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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 13:49:44 -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/t1257108781moi3o2h9jjdcw06.htm/, Retrieved Mon, 06 May 2024 17:38:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52407, Retrieved Mon, 06 May 2024 17:38:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact213

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] [WS 4 module 2] [2009-10-26 21:23:44] [830e13ac5e5ac1e5b21c6af0c149b21d]
- RMPD  [Partial Correlation] [WS 5 ] [2009-10-30 20:36:39] [023d83ebdf42a2acf423907b4076e8a1]
- RMPD      [Bivariate Explorative Data Analysis] [WS 5 Residus biva] [2009-11-01 20:49:44] [51118f1042b56b16d340924f16263174] [Current]
- RMP         [Pearson Correlation] [SHWWS5Review4] [2009-11-06 10:37:05] [a66d3a79ef9e5308cd94a469bc5ca464]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-43,46299021
-80,75309516
-70,74336158
38,9668564
103,8074054
-154,6120618
80,77812389
-8,071755014
98,25849525
-30,58100421
-44,78092348
40,3791734
-132,19098
-76,88100421
-106,2410204
-60,55099614
-2,200632843
-67,52066514
-28,0902534
-21,31993855
204,9200453
-150,9996641
90,49044089
3,190198694
-95,23997084
-53,65976094
-80,03964792
206,0103925
95,62085262
70,15086069
-4,308751793
-9,298856744
138,9711352
77,72149848
281,4313935
108,1314743
118,3119264
-143,9872663
73,21297587
215,4333311
67,37396079
-107,8253934
-100,1751915
-279,1043923
25,05610826
71,32658458
126,5560275
225,3961728
229,2960114
-32,31452952
256,6652767
74,69536553
8,935672307
161,5151556
-242,1946587
-173,2347233
-53,46489282
-290,1749493
-360,6546748
-187,924909
Dataseries Y:
Download CSV
Histogram 
0,002022723
-0,017208098
-0,051656261
-0,072675401
-0,04888664
-0,035594314
-0,043990322
-0,026968066
-0,008756337
0,032209121
0,042033292
0,026096897
0,026430772
0,042472121
0,058426687
0,053742338
0,041398106
0,052385238
0,052190308
0,039393774
0,00733234
0,018657154
0,017944976
0,006882464
0,009761905
0,019803549
0,004696588
-0,014269327
0,004359046
5,42631E-05
-0,004455318
-0,02117114
-0,021005357
-0,011061589
-0,028604411
-0,02249124
-0,030906084
-0,036827378
-0,055456866
-0,045366315
-0,043827384
-0,036552019
-0,067865593
-0,066311103
-0,051684645
-0,045133838
-0,061448816
-0,025835909
0,00011375
0,047607207
0,079794997
0,039112385
0,055018633
0,074915741
0,061521734
0,052521997
0,024700439
0,004811919
0,0048453
-0,007247995

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=52407&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=52407&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52407&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-3.17044717017007e-11
b-3.60050819519983e-05

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -3.17044717017007e-11 \tabularnewline
b & -3.60050819519983e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52407&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-3.17044717017007e-11[/C][/ROW]
[ROW][C]b[/C][C]-3.60050819519983e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52407&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52407&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-3.17044717017007e-11
b-3.60050819519983e-05






Descriptive Statistics about e[t]
# observations60
minimum-0.0763602794862197
Q1-0.0298464226835153
median-0.0020763102111994
mean-2.40399244203400e-18
Q30.0329875740759618
maximum0.0890362513535203

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.0763602794862197 \tabularnewline
Q1 & -0.0298464226835153 \tabularnewline
median & -0.0020763102111994 \tabularnewline
mean & -2.40399244203400e-18 \tabularnewline
Q3 & 0.0329875740759618 \tabularnewline
maximum & 0.0890362513535203 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52407&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]-0.0763602794862197[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0298464226835153[/C][/ROW]
[ROW][C]median[/C][C]-0.0020763102111994[/C][/ROW]
[ROW][C]mean[/C][C]-2.40399244203400e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0329875740759618[/C][/ROW]
[ROW][C]maximum[/C][C]0.0890362513535203[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52407&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52407&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-0.0763602794862197
Q1-0.0298464226835153
median-0.0020763102111994
mean-2.40399244203400e-18
Q30.0329875740759618
maximum0.0890362513535203


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')