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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 computationTue, 27 Oct 2009 11:27:01 -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/27/t1256664476dffknd1hen408zu.htm/, Retrieved Tue, 07 May 2024 19:16:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51072, Retrieved Tue, 07 May 2024 19:16:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsHSWWS4Q2
Estimated Impact123
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [] [2009-10-27 17:27:01] [4563e36d4b7005634fe3557528d9fcab] [Current]
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Dataseries X:
3.971090213
3.970207359
4.006423253
3.990693961
3.989894564
3.996117476
3.974465636
3.943247125
4.008131562
4.022387126
3.996248915
3.990782692
3.983400738
3.988068203
4.024854948
3.982768577
3.972573081
3.978180517
3.986323777
3.926033597
3.993171605
4.025346835
3.997473759
4.009833179
3.972249136
3.983851719
4.050302404
3.999956568
4.003848122
4.065280871
4.022552084
3.998477303
4.063220736
4.05388479
4.067665882
4.069926969
4.025100961
4.031448862
4.086324231
4.067814511
4.040523226
4.070148736
4.034989216
4.021933166
4.085754244
4.077985291
4.092123869
4.091983332
4.085004999
4.082641778
4.156094631
4.102776615
4.141919874
4.132355762
4.104964846
4.09565744
4.126748142
4.144916527
4.148849343
4.118694508
4.127525925
4.132867788
4.187182178
4.136974096
4.166992231
4.172690482
4.145848757
4.141575183
4.157275396
4.195124423
4.201506367
4.146624089
Dataseries Y:
4.154454406
4.146531122
4.20172477
4.155032229
4.168615322
4.167937313
4.143576832
4.12264177
4.194791758
4.193931191
4.179350682
4.16214604
4.179896333
4.173419384
4.208629438
4.149896207
4.145662471
4.153387979
4.143670433
4.093211492
4.189040908
4.208064948
4.179178229
4.164144582
4.16716959
4.161757195
4.232258962
4.181243161
4.18920949
4.23484617
4.202433822
4.176178109
4.260453018
4.251565224
4.255971639
4.23756887
4.222872477
4.224014811
4.276737459
4.249516316
4.223651667
4.256741793
4.223054413
4.224507165
4.290346301
4.284453294
4.299964669
4.279940573
4.29125782
4.28064665
4.35283829
4.275403503
4.296687124
4.30847904
4.259331025
4.280737674
4.318939392
4.334493962
4.349471799
4.308222819
4.326643036
4.312388949
4.364588514
4.303930064
4.326192438
4.335016361
4.318543299
4.31160554
4.344510166
4.383420373
4.39720978
4.33485569




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 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 & 16 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51072&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]16 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=51072&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51072&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 time16 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c0.0959634753694153
b1.02133626818553

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.0959634753694153 \tabularnewline
b & 1.02133626818553 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51072&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.0959634753694153[/C][/ROW]
[ROW][C]b[/C][C]1.02133626818553[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51072&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51072&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]
c0.0959634753694153
b1.02133626818553







Descriptive Statistics about e[t]
# observations72
minimum-0.0295693386040709
Q1-0.0094915386927146
median0.00134299578272001
mean-4.36542546277807e-19
Q30.00865764490430123
maximum0.0245666723131779

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 72 \tabularnewline
minimum & -0.0295693386040709 \tabularnewline
Q1 & -0.0094915386927146 \tabularnewline
median & 0.00134299578272001 \tabularnewline
mean & -4.36542546277807e-19 \tabularnewline
Q3 & 0.00865764490430123 \tabularnewline
maximum & 0.0245666723131779 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51072&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]72[/C][/ROW]
[ROW][C]minimum[/C][C]-0.0295693386040709[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0094915386927146[/C][/ROW]
[ROW][C]median[/C][C]0.00134299578272001[/C][/ROW]
[ROW][C]mean[/C][C]-4.36542546277807e-19[/C][/ROW]
[ROW][C]Q3[/C][C]0.00865764490430123[/C][/ROW]
[ROW][C]maximum[/C][C]0.0245666723131779[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51072&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51072&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]
# observations72
minimum-0.0295693386040709
Q1-0.0094915386927146
median0.00134299578272001
mean-4.36542546277807e-19
Q30.00865764490430123
maximum0.0245666723131779



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')