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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 computationWed, 11 Nov 2009 06:23:04 -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/11/t1257945835i1ni5x7zv0ns4lz.htm/, Retrieved Fri, 26 Apr 2024 17:12:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55573, Retrieved Fri, 26 Apr 2024 17:12:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [3/11/2009] [2009-11-02 21:54:51] [b98453cac15ba1066b407e146608df68]
- RMPD    [Bivariate Explorative Data Analysis] [WS6: Asumpties vo...] [2009-11-11 13:23:04] [b8ce264f75295a954feffaf60221d1b0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100,00
106,54
127,63
141,72
147,95
142,16
147,95
155,82
164,13
159,16
147,14
159,16
178,85
200,44
189,43
160,16
157,02
168,91
173,19
175,83
158,78
166,96
171,24
179,55
191,00
196,41
206,80
208,94
224,86
217,31
229,96
252,36
255,25
290,37
269,67
240,53
252,86
265,51
299,31
297,42
277,09
313,59
335,75
370,67
375,33
358,65
334,80
335,05
364,07
350,47
350,16
393,46
405,29
406,86
426,12
422,97
373,63
335,18
329,89
346,32
100,00
106,54
127,63
141,72
147,95
142,16
147,95
155,82
164,13
159,16
147,14
159,16
178,85
200,44
189,43
160,16
157,02
168,91
173,19
175,83
158,78
166,96
171,24
179,55
191,00
196,41
206,80
208,94
224,86
217,31
229,96
252,36
255,25
290,37
269,67
240,53
252,86
265,51
299,31
297,42
277,09
313,59
335,75
370,67
375,33
358,65
334,80
335,05
364,07
350,47
350,16
393,46
405,29
406,86
426,12
422,97
373,63
335,18
329,89
346,32
Dataseries Y:
Download CSV
Histogram 
100,00
100,28
100,00
98,62
98,35
98,35
104,68
104,13
103,58
104,68
104,41
105,79
107,99
108,54
107,99
109,09
107,99
109,09
115,43
115,98
115,70
115,15
112,95
115,15
117,36
117,91
118,46
116,80
116,53
117,63
121,49
123,69
124,52
127,27
125,34
127,00
127,00
127,55
127,27
125,62
125,34
125,62
130,03
130,03
129,75
128,10
126,45
128,10
128,93
128,65
127,55
126,72
127,27
127,00
131,13
131,13
129,75
124,79
122,04
121,76
100,00
100,28
100,00
98,62
98,35
98,35
104,68
104,13
103,58
104,68
104,41
105,79
107,99
108,54
107,99
109,09
107,99
109,09
115,43
115,98
115,70
115,15
112,95
115,15
117,36
117,91
118,46
116,80
116,53
117,63
121,49
123,69
124,52
127,27
125,34
127,00
127,00
127,55
127,27
125,62
125,34
125,62
130,03
130,03
129,75
128,10
126,45
128,10
128,93
128,65
127,55
126,72
127,27
127,00
131,13
131,13
129,75
124,79
122,04
121,76

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55573&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55573&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55573&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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Model: Y[t] = c + b X[t] + e[t]
c93.2479785345798
b0.0994798505421872

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 93.2479785345798 \tabularnewline
b & 0.0994798505421872 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55573&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]93.2479785345798[/C][/ROW]
[ROW][C]b[/C][C]0.0994798505421872[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55573&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55573&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]
c93.2479785345798
b0.0994798505421872






Descriptive Statistics about e[t]
# observations120
minimum-9.61602242229638
Q1-4.044651478153
median-0.31783774826804
mean1.92706094137574e-16
Q34.55525935233817
maximum9.82413301450794

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 120 \tabularnewline
minimum & -9.61602242229638 \tabularnewline
Q1 & -4.044651478153 \tabularnewline
median & -0.31783774826804 \tabularnewline
mean & 1.92706094137574e-16 \tabularnewline
Q3 & 4.55525935233817 \tabularnewline
maximum & 9.82413301450794 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55573&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]120[/C][/ROW]
[ROW][C]minimum[/C][C]-9.61602242229638[/C][/ROW]
[ROW][C]Q1[/C][C]-4.044651478153[/C][/ROW]
[ROW][C]median[/C][C]-0.31783774826804[/C][/ROW]
[ROW][C]mean[/C][C]1.92706094137574e-16[/C][/ROW]
[ROW][C]Q3[/C][C]4.55525935233817[/C][/ROW]
[ROW][C]maximum[/C][C]9.82413301450794[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55573&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55573&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]
# observations120
minimum-9.61602242229638
Q1-4.044651478153
median-0.31783774826804
mean1.92706094137574e-16
Q34.55525935233817
maximum9.82413301450794


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')