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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, 04 Nov 2009 14:21:58 -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/04/t1257369802gt9hz6cw968x5w2.htm/, Retrieved Mon, 29 Apr 2024 12:30:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53850, Retrieved Mon, 29 Apr 2024 12:30:40 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [Workshop5 Y,Z EDA] [2009-11-04 21:21:58] [5ed0eef5d4509bbfdac0ae6d87f3b4bf] [Current]
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Dataseries X:
87130
88620
89563
89056
88542
89504
89428
86040
96240
94423
93028
92285
91685
94260
93858
92437
92980
92099
92803
88551
98334
98329
96455
97109
97687
98512
98673
96028
98014
95580
97838
97760
99913
97588
93942
93656
93365
92881
93120
91063
90930
91946
94624
95484
95862
95530
94574
94677
93845
91533
91214
90922
89563
89945
91850
92505
92437
93876
93561
94119
95264
96089
97160
98644
96266
97938
99757
101550
102449
Dataseries Y:
258961
258647
256304
250498
247883
249552
262626
264416
273049
272441
267564
265952
263937
264765
263386
258985
257334
257477
271486
274488
281274
272674
269704
268227
276444
272247
268516
263406
263619
265905
281681
287413
289423
281242
273878
269022
272630
270287
260447
262248
252806
238663
258438
266719
263279
258064
248828
248284
253376
251846
239494
239709
228793
229521
249999
254016
251178
242936
241478
243985
246546
247323
247599
248985
241326
242967
263281
268145
263948




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53850&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]3 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=53850&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53850&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c119456.209064478
b1.49081278555879

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 119456.209064478 \tabularnewline
b & 1.49081278555879 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53850&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]119456.209064478[/C][/ROW]
[ROW][C]b[/C][C]1.49081278555879[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53850&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53850&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]
c119456.209064478
b1.49081278555879







Descriptive Statistics about e[t]
# observations69
minimum-24184.8745774809
Q1-6388.36341805389
median910.495686284231
mean5.8335301162884e-13
Q39420.45912055785
maximum23018.8279615046

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 69 \tabularnewline
minimum & -24184.8745774809 \tabularnewline
Q1 & -6388.36341805389 \tabularnewline
median & 910.495686284231 \tabularnewline
mean & 5.8335301162884e-13 \tabularnewline
Q3 & 9420.45912055785 \tabularnewline
maximum & 23018.8279615046 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53850&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]-24184.8745774809[/C][/ROW]
[ROW][C]Q1[/C][C]-6388.36341805389[/C][/ROW]
[ROW][C]median[/C][C]910.495686284231[/C][/ROW]
[ROW][C]mean[/C][C]5.8335301162884e-13[/C][/ROW]
[ROW][C]Q3[/C][C]9420.45912055785[/C][/ROW]
[ROW][C]maximum[/C][C]23018.8279615046[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53850&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53850&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-24184.8745774809
Q1-6388.36341805389
median910.495686284231
mean5.8335301162884e-13
Q39420.45912055785
maximum23018.8279615046



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')