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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 computationSun, 25 Oct 2009 07:01:07 -0600
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/Oct/25/t1256475702wzi6c7qdqx0uu1t.htm/, Retrieved Mon, 29 Apr 2024 11:21:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50308, Retrieved Mon, 29 Apr 2024 11:21:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact206
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [SHW_WS4_Q2(2)] [2009-10-23 08:55:58] [8b1aef4e7013bd33fbc2a5833375c5f5]
-         [Bivariate Explorative Data Analysis] [] [2009-10-25 13:01:07] [2a6f24d4847085573f343c759dfbabef] [Current]
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Dataseries X:
5.032396786
5.040194096
5.044714608
5.05560866
5.056245805
5.058790336
5.05751888
5.059425458
5.062595033
5.065754593
5.068904202
5.070789217
5.075173815
5.080161357
5.086978861
5.090678002
5.091908014
5.092522454
5.093136516
5.093750201
5.099866428
5.104125637
5.104732617
5.10533923
5.105945474
5.110782243
5.112590017
5.119190701
5.122176669
5.125748101
5.127529046
5.129306824
5.130490256
5.132852927
5.133442723
5.134032172
5.134621274
5.138148614
5.14107859
5.146912912
5.146912912
5.147494477
5.147494477
5.149817358
5.153291594
5.157329673
5.157905213
5.157905213
5.158480421
5.162497643
5.164785974
5.169915652
5.170483995
5.165357239
5.168208681
5.169915652
5.174453379
5.171052016
5.171052016
5.171619714
5.172187089
5.180659323
5.184588601
5.18961795
5.190175208
5.190732156
5.191288794
5.191288794
5.191845122
5.192401141
5.194067345
5.195176608
5.195176608
5.200153118
5.203457086
5.206750173
5.207845463
5.210032452
5.212759478
5.213303992
5.21384821
5.214392132
5.215479088
5.217107311
5.217649463
5.225208895
5.228967288
5.234312037
5.235377567
5.235909906
5.236441963
5.238036436
5.238567362
5.239098007
5.239098007
5.23962837
5.23962837
5.243861181
5.247024072
5.256974403
5.260096154
5.262690189
5.265277512
5.267342562
5.268888556
5.272486607
5.272486607
5.272486607
5.272486607
5.275560379
5.278114659
5.279134547
5.279134547
5.279134547
5.279134547
5.283203729
5.28675073
5.288267031
5.289276622
5.2907891
5.291292752
5.295814236
5.298317367
5.304796333
5.309257307
5.312713247
5.315666005
5.315666005
5.318119994
5.31861007
5.319589502
5.320567975
5.322033893
5.323497665
5.326418797
5.330300412
5.332235585
5.333201768
5.336576079
5.33753808
5.339939041
5.340418543
5.342334252
5.342812606
5.345677938
5.346154696
5.346631227
5.347107531
5.350909817
5.353752073
5.355170178
5.356586275
5.357529226
5.358471289
5.360822572
5.363168339
5.364573162
5.365976015
5.367376902
5.369707363
5.370638028
5.374815338
5.377128547
5.379436418
5.380818588
5.382198851
5.384036242
5.384953673
5.387243576
5.388615005
5.390440655
5.395444077
5.39771011
5.398162702
5.401776075
5.402677382
5.403577877
5.404927102
5.40672324
5.407620101
5.408963887
5.411646052
5.416544748
5.418320159
5.420092423
5.421861553
5.422744945
5.424950017
5.426270731
5.428468051
5.429784129
5.431098478
5.43153621
5.43284826
5.433722004
5.434158589
5.43503119
5.436338664
5.437644432
5.438079309
5.438948496
5.441551535
5.442417711
5.445443431
5.446306244
5.451038454
5.460010956
5.463831805
5.467638111
5.468481993
5.470167623
5.473110657
5.476045054
5.476881874
5.480638923
5.48147191
5.48272009
5.483551345
5.485211785
5.486455309
Dataseries Y:
1.355835154
1.381281819
1.190887565
1.057790294
1.16938136
1.286474026
1.340250423
1.264126727
0.928219303
0.797507196
1.047318994
1.022450928
0.824175443
0.815364813
0.996948635
1.01884732
1.01884732
0.970778917
0.940007258
0.727548607
0.841567186
0.770108222
0.802001585
0.875468737
1.043804052
1.01884732
1.075002423
1.068153081
0.989541194
0.867100488
0.947789399
1.160020917
1.036736885
1.00063188
0.928219303
0.993251773
0.88376754
0.916290732
0.837247525
0.879626748
0.940007258
1.01523068
0.996948635
0.891998039
0.90016135
0.751416089
0.688134639
0.620576488
0.631271777
0.598836501
0.553885113
0.536493371
0.322083499
0.2390169
0.173953307
0.246860078
0.173953307
0.198850859
0.385262401
0.378436436
0.672944473
0.631271777
0.708035793
0.712949808
0.641853886
0.587786665
0.652325186
0.652325186
0.678033543
0.90016135
0.858661619
0.928219303
0.837247525
0.683096845
0.378436436
0.231111721
0.457424847
0.553885113
0.636576829
0.615185639
0.482426149
0.262364264
0.350656872
0.139761942
-0.867500568
-0.301105093
0.019802627
0.412109651
0.620576488
0.463734016
0.029558802
-0.820980552
-0.198450939
-0.15082289
-0.544727175
-0.527632742
-0.051293294
-0.020202707
0.207014169
0.157003749
-0.174353387
-0.301105093
-0.430782916
-0.094310679
0.173953307
0.262364264
0.425267735
0.662687973
0.58221562
0.667829373
0.815364813
0.712949808
0.770108222
1.011600912
1.026041596
1.057790294
1.211940974
1.088561953
1.131402111
0.91228271
0.78845736
0.810930216
0.737164066
1.026041596
1.1442228
1.075002423
0.97455964
0.982078472
0.815364813
0.854415328
0.75612198
0.779324877
1.064710737
0.966983846
0.982078472
0.593326845
0.285178942
-0.127833372
0.246860078
0.231111721
0.231111721
0.254642218
0.09531018
0.31481074
0.19062036
0.553885113
0.565313809
0.392042088
0.039220713
0.482426149
0.39877612
0.58221562
0.587786665
0.457424847
0.620576488
0.553885113
0.463734016
0.231111721
0.122217633
0.652325186
0.959350221
0.815364813
0.879626748
0.815364813
0.708035793
1.050821625
0.936093359
0.819779831
0.815364813
0.943905899
1.121677562
1.01523068
0.920282753
1.05431203
1.1442228
1.134622726
1.150572028
0.904218151
0.943905899
1.061256502
0.966983846
0.867100488
0.524728529
0.672944473
0.783901544
0.625938431
0.470003629
0.488580015
0.198850859
0.19062036
0.39877612
0.494696242
0.506817602
0.570979547
0.598836501
0.576613364
0.246860078
0.254642218
0.31481074
0.113328685
0.412109651
0.806475866
1.078409581
1.128171091
1.241268589
1.291983682
1.479329227
1.423108334
1.650579856
1.757857918
1.776645831
1.684545385
1.69744879
1.5518088
1.1442228
0.966983846
0.841567186
0.657520003
-0.478035801
-0.510825624




