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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 computationMon, 09 Nov 2009 10:33:35 -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/09/t1257788056vi3camtbz08hkg4.htm/, Retrieved Fri, 29 Mar 2024 08:57:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54878, Retrieved Fri, 29 Mar 2024 08:57:26 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [workshop 6] [2009-11-09 17:33:35] [e81f30a5c3daacfe71a556c99a478849] [Current]
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Dataseries X:
0.120752452
0.105369762
0.559667132
0.617676236
0.620890174
0.488599698
0.402549931
-0.095793222
0.153556719
-0.00498901
0.069687925
0.237787193
0.681841701
0.620458256
0.784496766
0.765152642
0.53850517
0.232805449
0.443993156
1.059132549
0.684342181
0.591495739
0.405390277
0.583327688
0.31157195
0.395478121
0.202182743
0.300727018
0.455943488
0.643531286
0.591181184
0.327542165
0.341576746
-0.007494997
-0.133753157
-0.262777342
-0.24677077
-0.309592055
-0.396739797
-0.41720996
-0.734757037
-0.847271472
-0.922777775
-0.831189711
-0.907288335
-0.897944799
-0.644550531
-0.642097609
-0.128500176
-0.203568743
-0.049918523
-0.036844194
-0.173592444
-0.271557919
-0.158049785
-0.151899673
-0.101133272
0.395358593
0.303572316
0.47720363
0.273522005
-0.040706427
-0.552401086
-0.752792285
-0.418527341
-0.244474721
-0.068492716
-0.125391345
-0.357572751
-0.676559124
-0.563395652
-0.819421562
-1.541530688
-1.198739354
-0.886889366
-0.370127872
-0.008973614
-0.251839827
-0.777337249
-1.390870261
-1.047696764
-1.028501564
-1.275952072
-1.246978199
-0.869001956
-0.849706844
-0.617587106
-0.678722891
-1.024199243
-1.125463004
-1.22601374
-0.971781378
-0.673034372
-0.589506466
-0.323202046
0.081119026
-0.095091299
0.031922928
0.336710821
0.133430574
0.250632556
0.845533449
0.90233755
1.011292518
1.475292629
1.087161367
1.226576317
0.602429169
0.308627705
0.359856564
0.176243567
0.878538406
1.220666437
1.018000326
0.74814532
0.764889207
0.312975664
0.408389915
0.191030871
0.237936183
0.969820485
0.703547781
0.742067333
-0.106880207
-0.588664598
-1.074170623
-0.710571025
-0.743663826
-0.765352823
-0.753577746
-0.928815442
-0.665596707
-0.832658647
-0.328967863
-0.327967912
-0.579148625
-1.007949285
-0.420788455
-0.549344363
-0.235992702
-0.221328855
-0.437344153
-0.149537626
-0.266314962
-0.393959909
-0.710899102
-0.845496052
-0.046163995
0.634352704
0.291190686
0.44023523
0.297476045
0.088970169
0.935130028
0.638583488
0.369078962
0.367864213
0.69222223
1.19595098
0.887854621
0.629412578
0.994655225
1.274017821
1.257901746
1.310788474
0.623451244
0.733437722
1.072369422
0.837507949
0.608744668
-0.06600003
0.200735132
0.416999542
0.063414609
-0.187463182
-0.134098865
-0.528417462
-0.51392463
-0.225020129
-0.061765904
Dataseries Y:
-1,85995713
-1,950522648
-2,041741893
-2,145809864
-2,239242869
-2,243922967
-1,756284368
-1,273331809
-1,174660066
-1,171688575
-1,162132261
-0,966016
-0,757731484
-0,740125402
-0,731873573
-0,83053343
-0,844116114
-0,735329416
-0,212469739
0,498031509
0,688243419
0,802860181
0,810817833
0,927036228
1,043881608
1,051863032
0,945129634
0,842155172
0,752813909
0,627452237
0,922650308
1,535647608
1,523458554
1,404922395
1,212568041
1,114561911
1,106402198
1,000637506
0,78603263
0,605504807
0,430949681
0,325811974
0,83499388
1,338238748
1,566643226
1,424436174
1,331371633
1,256816507
1,384599944
1,294676269
1,10213471
0,908416441
0,615060694
0,419217809
0,705953075
1,218519509
1,220085485
1,033350219
0,850133198
0,75755301
0,690896105
0,723121921
0,540092104
0,339292773
0,268440124
0,297153638
0,750242288
1,315713568
1,411256332
1,213327461
0,999358484
1,027911537
1,144034845
1,090604045
1,055682661
1,01036403
0,833155363
0,788597435
1,159096049
1,711011388
1,735764332
1,393254188
1,05976209
0,998531128
1,035261723
0,913388581
0,776854104
0,57453337
0,342910767
0,140328542
0,318770377
0,506985446
0,245290931
-0,108799112
-0,334618821
-0,446222492
-0,699777667
-1,067177017
-1,477826839
-1,543663611
-1,849380759
-1,939366836
-1,405031262
-0,866300854
-1,098993193
-1,195174828
-1,375937398
-1,604844058
-1,912611535
-2,110100625
-2,158348718
-1,953659706
-1,969744384
-2,254759157
-2,034030039
-1,840683206
-1,526324537
-0,815261677
-0,80986545
-0,716188782
-0,691905761
-0,884289831
-0,987314808
-1,16473148
-1,368377499
-1,540926442
-0,915302851
-0,842055181
-0,686371992
-0,523610712
-0,393447111
-0,307303171
-0,22173273
-0,375489966
-0,61431249
-0,655426461
-0,932543012
-0,917911393
-0,214960702
-0,087679447
-0,078149877
-0,070007993
-0,054057031
0,152527792
0,498205545
0,424892502
-0,08450038
-0,865432324
-1,184809415
-0,970837466
0,427210265
0,942005317
0,985923947
0,418943151
-0,05356759
0,067877658
0,285828433
0,415165959
0,322784861
0,026674542
-0,090574961
-0,279862737
0,439267719
0,56763654
0,573534949
0,378975748
0,299380974
0,438063839
0,689429025
0,732821702
0,663992638
0,557321642
0,329255913
-0,03936769
0,199704439
0,147444407
0,17948599
0,129531835
0,047726272
0,074808437




