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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, 22 Nov 2009 01:33:39 -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/22/t12588789210q2be4xp68eyvft.htm/, Retrieved Sat, 27 Apr 2024 18:20:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58600, Retrieved Sat, 27 Apr 2024 18:20:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162

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] [SHW_WS4_Q2(2)] [2009-10-23 08:55:58] [8b1aef4e7013bd33fbc2a5833375c5f5]
-  M D    [Bivariate Explorative Data Analysis] [paper] [2009-11-22 08:33:39] [f0f26816ac6124f58333f11f6c174000] [Current]
- RM D      [Univariate Explorative Data Analysis] [paper] [2009-11-22 09:17:04] [8b1aef4e7013bd33fbc2a5833375c5f5]
- R  D        [Univariate Explorative Data Analysis] [model_3et] [2009-12-29 10:04:25] [2663058f2a5dda519058ac6b2228468f]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-22.55812594
-21.35812594
-19.86358022
-17.3690345
-16.47448878
-16.07448878
-17.86358022
-20.74176309
-21.83085453
-21.33085453
-20.83085453
-21.32540024
-21.41994596
-20.61994596
-18.72540024
-18.12540024
-17.92540024
-17.03085453
-20.1090374
-23.18722027
-22.98176599
-23.0763117
-22.9763117
-24.46540314
-25.95449458
-25.94904029
-25.64904029
-23.75449458
-23.25449458
-23.44904029
-26.32722316
-30.79449747
-32.97813462
-32.57813462
-33.27268034
-33.96722606
-35.4563175
-34.8563175
-33.56177178
-31.76722606
-30.97268034
-29.28358891
-31.66722606
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-33.84540893
-32.35086321
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0.767322553
0.767322553
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13.98550832
10.01277973
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10.2236883
11.21823401
12.31277973
12.41277973
13.31277973
13.01823401
11.93459686
13.62914258
16.71277973
15.7236883
14.13459686
11.45641399
6.789139682
7.7836854
7.9836854
10.66732255
11.76186827
12.36186827
12.36732255
13.56186827
16.14550542
14.46186827
14.66186827
12.77823112
5.727319657
3.743682504
3.049136786
4.443682504
6.132773939
7.027319657
6.332773939
7.927319657
10.11641109
8.032773939
9.127319657
8.532773939
6.349136786
6.849136786
5.76004535
5.265499632
7.154591068
11.42731966
17.48913968
20.07277684
20.17823112
12.73277394
10.05459107
9.56004535
13.03822822
15.02731966
14.43277394
13.3436825
13.6436825
14.0436825
17.52731966
18.02731966
21.30550253
18.92731966
19.12731966
18.53277394
18.03822822
18.43822822
17.04913679
15.76004535
15.56549963
16.66549963
17.06549963
19.84913679
25.01641109
28.39459396
31.27823112
30.7836854
29.69459396
29.20004825
28.70550253
28.01095681
29.10550253
30.89459396
30.20004825
31.98913968
35.46732255
33.3836854
34.27823112
36.06732255
37.46186827
38.45641399
36.77277684
34.58913968
35.68913968
40.96732255
44.25095971
47.53459686
45.35095971
37.01095681
36.91641109
40.79459396
47.35095971
50.63459686
47.65641399
40.80550253
36.23822822
35.04913679
36.93822822
40.12186538
40.02731966
36.35459107
36.26004535
Dataseries Y:
Download CSV
Histogram 
0.635439214
0.735439214
0.003836396
-0.447766422
-0.14936924
0.25063076
0.533836396
0.420247668
-0.506546695
-0.816546695
-0.186546695
-0.214943877
-0.673341059
-0.693341059
-0.284943877
-0.224943877
-0.224943877
-0.396546695
-0.310135423
-0.63372415
-0.342121332
-0.460518514
-0.390518514
-0.137312877
0.385892759
0.357495577
0.517495577
0.455892759
0.235892759
-0.032504423
0.33390685
1.193523758
0.948332213
0.848332213
0.699935031
0.911537849
0.714743485
0.794743485
0.563140667
0.621537849
0.729935031
0.846729395
0.921537849
0.817949122
0.837949122
0.456346304
0.284743485
0.113140667
0.174743485
0.073140667
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0.296346304
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0.168332213
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0.089935031
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0.588332213
0.446729395
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0.396729395
0.025126577
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0.061537849
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-0.293270605
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0.196346304
0.15955194
0.051154758
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0.36390685
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0.621537849
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0.44955194
1.113140667
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0.554743485
0.864743485
1.364743485
0.929935031
0.679935031
0.873523758
1.309935031
1.279935031
1.371537849
0.723140667
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1.226346304
1.04955194
0.841154758
0.151154758
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0.526346304
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-0.25807906
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-0.997695969
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-1.084490332
-0.777695969
-0.089298787
0.569098395
0.84390685
1.338715304
1.518715304
2.102304031
1.737495577
2.672687123
3.387495577
3.955126577
3.476729395
3.380318122
2.307495577
0.602687123
0.259098395
0.323523758
0.183140667
-1.043653696
-1.146859333
-2.241667787
-2.930064969
-3.302050878
-2.36044806

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58600&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]7 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=58600&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58600&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 time7 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c-1.30109935821623e-11
b0.00475138357661247

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -1.30109935821623e-11 \tabularnewline
b & 0.00475138357661247 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58600&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-1.30109935821623e-11[/C][/ROW]
[ROW][C]b[/C][C]0.00475138357661247[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58600&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58600&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]
c-1.30109935821623e-11
b0.00475138357661247






Descriptive Statistics about e[t]
# observations224
minimum-3.47478548493145
Q1-0.526779044866043
median-0.0704817067633388
mean5.50058355758673e-17
Q30.496048257234306
maximum3.77927332467126

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 224 \tabularnewline
minimum & -3.47478548493145 \tabularnewline
Q1 & -0.526779044866043 \tabularnewline
median & -0.0704817067633388 \tabularnewline
mean & 5.50058355758673e-17 \tabularnewline
Q3 & 0.496048257234306 \tabularnewline
maximum & 3.77927332467126 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58600&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]224[/C][/ROW]
[ROW][C]minimum[/C][C]-3.47478548493145[/C][/ROW]
[ROW][C]Q1[/C][C]-0.526779044866043[/C][/ROW]
[ROW][C]median[/C][C]-0.0704817067633388[/C][/ROW]
[ROW][C]mean[/C][C]5.50058355758673e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.496048257234306[/C][/ROW]
[ROW][C]maximum[/C][C]3.77927332467126[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58600&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58600&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]
# observations224
minimum-3.47478548493145
Q1-0.526779044866043
median-0.0704817067633388
mean5.50058355758673e-17
Q30.496048257234306
maximum3.77927332467126


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')