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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, 01 Nov 2009 11:21:52 -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/01/t1257099880x9c2poolocm4w9i.htm/, Retrieved Mon, 06 May 2024 21:18:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52383, Retrieved Mon, 06 May 2024 21:18:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact220

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_WS5_volledigm...] [2009-10-29 19:10:17] [8b1aef4e7013bd33fbc2a5833375c5f5]
-  MPD    [Bivariate Explorative Data Analysis] [ws 5] [2009-11-01 18:21:52] [f7d3e79b917995ba1c8c80042fc22ef9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-8.420276058
5.603810549
7.227897157
-0.439987367
-8.023929628
-10.08378528
-10.65969868
-2.827583199
-3.339265638
-2.699121292
5.708907577
-19.42686147
-11.31080373
5.505254006
2.529340614
3.06145609
-4.822486171
-5.698399564
-5.450226349
7.438091212
0.070206688
5.602322165
8.934437641
-17.34950462
-6.409360275
9.214726333
12.15487068
5.578957286
1.503043893
-0.488927238
-0.46484063
12.15121711
4.459245977
6.675303715
11.79939032
-12.67652307
-2.168494201
10.64756354
14.39573675
8.711794491
-0.832003425
4.284054313
7.172371874
9.140978126
10.51323795
9.58549777
13.30155551
-10.16632902
-1.210126931
10.14607515
8.762132891
-0.865607287
-10.54954955
-12.32546294
-11.6094052
-0.077289726
-10.75320312
-6.588972166
-1.932770082
-22.20868347
Dataseries Y:
Download CSV
Histogram 
0.650033625
0.669304839
0.088576053
-0.385728995
-0.272881519
-0.04076283
0.078508384
0.004203336
-0.225135547
-0.293016857
-0.486593119
0.264796785
0.37764426
0.390491736
0.20976295
0.135457902
0.248305378
0.467576592
0.506119019
0.476780137
0.402475088
0.22817004
-0.046135008
0.166712468
0.098831158
0.118102371
0.050221061
-0.030507725
-0.011236511
0.095187227
0.114458441
0.027305917
0.133729654
-0.15342287
-0.634151656
-0.314880442
-0.508456704
-0.795609228
-0.7570668
-0.744219325
-0.499253159
-0.386405683
-0.515744566
-0.680846069
-1.023032427
-1.265218786
-0.85237131
0.373323642
0.618289807
0.263255973
-0.323896551
-0.56608291
-0.253235434
0.56603578
0.878883256
0.904578208
0.623849422
0.275239325
0.420205491
1.139476705

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=52383&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=52383&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52383&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]
c-1.61757329871507e-11
b-0.0294525288278295

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -1.61757329871507e-11 \tabularnewline
b & -0.0294525288278295 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52383&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-1.61757329871507e-11[/C][/ROW]
[ROW][C]b[/C][C]-0.0294525288278295[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52383&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52383&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-1.61757329871507e-11
b-0.0294525288278295






Descriptive Statistics about e[t]
# observations60
minimum-0.982901636583804
Q1-0.339385434215734
median0.059206015286928
mean-2.11500738797610e-17
Q30.350017183880169
maximum0.902301830133066

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.982901636583804 \tabularnewline
Q1 & -0.339385434215734 \tabularnewline
median & 0.059206015286928 \tabularnewline
mean & -2.11500738797610e-17 \tabularnewline
Q3 & 0.350017183880169 \tabularnewline
maximum & 0.902301830133066 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52383&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]-0.982901636583804[/C][/ROW]
[ROW][C]Q1[/C][C]-0.339385434215734[/C][/ROW]
[ROW][C]median[/C][C]0.059206015286928[/C][/ROW]
[ROW][C]mean[/C][C]-2.11500738797610e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.350017183880169[/C][/ROW]
[ROW][C]maximum[/C][C]0.902301830133066[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52383&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52383&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-0.982901636583804
Q1-0.339385434215734
median0.059206015286928
mean-2.11500738797610e-17
Q30.350017183880169
maximum0.902301830133066


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')