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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 13:07:43 -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/t125779730389p6pcdds48o03y.htm/, Retrieved Fri, 29 Mar 2024 10:22:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54984, Retrieved Fri, 29 Mar 2024 10:22:16 +0000
QR Codes:

Original text written by user:Bivariate EDA Y=f(Z) en X=f(Z)
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Box-Cox Linearity Plot] [3/11/2009] [2009-11-02 21:47:57] [b98453cac15ba1066b407e146608df68]
- RMPD    [Bivariate Explorative Data Analysis] [Shw5: Bivariate E...] [2009-11-09 20:07:43] [7a39e26d7a09dd77604df90cb29f8d39] [Current]
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Dataseries X:
-40844.25096
-39642.2792
-40387.28856
-39569.2418
-40148.79021
-39863.32829
-39214.02298
-37998.98205
-39201.05258
-41419.06871
-41419.37972
-38973.17654
-40015.01316
-39956.46282
-40836.73284
-40532.39319
-40936.02655
-42877.16523
-41299.49653
-40972.33476
-43876.26117
-46313.92341
-45101.62748
-48202.16992
-46874.10431
-46249.28511
-45528.49008
-45286.43675
-45660.00557
-45845.88583
-45957.86748
-45918.29858
-45496.07747
-45592.84717
-47339.05301
-47647.49435
-49806.96381
-48474.33669
-48058.90168
-46661.75709
-46475.99397
-46566.04365
-45282.92189
-40623.09239
-40500.54352
-45587.72861
-44493.85864
-42024.80743
-41966.23753
-41389.86007
-37635.1674
-37887.51141
-43418.43387
-45233.15894
-46915.80807
-48156.89717
-46639.67061
-47716.72199
-40342.78154
Dataseries Y:
-1.069110747
-0.224600155
-0.519176561
-0.443841916
-0.891681921
-1.156458458
-1.006923284
-0.875826413
-0.540297967
0.171800008
0.591873748
0.389981437
0.673187551
1.247849664
0.778924303
0.678994652
0.484846026
-0.005963015
-0.059886436
0.354323765
-0.043744137
-2.324150774
-0.742260114
-0.928757841
0.452743329
0.698858699
1.179755043
1.546243351
-0.10570001
-0.32691026
0.362464223
0.651949789
0.551157845
0.446572065
0.494726378
0.755766464
1.09262198
0.863112479
0.364138006
0.637611953
0.988913294
-0.167260062
-0.154025582
-0.096528058
-0.45853115
-1.333579753
0.209242602
0.691360013
0.845796569
0.714135402
1.718736881
1.594872844
-2.013866339
-1.988010127
-1.266473304
-0.471055044
-0.459380319
-0.626904673
-1.931655944




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54984&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]5 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=54984&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54984&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 time5 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c0.00109477307821679
b2.51833338385049e-08

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.00109477307821679 \tabularnewline
b & 2.51833338385049e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54984&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.00109477307821679[/C][/ROW]
[ROW][C]b[/C][C]2.51833338385049e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54984&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54984&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]
c0.00109477307821679
b2.51833338385049e-08







Descriptive Statistics about e[t]
# observations59
minimum-2.32407920808361
Q1-0.529829887195926
median0.171748305156387
mean-8.65340344107498e-17
Q30.676010554533752
maximum1.71858988690649

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 59 \tabularnewline
minimum & -2.32407920808361 \tabularnewline
Q1 & -0.529829887195926 \tabularnewline
median & 0.171748305156387 \tabularnewline
mean & -8.65340344107498e-17 \tabularnewline
Q3 & 0.676010554533752 \tabularnewline
maximum & 1.71858988690649 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54984&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]59[/C][/ROW]
[ROW][C]minimum[/C][C]-2.32407920808361[/C][/ROW]
[ROW][C]Q1[/C][C]-0.529829887195926[/C][/ROW]
[ROW][C]median[/C][C]0.171748305156387[/C][/ROW]
[ROW][C]mean[/C][C]-8.65340344107498e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.676010554533752[/C][/ROW]
[ROW][C]maximum[/C][C]1.71858988690649[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54984&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54984&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]
# observations59
minimum-2.32407920808361
Q1-0.529829887195926
median0.171748305156387
mean-8.65340344107498e-17
Q30.676010554533752
maximum1.71858988690649



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')