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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, 28 Oct 2009 14:19:41 -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/28/t12567612093zzypnpoak00622.htm/, Retrieved Mon, 06 May 2024 03:53:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51806, Retrieved Mon, 06 May 2024 03:53:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [Workshop 4] [2009-10-28 19:51:33] [85be98bd9ebcfd4d73e77f8552419c9a]
-    D    [Bivariate Explorative Data Analysis] [Workshop 4] [2009-10-28 20:04:10] [85be98bd9ebcfd4d73e77f8552419c9a]
-    D        [Bivariate Explorative Data Analysis] [Workshop 4] [2009-10-28 20:19:41] [5cd0e65b1f56b3935a0672588b930e12] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3.04
3.12
3.21
3.34
3.45
3.74
4.02
4.24
4.87
5.62
6.02
5.98
5.89
5.76
5.58
5.39
5.19
5.16
5.2
5.25
5.26
5.21
5.18
5.13
5.03
5.01
4.87
4.86
4.82
4.69
4.65
4.61
4.47
4.37
4.29
4.2
4.19
4.09
3.88
3.87
3.74
3.61
3.43
3.29
3.18
3.07
3.02
2.97
2.98
3.01
3.06
3.12
3.16
3.19
3.21
3.27
3.36
3.45
3.52
3.58
Dataseries Y:
Download CSV
Histogram 
0.491217355
0.503850111
0.509039441
0.536704225
0.574791423
0.587191169
0.611785216
0.570544558
0.552866603
0.616889289
0.563457407
0.484268459
0.445930128
0.402101833
0.413401419
0.413187983
0.403072614
0.414786234
0.459762651
0.461638714
0.471065341
0.463778706
0.494052946
0.517870215
0.538913087
0.531551814
0.555340925
0.547804259
0.547398738
0.57028626
0.585036825
0.591807104
0.572791649
0.602699138
0.628783976
0.617373204
0.609303575
0.621566676
0.624912384
0.613222117
0.664110905
0.692135811
0.701675951
0.68267419
0.711416337
0.719891159
0.692711638
0.665736869
0.66184245
0.690182116
0.675733321
0.620587875
0.597400689
0.57383352
0.59044317
0.581029636
0.556251947
0.592536616
0.641026011
0.669884956

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51806&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]2 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=51806&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51806&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c0.82913697494411
b-0.061297247920969

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.82913697494411 \tabularnewline
b & -0.061297247920969 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51806&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.82913697494411[/C][/ROW]
[ROW][C]b[/C][C]-0.061297247920969[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51806&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51806&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]
c0.82913697494411
b-0.061297247920969






Descriptive Statistics about e[t]
# observations60
minimum-0.151575986264366
Q1-0.0435744623023302
median0.0171126406072111
mean1.38066370402451e-18
Q30.0418572136160574
maximum0.132242847371737

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.151575986264366 \tabularnewline
Q1 & -0.0435744623023302 \tabularnewline
median & 0.0171126406072111 \tabularnewline
mean & 1.38066370402451e-18 \tabularnewline
Q3 & 0.0418572136160574 \tabularnewline
maximum & 0.132242847371737 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51806&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]-0.151575986264366[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0435744623023302[/C][/ROW]
[ROW][C]median[/C][C]0.0171126406072111[/C][/ROW]
[ROW][C]mean[/C][C]1.38066370402451e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0418572136160574[/C][/ROW]
[ROW][C]maximum[/C][C]0.132242847371737[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51806&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51806&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-0.151575986264366
Q1-0.0435744623023302
median0.0171126406072111
mean1.38066370402451e-18
Q30.0418572136160574
maximum0.132242847371737


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')