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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 13:31:36 -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/t1257280422zxi4vbw1zot5kw3.htm/, Retrieved Wed, 01 May 2024 20:16:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53394, Retrieved Wed, 01 May 2024 20:16:50 +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)
-     [Trivariate Scatterplots] [Ws5] [2009-11-03 18:30:01] [ba905ddf7cdf9ecb063c35348c4dab2e]
- RMPD  [Partial Correlation] [WS5] [2009-11-03 18:33:47] [ba905ddf7cdf9ecb063c35348c4dab2e]
- RMPD    [Bivariate Explorative Data Analysis] [Bouwvergunningen ...] [2009-11-03 18:39:43] [ba905ddf7cdf9ecb063c35348c4dab2e]
-    D      [Bivariate Explorative Data Analysis] [bouwvergunningen ...] [2009-11-03 18:46:49] [ba905ddf7cdf9ecb063c35348c4dab2e]
-    D          [Bivariate Explorative Data Analysis] [et-et'] [2009-11-03 20:31:36] [244731fa3e7e6c85774b8c0902c58f85] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3,35
2,69
2,13
2,15
2,47
2,63
2,67
2,39
2,29
2,61
3,03
3,13
3,03
2,53
2,33
2,41
2,49
2,51
2,37
2,27
2,25
2,21
2,41
2,47
2,37
2,33
2,25
2,41
2,53
2,53
2,47
2,27
2,01
1,67
1,43
1,31
1,29
1,59
1,69
1,67
1,55
1,35
1,17
1,05
0,83
0,99
1,35
1,45
1,37
1,37
1,41
1,55
1,63
1,47
1,15
0,73
0,41
0,41
Dataseries Y:
Download CSV
Histogram 
-195,627
200,102
-245,169
-73,627
-109,085
82,186
235,915
238,102
378,102
481,289
-76,169
49,831
152,831
236,831
148,831
399,644
838,457
95,999
155,27
-277,73
17,728
-75,356
-20,711
-36,795
83,205
151,476
-244,982
-67,711
-9,169
-89,169
24,56
-91,44
-169,711
295,205
54,476
-164,066
-214,608
259,392
-97,608
-139,795
62,018
79,018
-6,795
219,663
-71,879
302,392
-127,982
-237,982
161,205
-55,15
-240,421
-158,337
-466,169
-461,085
-306,272
-436,814
-403,356
-31,356

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=53394&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=53394&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53394&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]
c-233.550787327971
b118.963362004060

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -233.550787327971 \tabularnewline
b & 118.963362004060 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53394&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-233.550787327971[/C][/ROW]
[ROW][C]b[/C][C]118.963362004060[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53394&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53394&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-233.550787327971
b118.963362004060






Descriptive Statistics about e[t]
# observations58
minimum-426.528492738646
Q1-151.076626321042
median-45.380234099783
mean1.27005685661861e-14
Q3116.842220630887
maximum775.789015937862

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 58 \tabularnewline
minimum & -426.528492738646 \tabularnewline
Q1 & -151.076626321042 \tabularnewline
median & -45.380234099783 \tabularnewline
mean & 1.27005685661861e-14 \tabularnewline
Q3 & 116.842220630887 \tabularnewline
maximum & 775.789015937862 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53394&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]58[/C][/ROW]
[ROW][C]minimum[/C][C]-426.528492738646[/C][/ROW]
[ROW][C]Q1[/C][C]-151.076626321042[/C][/ROW]
[ROW][C]median[/C][C]-45.380234099783[/C][/ROW]
[ROW][C]mean[/C][C]1.27005685661861e-14[/C][/ROW]
[ROW][C]Q3[/C][C]116.842220630887[/C][/ROW]
[ROW][C]maximum[/C][C]775.789015937862[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53394&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53394&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]
# observations58
minimum-426.528492738646
Q1-151.076626321042
median-45.380234099783
mean1.27005685661861e-14
Q3116.842220630887
maximum775.789015937862


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')