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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, 04 Nov 2009 04:01:39 -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/04/t1257332550451w1plcajmjmva.htm/, Retrieved Mon, 29 Apr 2024 15:05:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53549, Retrieved Mon, 29 Apr 2024 15:05:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

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] [werkloosheid mann...] [2009-11-04 10:37:31] [ba905ddf7cdf9ecb063c35348c4dab2e]
-    D          [Bivariate Explorative Data Analysis] [werkloosheid vrou...] [2009-11-04 11:01:39] [244731fa3e7e6c85774b8c0902c58f85] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1470
1849
1387
1592
1590
1798
1935
1887
2027
2080
1556
1682
1785
1869
1781
2082
2571
1862
1938
1505
1767
1607
1578
1495
1615
1700
1337
1531
1623
1543
1640
1524
1429
1827
1603
1351
1267
1741
1384
1392
1644
1661
1525
1718
1393
1784
1454
1344
1693
1393
1191
1340
1166
1238
1443
1279
1279
1651
Dataseries Y:
Download CSV
Histogram 
8,9
8,2
7,6
7,7
8,1
8,3
8,3
7,9
7,8
8
8,5
8,6
8,5
8
7,8
8
8,2
8,3
8,2
8,1
8
7,8
7,8
7,7
7,6
7,6
7,6
7,8
8
8
7,9
7,7
7,4
6,9
6,7
6,5
6,4
6,7
6,8
6,9
6,9
6,7
6,4
6,2
5,9
6,1
6,7
6,8
6,6
6,4
6,4
6,7
7,1
7,1
6,9
6,4
6
6

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'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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53549&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53549&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53549&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Model: Y[t] = c + b X[t] + e[t]
c5.0401384399708
b0.00145372361216427

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 5.0401384399708 \tabularnewline
b & 0.00145372361216427 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53549&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]5.0401384399708[/C][/ROW]
[ROW][C]b[/C][C]0.00145372361216427[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53549&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53549&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]
c5.0401384399708
b0.00145372361216427






Descriptive Statistics about e[t]
# observations58
minimum-1.53358136407185
Q1-0.502952014985763
median0.143732455319940
mean-7.00076820030252e-17
Q30.474797777344224
maximum1.72288785014772

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 58 \tabularnewline
minimum & -1.53358136407185 \tabularnewline
Q1 & -0.502952014985763 \tabularnewline
median & 0.143732455319940 \tabularnewline
mean & -7.00076820030252e-17 \tabularnewline
Q3 & 0.474797777344224 \tabularnewline
maximum & 1.72288785014772 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53549&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]-1.53358136407185[/C][/ROW]
[ROW][C]Q1[/C][C]-0.502952014985763[/C][/ROW]
[ROW][C]median[/C][C]0.143732455319940[/C][/ROW]
[ROW][C]mean[/C][C]-7.00076820030252e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.474797777344224[/C][/ROW]
[ROW][C]maximum[/C][C]1.72288785014772[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53549&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53549&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-1.53358136407185
Q1-0.502952014985763
median0.143732455319940
mean-7.00076820030252e-17
Q30.474797777344224
maximum1.72288785014772


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')