[/C][/ROW]
[ROW][C]median[/C][C]0.00266142704705364[/C][/ROW]
[ROW][C]mean[/C][C]3.26778534787131e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.739491872450833[/C][/ROW]
[ROW][C]maximum[/C][C]3.63167875462439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55923&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55923&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-3.93320243311902
Q1-0.789897979081242
median0.00266142704705364
mean3.26778534787131e-17
Q30.739491872450833
maximum3.63167875462439


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')