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=50308&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=50308&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50308&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c1.27988698126615
b-0.114294646993620

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 1.27988698126615 \tabularnewline
b & -0.114294646993620 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50308&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]1.27988698126615[/C][/ROW]
[ROW][C]b[/C][C]-0.114294646993620[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50308&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50308&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]
c1.27988698126615
b-0.114294646993620







Descriptive Statistics about e[t]
# observations220
minimum-1.55103814575611
Q1-0.262647594788117
median0.0619153399971973
mean3.91771526835944e-17
Q30.305332541570862
maximum1.12196972720057

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 220 \tabularnewline
minimum & -1.55103814575611 \tabularnewline
Q1 & -0.262647594788117 \tabularnewline
median & 0.0619153399971973 \tabularnewline
mean & 3.91771526835944e-17 \tabularnewline
Q3 & 0.305332541570862 \tabularnewline
maximum & 1.12196972720057 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50308&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]220[/C][/ROW]
[ROW][C]minimum[/C][C]-1.55103814575611[/C][/ROW]
[ROW][C]Q1[/C][C]-0.262647594788117[/C][/ROW]
[ROW][C]median[/C][C]0.0619153399971973[/C][/ROW]
[ROW][C]mean[/C][C]3.91771526835944e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.305332541570862[/C][/ROW]
[ROW][C]maximum[/C][C]1.12196972720057[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50308&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50308&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]
# observations220
minimum-1.55103814575611
Q1-0.262647594788117
median0.0619153399971973
mean3.91771526835944e-17
Q30.305332541570862
maximum1.12196972720057



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')