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Author's title

Author*Unverified author*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationTue, 03 Nov 2009 11:04:05 -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/03/t1257271482bijpalgnc0kroq6.htm/, Retrieved Wed, 01 May 2024 19:23:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53284, Retrieved Wed, 01 May 2024 19:23:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [ws5555555555555] [2009-11-03 18:04:05] [9a1fef436e1d399a5ecd6808bfbd8489] [Current]
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Dataseries X:
335,2807094
-6315,156455
-8630,36
7249,484254
3022,609926
6452,735598
3829,376307
-360,9351859
4232,268359
-4860,450223
-4137,887387
-3268,121007
-3195,19888
-4482,480298
-12291,55817
8975,80112
6572,597575
11656,83119
4297,112613
3942,986941
926,0648141
-4589,216604
-5380,77944
-4466,342276
-1629,54582
-5233,186529
-13266,90511
8499,45418
3926,45418
7970,298433
3178,298433
2400,579851
3087,939142
-2262,701567
-3992,701567
-2256,701567
2104,657724
-2847,982984
-9914,623693
8904,017016
7430,298433
7357,017016
9309,45418
3135,939142
4144,939142
-2513,138731
-4901,060858
-2141,982984
-200,1387307
-7155,498022
-11218,49802
2728,861269
1390,579851
5086,579851
3458,142687
-2174,060858
87,65772447
-3633,982984
-5709,701567
-2663,420149
Dataseries Y:
-97,0413027
-338,0413544
138,4587102
517,4586327
-277,5414708
-120,5415742
-305,0415871
-253,0417423
439,458193
110,4581672
858,4581155
519,9579991
-967,5420397
-129,5420138
57,95794738
-375,5420397
-542,041975
874,4581413
834,4581155
299,4582189
1419,958258
260,9582836
803,9583353
1090,958387
229,4584516
360,9584646
601,9584387
909,4584516
-243,5415484
118,4583741
229,4583741
-326,5416518
589,9583611
-301,5416259
-385,5416259
596,4583741
-187,041613
110,4583999
-639,0415871
1058,4584
-259,5416259
-637,5416001
4,45845164
299,9583611
-117,0416389
-15,54167766
-420,0416389
326,4583999
-670,5416777
-811,0416906
-199,0416906
-562,5416777
-445,5416518
242,4583482
-1460,541704
-941,0416389
-584,041613
-289,5416001
-643,5416259
-358,5416518




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=53284&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=53284&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53284&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]
c2.90153697748201e-10
b0.0101967225030024

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 2.90153697748201e-10 \tabularnewline
b & 0.0101967225030024 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53284&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]2.90153697748201e-10[/C][/ROW]
[ROW][C]b[/C][C]0.0101967225030024[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53284&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53284&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]
c2.90153697748201e-10
b0.0101967225030024







Descriptive Statistics about e[t]
# observations60
minimum-1495.80342535542
Q1-346.376791585025
median-87.558624339017
mean1.53525340588582e-14
Q3360.300436241471
maximum1410.51543207054

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1495.80342535542 \tabularnewline
Q1 & -346.376791585025 \tabularnewline
median & -87.558624339017 \tabularnewline
mean & 1.53525340588582e-14 \tabularnewline
Q3 & 360.300436241471 \tabularnewline
maximum & 1410.51543207054 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53284&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]-1495.80342535542[/C][/ROW]
[ROW][C]Q1[/C][C]-346.376791585025[/C][/ROW]
[ROW][C]median[/C][C]-87.558624339017[/C][/ROW]
[ROW][C]mean[/C][C]1.53525340588582e-14[/C][/ROW]
[ROW][C]Q3[/C][C]360.300436241471[/C][/ROW]
[ROW][C]maximum[/C][C]1410.51543207054[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53284&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53284&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-1495.80342535542
Q1-346.376791585025
median-87.558624339017
mean1.53525340588582e-14
Q3360.300436241471
maximum1410.51543207054



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')