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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, 04 Nov 2009 03:21:13 -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/04/t1257330156m5c3zeofo6ypjlx.htm/, Retrieved Mon, 29 Apr 2024 15:54:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53507, Retrieved Mon, 29 Apr 2024 15:54:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordscvm
Estimated Impact170

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] [W5: Bivariate EDA...] [2009-11-04 10:21:13] [a5ada8bd39e806b5b90f09589c89554a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6,39170155
4,14280265
1,85518345
0,9440078
-0,2987007
-0,47934055
0,22863585
0,1541864
-0,87734645
0,27333845
0,84342695
2,60229635
4,2090676
2,93881445
2,2050794
1,20827865
-0,0947125
-0,23862615
0,32024325
-1,23862615
-0,79392355
-0,3623907
0,7565967
2,84301075
3,8559724
2,41205875
0,58152295
-1,519266
-1,352004
-1,61627485
-0,1767656
-0,04282245
-0,44901285
-0,5236704
-0,09151325
0,3827281
-0,25520325
-0,3462298
-2,28175085
-3,402897
-2,12047115
-2,5276586
-4,3031051
-4,61448885
-6,26737595
-3,74303055
1,229841
3,1787399
3,2396034
0,43860635
-3,9579863
-3,72624535
-1,5292365
0,0727576
1,28173105
-0,44460845
-2,1557841
-0,65499515
1,3995133
2,49631405
Dataseries Y:
Download CSV
Histogram 
-302,8565274
-296,2381342
-283,8545246
-280,1276024
-267,9674044
-270,2000126
-285,6899758
-281,7807792
-273,7475034
-302,1976646
-242,5853026
-269,1411498
-300,3416448
-287,1431526
-293,1466632
-281,3836222
-274,962386
-278,0127198
-304,568567
-278,6127198
-294,7204086
-302,9536844
-250,8597156
-278,053857
-303,8125472
-307,262881
-301,0033506
-281,145328
-288,222584
-287,3665642
-311,4898032
-288,7020154
-294,4438202
-309,1189008
-264,799345
-285,7928188
-300,785625
-318,3493336
-301,2210762
-276,6567
-295,6558598
-299,0239192
-293,5409772
-306,1983322
-291,7849574
-302,9862926
-266,579444
-273,2978372
-304,3011752
-302,2274298
-273,6801116
-266,1291102
-260,707874
-265,2553648
-283,2190734
-268,3702474
-264,1433252
-284,6013478
-249,3356364
-261,6986774

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'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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53507&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53507&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53507&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'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c-285.234256807020
b-0.105294166911745

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -285.234256807020 \tabularnewline
b & -0.105294166911745 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53507&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-285.234256807020[/C][/ROW]
[ROW][C]b[/C][C]-0.105294166911745[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53507&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53507&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-285.234256807020
b-0.105294166911745






Descriptive Statistics about e[t]
# observations60
minimum-33.1515327713315
Q1-15.6106454095418
median-0.474953964082863
mean3.22427270068223e-16
Q311.6135610517602
maximum42.7377621450708

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -33.1515327713315 \tabularnewline
Q1 & -15.6106454095418 \tabularnewline
median & -0.474953964082863 \tabularnewline
mean & 3.22427270068223e-16 \tabularnewline
Q3 & 11.6135610517602 \tabularnewline
maximum & 42.7377621450708 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53507&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]-33.1515327713315[/C][/ROW]
[ROW][C]Q1[/C][C]-15.6106454095418[/C][/ROW]
[ROW][C]median[/C][C]-0.474953964082863[/C][/ROW]
[ROW][C]mean[/C][C]3.22427270068223e-16[/C][/ROW]
[ROW][C]Q3[/C][C]11.6135610517602[/C][/ROW]
[ROW][C]maximum[/C][C]42.7377621450708[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53507&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53507&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-33.1515327713315
Q1-15.6106454095418
median-0.474953964082863
mean3.22427270068223e-16
Q311.6135610517602
maximum42.7377621450708


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')