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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 07:25:25 -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/t1257344814ttvxvrh3h17u682.htm/, Retrieved Mon, 29 Apr 2024 09:18:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53594, Retrieved Mon, 29 Apr 2024 09:18:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsbhschhwstws5prt1
Estimated Impact123
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [Workshop 5] [2009-11-04 14:25:25] [682632737e024f9e62885141c5f654cd] [Current]
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Dataseries X:
-10.07769062
-10.22784057
-10.4179572
-10.41801384
-10.82816379
-11.21831374
-11.38837705
-11.72847701
-11.86855365
-12.51880023
-12.50879023
-12.66884022
-12.78887687
-13.02890019
-13.02887354
-12.94886354
-15.22958662
-15.3796266
-15.4996366
-15.61969658
-15.86974989
-15.94981653
-16.05984319
-16.04987651
-16.1299165
-16.15993316
-16.19996648
-16.18996981
-16.09995982
-16.08000647
-16.29003646
-16.35006311
-16.41012309
-16.34016308
-16.20016974
-16.1502064
-15.97025638
-16.97073288
-17.68110274
-17.5411394
-17.44118938
-17.10127602
-16.16134932
-15.40140597
-13.43143929
-12.70149927
-12.25155258
-12.55169587
-12.73178584
-13.57205241
-16.28299207
-16.21308204
-15.82316868
-15.49322532
-14.85325198
-13.85326864
-13.64326531
-13.80328197
-14.09327864
-14.28327864
Dataseries Y:
26.18358961
22.86693241
16.83731015
23.17035076
22.23369356
24.86703636
25.33866998
26.22756518
31.04638484
28.05432633
30.67143681
33.06588441
33.85314598
22.92322153
24.99884947
27.45595995
23.5683019
25.35985998
27.8027495
30.77008662
27.89883072
27.99476086
28.04913291
25.68209798
32.84365606
31.61513859
26.60810365
25.94240016
22.82951064
23.95966173
25.29833029
26.18270235
24.18003947
26.19159755
26.62019056
32.88745213
36.97189973
34.66630018
33.82321242
32.640474
29.2949216
33.37663077
36.20115391
35.77419453
35.20715959
36.88449671
35.82324082
32.00799061
36.60399629
36.93771682
32.09933169
29.98533737
23.28704655
26.86008716
29.35445921
26.99594174
24.71164524
25.94312777
25.66883126
30.22883126




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 8 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53594&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53594&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53594&T=0

As an alternative you can also use a 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 time8 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c21.4216345140074
b-0.504888129126506

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 21.4216345140074 \tabularnewline
b & -0.504888129126506 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53594&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]21.4216345140074[/C][/ROW]
[ROW][C]b[/C][C]-0.504888129126506[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53594&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53594&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c21.4216345140074
b-0.504888129126506







Descriptive Statistics about e[t]
# observations60
minimum-9.84422728403543
Q1-3.49821752176148
median-1.26784090451673
mean3.91324704122435e-17
Q33.31401884141195
maximum9.0500259924606

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -9.84422728403543 \tabularnewline
Q1 & -3.49821752176148 \tabularnewline
median & -1.26784090451673 \tabularnewline
mean & 3.91324704122435e-17 \tabularnewline
Q3 & 3.31401884141195 \tabularnewline
maximum & 9.0500259924606 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53594&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]-9.84422728403543[/C][/ROW]
[ROW][C]Q1[/C][C]-3.49821752176148[/C][/ROW]
[ROW][C]median[/C][C]-1.26784090451673[/C][/ROW]
[ROW][C]mean[/C][C]3.91324704122435e-17[/C][/ROW]
[ROW][C]Q3[/C][C]3.31401884141195[/C][/ROW]
[ROW][C]maximum[/C][C]9.0500259924606[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53594&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53594&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations60
minimum-9.84422728403543
Q1-3.49821752176148
median-1.26784090451673
mean3.91324704122435e-17
Q33.31401884141195
maximum9.0500259924606



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')