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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 computationSun, 08 Nov 2009 09:25:45 -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/08/t12576975905jmyycmdcaxyf38.htm/, Retrieved Sat, 04 May 2024 19:00:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54603, Retrieved Sat, 04 May 2024 19:00:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197

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] [3/11/2009] [2009-11-02 22:01:32] [b98453cac15ba1066b407e146608df68]
-    D    [Bivariate Explorative Data Analysis] [Regressierechte] [2009-11-08 16:25:45] [2622964eb3e61db9b0dfd11950e3a18c] [Current]
-   PD      [Bivariate Explorative Data Analysis] [Regressierechte] [2009-12-13 19:32:48] [e2a6b1b31bd881219e1879835b4c60d0]
-    D        [Bivariate Explorative Data Analysis] [Regressierechte] [2009-12-13 19:42:44] [e2a6b1b31bd881219e1879835b4c60d0]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
433
344
357
385
392
308
294
302
400
392
373
379
303
324
353
392
327
376
329
359
413
338
422
390
370
367
406
418
346
350
329
318
381
337
372
422
427
426
396
458
314
336
385
351
381
438
397
451
362
363
468
371
407
391
364
366
424
364
366
423
Dataseries Y:
Download CSV
Histogram 
34.97
34.97
34.93
34.92
34.97
34.97
34.97
35.38
35.64
35.9
36.01
36.03
36.04
36.06
36.09
36.15
36.15
36.15
36.1
36.38
36.89
37
37.09
37.13
37.24
37.29
37.34
37.49
37.49
37.54
37.67
38.13
38.68
38.77
39
39.03
39.03
39.04
39.16
39.23
39.26
39.25
39.41
39.56
39.69
39.87
39.83
39.84
39.85
39.91
40.62
40.73
40.86
40.89
40.9
41.15
41.24
41.24
41.33
41.36

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=54603&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=54603&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54603&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]
c31.3075803286905
b0.0178142556714856

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 31.3075803286905 \tabularnewline
b & 0.0178142556714856 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54603&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]31.3075803286905[/C][/ROW]
[ROW][C]b[/C][C]0.0178142556714856[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54603&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54603&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]
c31.3075803286905
b0.0178142556714856






Descriptive Statistics about e[t]
# observations60
minimum-4.05115303444378
Q1-1.52325230957049
median0.00805869763252206
mean1.27386527252564e-16
Q31.49305869763252
maximum3.50240209554578

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -4.05115303444378 \tabularnewline
Q1 & -1.52325230957049 \tabularnewline
median & 0.00805869763252206 \tabularnewline
mean & 1.27386527252564e-16 \tabularnewline
Q3 & 1.49305869763252 \tabularnewline
maximum & 3.50240209554578 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54603&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]-4.05115303444378[/C][/ROW]
[ROW][C]Q1[/C][C]-1.52325230957049[/C][/ROW]
[ROW][C]median[/C][C]0.00805869763252206[/C][/ROW]
[ROW][C]mean[/C][C]1.27386527252564e-16[/C][/ROW]
[ROW][C]Q3[/C][C]1.49305869763252[/C][/ROW]
[ROW][C]maximum[/C][C]3.50240209554578[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54603&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54603&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-4.05115303444378
Q1-1.52325230957049
median0.00805869763252206
mean1.27386527252564e-16
Q31.49305869763252
maximum3.50240209554578


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')