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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 computationWed, 28 Oct 2009 14:45:10 -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/28/t1256762783pnbb6odh8ew9lt4.htm/, Retrieved Mon, 06 May 2024 09:19:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51820, Retrieved Mon, 06 May 2024 09:19:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Partial Correlation] [partial correlation] [2009-10-28 19:24:30] [cd6314e7e707a6546bd4604c9d1f2b69]
- RMPD  [Bivariate Explorative Data Analysis] [relatie vlaandere...] [2009-10-28 19:52:15] [cd6314e7e707a6546bd4604c9d1f2b69]
-    D      [Bivariate Explorative Data Analysis] [bivariate EDA tus...] [2009-10-28 20:45:10] [ea241b681aafed79da4b5b99fad98471] [Current]
- RMP         [Pearson Correlation] [correlation tusse...] [2009-10-29 16:05:24] [cd6314e7e707a6546bd4604c9d1f2b69]
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Dataseries X:
5877.641004
5264.324975
6142.177029
10268.13606
10473.95003
11975.11389
27071.77554
39415.43061
17684.58436
18056.32275
14220.73908
19910.88099
20825.80839
17078.14492
15893.85256
16587.08554
15452.75508
16634.15379
30075.88387
30024.98807
10837.18097
18212.88846
9612.37698
15383.76942
-10793.78215
-2665.770597
-2747.627613
5616.223003
3604.418271
-2472.739559
1060.469578
-8354.360115
-19737.63012
-29682.41175
-31450.81059
-26654.75529
-33207.92652
-38530.07447
-28833.33473
-39506.72592
-28597.11427
-2341.826355
343.2037971
-13047.16234
-26584.87934
-26927.22357
-18923.29632
-13025.37249
-24270.05651
-29451.89576
-10651.68425
-13617.95194
-4687.142289
1547.342007
-3588.856605
-9350.202187
-17243.26871
-6501.430206
-6826.935843
600.2497751
5685.935602
7979.577494
10909.68967
7336.861697
15319.24875
23453.89399
18322.6577
15060.75058
10453.76214
Dataseries Y:
12759.67629
10622.97664
10308.72729
14324.40815
14766.20241
15482.80982
32045.46369
47967.4267
16954.41759
19078.51507
16119.42199
22381.18044
23681.8785
17447.24575
16518.34184
18164.67245
16311.81215
18389.41422
32616.54318
37136.81187
8887.473886
15353.85271
8311.578885
13271.94069
-12610.00173
-5753.20383
-6392.730644
4072.838634
97.67948377
-3302.437027
-349.966368
-9077.38537
-22399.95763
-30889.52098
-29794.84033
-25229.06177
-31107.64024
-36194.88959
-27783.31195
-36208.22571
-26169.46189
-2433.81936
-324.3648547
-13694.31753
-27975.766
-28540.55489
-20562.5741
-14825.48688
-24696.80327
-27729.30797
-9923.327593
-12574.73706
-3445.486919
2484.396362
-2379.636843
-8368.905883
-16495.70087
-8069.129444
-8234.645685
-1098.922628
3114.041771
4665.292196
6553.747945
1644.27573
11190.37869
17827.49059
13036.98367
8499.203837
2547.001736




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51820&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]4 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=51820&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51820&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c5.45446904841e-08
b1.00805734791398

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 5.45446904841e-08 \tabularnewline
b & 1.00805734791398 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51820&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]5.45446904841e-08[/C][/ROW]
[ROW][C]b[/C][C]1.00805734791398[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51820&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51820&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]
c5.45446904841e-08
b1.00805734791398







Descriptive Statistics about e[t]
# observations69
minimum-7990.99000262656
Q1-1704.00882442782
median-73.1240953581747
mean-2.47209660149868e-13
Q31909.38038304590
maximum8234.4122523412

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 69 \tabularnewline
minimum & -7990.99000262656 \tabularnewline
Q1 & -1704.00882442782 \tabularnewline
median & -73.1240953581747 \tabularnewline
mean & -2.47209660149868e-13 \tabularnewline
Q3 & 1909.38038304590 \tabularnewline
maximum & 8234.4122523412 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51820&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]69[/C][/ROW]
[ROW][C]minimum[/C][C]-7990.99000262656[/C][/ROW]
[ROW][C]Q1[/C][C]-1704.00882442782[/C][/ROW]
[ROW][C]median[/C][C]-73.1240953581747[/C][/ROW]
[ROW][C]mean[/C][C]-2.47209660149868e-13[/C][/ROW]
[ROW][C]Q3[/C][C]1909.38038304590[/C][/ROW]
[ROW][C]maximum[/C][C]8234.4122523412[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51820&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51820&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]
# observations69
minimum-7990.99000262656
Q1-1704.00882442782
median-73.1240953581747
mean-2.47209660149868e-13
Q31909.38038304590
maximum8234.4122523412



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')