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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 13:16:20 -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/t12567575046uipx4qahnfhgvm.htm/, Retrieved Mon, 06 May 2024 02:58:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51755, Retrieved Mon, 06 May 2024 02:58:07 +0000
QR Codes:

Original text written by user:WS 4 Question 2c
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118

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] [WS 4 y(t) = c + b...] [2009-10-28 17:48:59] [101f710c1bf3d900563184d79f7da6e1]
- RMP     [Kendall tau Rank Correlation] [WS 4 y(t) = c + b...] [2009-10-28 18:25:35] [101f710c1bf3d900563184d79f7da6e1]
- RMPD      [Bivariate Explorative Data Analysis] [WS 4 y(t) = c + b...] [2009-10-28 18:38:05] [101f710c1bf3d900563184d79f7da6e1]
F    D        [Bivariate Explorative Data Analysis] [WS 4 y(t) = c + b...] [2009-10-28 19:03:20] [101f710c1bf3d900563184d79f7da6e1]
-    D            [Bivariate Explorative Data Analysis] [WS 4 y(t) = c + b...] [2009-10-28 19:16:20] [9b6f46453e60f88d91cef176fe926003] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
219,04
216,09
256
237,16
225
240,25
228,01
136,89
265,69
278,89
225
222,01
213,16
234,09
320,41
268,96
237,16
320,41
252,81
193,21
316,84
320,41
302,76
278,89
256
275,56
364,81
316,84
295,84
345,96
265,69
228,01
368,64
313,29
364,81
324
306,25
316,84
445,21
295,84
376,36
392,04
309,76
262,44
380,25
396,01
400
299,29
357,21
345,96
457,96
345,96
392,04
432,64
384,16
313,29
392,04
492,84
428,49
320,41
436,81
449,44
457,96
529
453,69
571,21
501,76
334,89
519,84
497,29
316,84
268,96
256
268,96
313,29
275,56
262,44
334,89
Dataseries Y:
Download CSV
Histogram 
14.5
14.3
15.3
14.4
13.7
14.2
13.5
11.9
14.6
15.6
14.1
14.9
14.2
14.6
17.2
15.4
14.3
17.5
14.5
14.4
16.6
16.7
16.6
16.9
15.7
16.4
18.4
16.9
16.5
18.3
15.1
15.7
18.1
16.8
18.9
19
18.1
17.8
21.5
17.1
18.7
19
16.4
16.9
18.6
19.3
19.4
17.6
18.6
18.1
20.4
18.1
19.6
19.9
19.2
17.8
19.2
22
21.1
19.5
22.2
20.9
22.2
23.5
21.5
24.3
22.8
20.3
23.7
23.3
19.6
18
17.3
16.8
18.2
16.5
16
18.4

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51755&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51755&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51755&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'George Udny Yule' @ 72.249.76.132






Model: Y[t] = c + b X[t] + e[t]
c8.15424167385169
b0.029236861485867

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 8.15424167385169 \tabularnewline
b & 0.029236861485867 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51755&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]8.15424167385169[/C][/ROW]
[ROW][C]b[/C][C]0.029236861485867[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51755&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51755&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]
c8.15424167385169
b0.029236861485867






Descriptive Statistics about e[t]
# observations78
minimum-1.3221834020317
Q1-0.561159697208245
median-0.169026273502245
mean1.37247485011598e-16
Q30.409129444293412
maximum2.3546257831463

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 78 \tabularnewline
minimum & -1.3221834020317 \tabularnewline
Q1 & -0.561159697208245 \tabularnewline
median & -0.169026273502245 \tabularnewline
mean & 1.37247485011598e-16 \tabularnewline
Q3 & 0.409129444293412 \tabularnewline
maximum & 2.3546257831463 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51755&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]78[/C][/ROW]
[ROW][C]minimum[/C][C]-1.3221834020317[/C][/ROW]
[ROW][C]Q1[/C][C]-0.561159697208245[/C][/ROW]
[ROW][C]median[/C][C]-0.169026273502245[/C][/ROW]
[ROW][C]mean[/C][C]1.37247485011598e-16[/C][/ROW]
[ROW][C]Q3[/C][C]0.409129444293412[/C][/ROW]
[ROW][C]maximum[/C][C]2.3546257831463[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51755&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51755&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]
# observations78
minimum-1.3221834020317
Q1-0.561159697208245
median-0.169026273502245
mean1.37247485011598e-16
Q30.409129444293412
maximum2.3546257831463


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')