FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 11:37:40 -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/t1257273527qcchjjgcjs0s1qi.htm/, Retrieved Wed, 01 May 2024 22:25:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53322, Retrieved Wed, 01 May 2024 22:25:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact203

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] [workshop 5] [2009-11-03 18:37:40] [6198946fb53eb5eb18db46bb758f7fde] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-0,533226576
-0,515978057
-0,477093095
-0,496333869
-0,558827111
-0,581203315
-0,559508891
-0,526763132
-0,485216419
-0,488433897
-0,534946188
-0,523998828
-0,540816723
-0,552659929
-0,562550228
-0,572475926
-0,551776608
-0,529103402
-0,475390277
-0,471325588
-0,483238705
-0,488910901
-0,480923869
-0,463863837
-0,441495171
-0,434380513
-0,43007547
-0,430772563
-0,403799892
-0,43120666
-0,452248414
-0,457170432
-0,467120671
-0,471652125
-0,504228836
-0,479929931
-0,502923197
-0,524137056
-0,524042456
-0,541890172
-0,48902791
-0,472776364
-0,489501826
-0,485214052
-0,46030773
-0,468320878
-0,470662125
-0,443154969
-0,455964052
-0,489908091
-0,480143313
-0,493100702
-0,500777231
-0,552228157
-0,526974209
-0,521835543
-0,536568007
-0,536564655
-0,533739402
-0,536517444
Dataseries Y:
Download CSV
Histogram 
0,0142377
0,05948486
0,1525919
0,12065245
0,00982269
-0,03951274
-0,00147403
0,03059889
0,10436959
0,08331938
-0,01716591
0,01109873
-0,01768092
-0,02931767
-0,06896155
-0,08861504
-0,08324867
-0,05371193
0,06273226
0,07767516
0,06579092
0,05516475
0,05925245
0,08543882
0,09550461
0,08896114
0,07296073
0,0845536
0,10957533
0,10009183
0,06547486
0,05005369
0,04102925
0,03095616
-0,01776122
0,00992901
-0,00692717
-0,0119645
-0,0060741
-0,04384874
0,04100349
0,0704824
0,03940004
0,05244081
0,08466181
0,04539119
0,00405616
0,08533605
0,06064081
0,01054517
0,02504058
0,01554287
-0,00581619
-0,08928089
-0,05639107
-0,04552528
-0,06380895
-0,07245358
-0,0661626
-0,06886088

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=53322&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=53322&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53322&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]
c0.611059060929288
b1.18221552481734

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.611059060929288 \tabularnewline
b & 1.18221552481734 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53322&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.611059060929288[/C][/ROW]
[ROW][C]b[/C][C]1.18221552481734[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53322&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53322&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]
c0.611059060929288
b1.18221552481734






Descriptive Statistics about e[t]
# observations60
minimum-0.0505788298107669
Q1-0.023593272155668
median-0.00597356548829838
mean2.96913282444207e-19
Q30.0186399768982567
maximum0.105559702762868

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.0505788298107669 \tabularnewline
Q1 & -0.023593272155668 \tabularnewline
median & -0.00597356548829838 \tabularnewline
mean & 2.96913282444207e-19 \tabularnewline
Q3 & 0.0186399768982567 \tabularnewline
maximum & 0.105559702762868 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53322&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]-0.0505788298107669[/C][/ROW]
[ROW][C]Q1[/C][C]-0.023593272155668[/C][/ROW]
[ROW][C]median[/C][C]-0.00597356548829838[/C][/ROW]
[ROW][C]mean[/C][C]2.96913282444207e-19[/C][/ROW]
[ROW][C]Q3[/C][C]0.0186399768982567[/C][/ROW]
[ROW][C]maximum[/C][C]0.105559702762868[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53322&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53322&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-0.0505788298107669
Q1-0.023593272155668
median-0.00597356548829838
mean2.96913282444207e-19
Q30.0186399768982567
maximum0.105559702762868


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')