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=54878&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=54878&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54878&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c7.81089959040418e-12
b-0.594026280696515

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 7.81089959040418e-12 \tabularnewline
b & -0.594026280696515 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54878&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]7.81089959040418e-12[/C][/ROW]
[ROW][C]b[/C][C]-0.594026280696515[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54878&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54878&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]
c7.81089959040418e-12
b-0.594026280696515







Descriptive Statistics about e[t]
# observations180
minimum-2.17901202202196
Q1-0.706102292776905
median0.0780662695959053
mean1.29269707369762e-16
Q30.858879936351693
maximum1.73021626203842

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 180 \tabularnewline
minimum & -2.17901202202196 \tabularnewline
Q1 & -0.706102292776905 \tabularnewline
median & 0.0780662695959053 \tabularnewline
mean & 1.29269707369762e-16 \tabularnewline
Q3 & 0.858879936351693 \tabularnewline
maximum & 1.73021626203842 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54878&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]180[/C][/ROW]
[ROW][C]minimum[/C][C]-2.17901202202196[/C][/ROW]
[ROW][C]Q1[/C][C]-0.706102292776905[/C][/ROW]
[ROW][C]median[/C][C]0.0780662695959053[/C][/ROW]
[ROW][C]mean[/C][C]1.29269707369762e-16[/C][/ROW]
[ROW][C]Q3[/C][C]0.858879936351693[/C][/ROW]
[ROW][C]maximum[/C][C]1.73021626203842[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54878&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54878&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]
# observations180
minimum-2.17901202202196
Q1-0.706102292776905
median0.0780662695959053
mean1.29269707369762e-16
Q30.858879936351693
maximum1.73021626203842



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')