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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 computationTue, 15 Dec 2009 06:25:14 -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/Dec/15/t1260883559onovw4e673rym65.htm/, Retrieved Wed, 08 May 2024 09:29:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67892, Retrieved Wed, 08 May 2024 09:29:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87

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] [] [2009-11-13 13:07:31] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   PD      [Bivariate Explorative Data Analysis] [] [2009-12-15 13:25:14] [5858ea01c9bd81debbf921a11363ad90] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
27
29
27
26
24
30
26
28
28
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
18
20
Dataseries Y:
Download CSV
Histogram 
36
35
37
40
41
31
34
31
33
42
41
42
41
40
35
35
47
46
45
41
40
38
40
36
27
27
34
28
31
27
28
19
20
14
15
42
22
17
18
10
15
15
17
12
11
7
10
6
8
3
1
9
14
12
20
24
24
44
60
68
71
76
74
74
73
72
68
60
60
60
58

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67892&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67892&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67892&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c85.2273239699264
b-2.23128236859727

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 85.2273239699264 \tabularnewline
b & -2.23128236859727 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67892&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]85.2273239699264[/C][/ROW]
[ROW][C]b[/C][C]-2.23128236859727[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67892&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67892&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]
c85.2273239699264
b-2.23128236859727






Descriptive Statistics about e[t]
# observations71
minimum-30.8329589665782
Q1-4.94860015087687
median2.16704103342177
mean-7.23013198607122e-16
Q39.32345287640811
maximum17.3983234020190

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 71 \tabularnewline
minimum & -30.8329589665782 \tabularnewline
Q1 & -4.94860015087687 \tabularnewline
median & 2.16704103342177 \tabularnewline
mean & -7.23013198607122e-16 \tabularnewline
Q3 & 9.32345287640811 \tabularnewline
maximum & 17.3983234020190 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67892&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]71[/C][/ROW]
[ROW][C]minimum[/C][C]-30.8329589665782[/C][/ROW]
[ROW][C]Q1[/C][C]-4.94860015087687[/C][/ROW]
[ROW][C]median[/C][C]2.16704103342177[/C][/ROW]
[ROW][C]mean[/C][C]-7.23013198607122e-16[/C][/ROW]
[ROW][C]Q3[/C][C]9.32345287640811[/C][/ROW]
[ROW][C]maximum[/C][C]17.3983234020190[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67892&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67892&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]
# observations71
minimum-30.8329589665782
Q1-4.94860015087687
median2.16704103342177
mean-7.23013198607122e-16
Q39.32345287640811
maximum17.3983234020190


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')