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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, 03 Nov 2009 10:20:47 -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/03/t12572689292dymhyt1a2c394n.htm/, Retrieved Wed, 01 May 2024 19:01:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53259, Retrieved Wed, 01 May 2024 19:01:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Bivariate Explorative Data Analysis] [WS5] [2009-11-03 17:20:47] [612b7913d2a3b4fa79d126829bd148db] [Current]
-    D    [Bivariate Explorative Data Analysis] [reeks X t.o.v. Z] [2009-11-04 17:20:11] [cd6314e7e707a6546bd4604c9d1f2b69]
-    D    [Bivariate Explorative Data Analysis] [reeks Y t.o.v. Z] [2009-11-04 17:23:26] [cd6314e7e707a6546bd4604c9d1f2b69]
Feedback Forum
2009-11-04 18:13:38 [Joris Van Mol] [reply] 
Ik heb een aantal verbeteringen gedaan aan de WS en heb ze hieronder geblogd:

X – Z

http://www.freestatistics.org/blog/index.php?v=date/2009/Nov/04/t1257356673sd7v3rs25fitwfz.htm/

Y-Z

http://www.freestatistics.org/blog/index.php?v=date/2009/Nov/04/t12573567847saojni8poiddi2.htm/

e(t) – e’(t)

http://www.freestatistics.org/blog/index.php?v=date/2009/Nov/04/t1257357814eb6mtjna6mq8r5g.htm/

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25.5
25.6
23.7
22
21.3
20.7
20.4
20.3
20.4
19.8
19.5
23.1
23.5
23.5
22.9
21.9
21.5
20.5
20.2
19.4
19.2
18.8
18.8
22.6
23.3
23
21.4
19.9
18.8
18.6
18.4
18.6
19.9
19.2
18.4
21.1
20.5
19.1
18.1
17
17.1
17.4
16.8
15.3
14.3
13.4
15.3
22.1
23.7
22.2
19.5
16.6
17.3
19.8
21.2
21.5
20.6
19.1
19.6
23.5
24
Dataseries Y:
Download CSV
Histogram 
-11,764
-11,664
-10,178
-10,378
-10,278
-9,176
-9,176
-9,176
-10,132
-10,132
-10,532
-10,542
-10,542
-10,442
-11,408
-11,408
-11,208
-9,45
-9,35
-9,35
-7,628
-7,928
-8,528
-8,272
-8,572
-8,472
-9,01
-8,91
-8,81
-7,726
-7,826
-8,026
-7,024
-7,224
-7,624
-9,21
-9,31
-9,51
-7,806
-7,906
-7,606
-7,716
-7,716
-8,116
-6,776
-7,076
-6,776
-11,088
-10,988
-11,388
-7,842
-8,142
-7,742
-9,712
-9,112
-8,912
-8,538
-8,838
-8,738
-8,238
-8,138

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=53259&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=53259&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53259&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]
c-1.61191614432958
b-0.367659961969526

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -1.61191614432958 \tabularnewline
b & -0.367659961969526 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53259&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-1.61191614432958[/C][/ROW]
[ROW][C]b[/C][C]-0.367659961969526[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53259&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53259&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]
c-1.61191614432958
b-0.367659961969526






Descriptive Statistics about e[t]
# observations61
minimum-1.75071459726466
Q1-0.639988829250555
median-0.00407657064333192
mean1.37427068814064e-17
Q30.469839330477435
maximum2.29775523159820

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -1.75071459726466 \tabularnewline
Q1 & -0.639988829250555 \tabularnewline
median & -0.00407657064333192 \tabularnewline
mean & 1.37427068814064e-17 \tabularnewline
Q3 & 0.469839330477435 \tabularnewline
maximum & 2.29775523159820 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53259&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]-1.75071459726466[/C][/ROW]
[ROW][C]Q1[/C][C]-0.639988829250555[/C][/ROW]
[ROW][C]median[/C][C]-0.00407657064333192[/C][/ROW]
[ROW][C]mean[/C][C]1.37427068814064e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.469839330477435[/C][/ROW]
[ROW][C]maximum[/C][C]2.29775523159820[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53259&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53259&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]
# observations61
minimum-1.75071459726466
Q1-0.639988829250555
median-0.00407657064333192
mean1.37427068814064e-17
Q30.469839330477435
maximum2.29775523159820


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')