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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 computationMon, 26 Oct 2009 15:16:15 -0600
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/Oct/26/t1256591824oeweoq25eh65uud.htm/, Retrieved Thu, 02 May 2024 16:37:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50760, Retrieved Thu, 02 May 2024 16:37:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183

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] [WS 4 model1] [2009-10-26 21:16:15] [51118f1042b56b16d340924f16263174] [Current]
- RMP     [Bivariate Kernel Density Estimation] [WS4 part 2] [2009-10-27 20:49:43] [830e13ac5e5ac1e5b21c6af0c149b21d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.818465
0.800641
0.769764
0.745823
0.762253
0.768403
0.757518
0.772917
0.787774
0.82203
0.830772
0.813537
0.815927
0.832293
0.848464
0.843455
0.826241
0.837661
0.831947
0.81493
0.783085
0.790514
0.788395
0.780579
0.785731
0.792959
0.776337
0.75683
0.76929
0.764877
0.755173
0.739864
0.740138
0.745212
0.729076
0.734107
0.719632
0.702889
0.681013
0.686342
0.67944
0.678058
0.644039
0.63488
0.642797
0.642963
0.634115
0.66778
0.695894
0.750638
0.785423
0.74355
0.755344
0.782167
0.766284
0.75815
0.732601
0.71347
0.709824
0.700869
Dataseries Y:
Download CSV
Histogram 
1076.7
1035.9
1037
1154
1237.2
996.6
1238.2
1153.4
1268.1
1156
1144.5
1232.9
1055.2
1109.7
1079.8
1126.3
1196.8
1130.4
1183.6
1200.9
1426.6
1080.4
1325.4
1230
1125.9
1174.5
1151.9
1439.3
1344.3
1319.1
1257.6
1249.1
1397.1
1348
1548.2
1377.6
1402.9
1167.6
1392.9
1547
1420
1266.4
1280.8
1128.6
1449.5
1511.7
1548.3
1652
1650.5
1370.8
1653.3
1474.3
1418.8
1554.1
1156.6
1223.4
1337.5
1098.9
1037.6
1202.5

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=50760&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=50760&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50760&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]
c2386.00737929229
b-1472.24930380932

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 2386.00737929229 \tabularnewline
b & -1472.24930380932 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50760&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]2386.00737929229[/C][/ROW]
[ROW][C]b[/C][C]-1472.24930380932[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50760&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50760&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]
c2386.00737929229
b-1472.24930380932






Descriptive Statistics about e[t]
# observations60
minimum-322.705741289826
Q1-101.763585719271
median-11.7024728804011
mean1.25779016831492e-15
Q379.7574721851
maximum423.631085653541

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -322.705741289826 \tabularnewline
Q1 & -101.763585719271 \tabularnewline
median & -11.7024728804011 \tabularnewline
mean & 1.25779016831492e-15 \tabularnewline
Q3 & 79.7574721851 \tabularnewline
maximum & 423.631085653541 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50760&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]-322.705741289826[/C][/ROW]
[ROW][C]Q1[/C][C]-101.763585719271[/C][/ROW]
[ROW][C]median[/C][C]-11.7024728804011[/C][/ROW]
[ROW][C]mean[/C][C]1.25779016831492e-15[/C][/ROW]
[ROW][C]Q3[/C][C]79.7574721851[/C][/ROW]
[ROW][C]maximum[/C][C]423.631085653541[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50760&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50760&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-322.705741289826
Q1-101.763585719271
median-11.7024728804011
mean1.25779016831492e-15
Q379.7574721851
maximum423.631085653541


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')