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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 computationSat, 12 Dec 2015 12:57:44 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Dec/12/t1449925081p8k68acm09ezmtn.htm/, Retrieved Thu, 16 May 2024 13:51:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286074, Retrieved Thu, 16 May 2024 13:51:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [bivariate EDA] [2015-12-12 12:57:44] [20fcaaf1d4bc4a12bf87c6c50d624c14] [Current]
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Dataseries X:
287224
279998
283495
285775
282329
277799
271980
266730
262433
285378
286692
282917
277686
274371
277466
290604
290770
283654
278601
274405
272817
294292
300562
298982
296917
295008
297295
305671
303853
300708
298194
292254
290646
314707
317009
317706
313312
311048
315917
326174
322116
317092
310468
302438
298493
320124
321873
321676
316696
312612
313307
320883
318749
315126
304600
295245
293619
309700
310597
307416
301126
Dataseries Y:
276444
268606
267679
269879
265641
262525
258597
253849
256221
286895
294610
280363
269926
264341
263269
271045
267915
262078
257751
253271
257638
287452
298152
284793
274560
268270
267577
271866
268546
264722
262425
258973
262751
296186
304659
295442
285466
279575
279985
286012
281337
276270
271472
265637
268974
299299
305452
295468
285584
278204
276505
279732
276980
271832
263105
256162
260705
285857
291870
280358
270981




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286074&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286074&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286074&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'Sir Maurice George Kendall' @ kendall.wessa.net







Model: Y[t] = c + b X[t] + e[t]
c111903.047218648
b0.545225612413163

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 111903.047218648 \tabularnewline
b & 0.545225612413163 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286074&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]111903.047218648[/C][/ROW]
[ROW][C]b[/C][C]0.545225612413163[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286074&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286074&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]
c111903.047218648
b0.545225612413163







Descriptive Statistics about e[t]
# observations61
minimum-16716.1831555721
Q1-6696.70539059172
median-1919.38350853729
mean5.02395939058081e-13
Q35097.58061699565
maximum26395.1315073977

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -16716.1831555721 \tabularnewline
Q1 & -6696.70539059172 \tabularnewline
median & -1919.38350853729 \tabularnewline
mean & 5.02395939058081e-13 \tabularnewline
Q3 & 5097.58061699565 \tabularnewline
maximum & 26395.1315073977 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286074&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-16716.1831555721[/C][/ROW]
[ROW][C]Q1[/C][C]-6696.70539059172[/C][/ROW]
[ROW][C]median[/C][C]-1919.38350853729[/C][/ROW]
[ROW][C]mean[/C][C]5.02395939058081e-13[/C][/ROW]
[ROW][C]Q3[/C][C]5097.58061699565[/C][/ROW]
[ROW][C]maximum[/C][C]26395.1315073977[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286074&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286074&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]
# observations61
minimum-16716.1831555721
Q1-6696.70539059172
median-1919.38350853729
mean5.02395939058081e-13
Q35097.58061699565
maximum26395.1315073977



Parameters (Session):
par1 = 12 ; par2 = 0 ;
Parameters (R input):
par1 = 0 ; par2 = 0 ;
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')