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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 12:40:38 -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/t1257364133kmsw6f65e4nmc9o.htm/, Retrieved Mon, 29 Apr 2024 10:12:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53834, Retrieved Mon, 29 Apr 2024 10:12:38 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [] [2009-11-04 19:40:38] [82bf023f1e4d9556a54030fcde33aa09] [Current]
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Dataseries X:
561278,953403
531688,863508
530476,739984
516554,039015
529717,931445
516329,925670
498702,735525
485559,950110
484415,489208
585513,012854
591640,832901
591184,538059
562076,281333
530999,465840
532933,809615
518188,961997
533223,711085
511609,605386
506174,094115
496165,453587
496047,989229
579981,128842
586091,473023
574269,182369
514907,874461
476875,512441
457465,603353
455610,427846
455500,237443
418876,375959
412242,387427
379690,136583
355843,920372
462294,800073
474151,341638
429638,357104
404162,558230
376383,480981
379651,991480
377545,637891
378910,852584
349587,403733
345057,419945
308009,944364
317241,810145
413015,475329
416106,506654
384505,026884
365277,427820
359238,927542
378922,695756
397396,594516
419572,566945
425088,005901
429181,353756
403454,736163
421312,533750
517493,790015
532462,390475
500425,214996
Dataseries Y:
-728,6536239
-142,7511303
-787,4949964
-451,4486862
-608,6620624
-296,7188762
552,6397207
292,2142193
1109,976956
676,0328384
-795,667833
6,748639935
337,1910648
-28,2329969
-301,334858
959,2260214
975,7066251
338,5370335
1429,849533
239,3427171
703,4676389
668,1531457
-323,5548664
-180,6756105
268,5288785
671,1955607
-437,4322114
24,26534452
196,6884971
-230,2832497
696,8676478
-136,156074
-155,3059685
529,5866478
-321,7732118
76,40069887
-616,1635797
1191,089993
-111,028839
-541,98817
71,06336825
581,3435659
176,8095
446,251913
-59,83651764
361,9772745
-545,3283088
-584,3486789
89,33123317
-271,0948937
-267,8957385
356,7999528
-1291,339839
-888,6439591
-571,7600768
-228,9650974
-610,0780403
-549,9429329
-611,468584
-351,2567187




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53834&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53834&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53834&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Model: Y[t] = c + b X[t] + e[t]
c-87.772122128573
b0.000189819113000873

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -87.772122128573 \tabularnewline
b & 0.000189819113000873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53834&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-87.772122128573[/C][/ROW]
[ROW][C]b[/C][C]0.000189819113000873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53834&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53834&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]
c-87.772122128573
b0.000189819113000873







Descriptive Statistics about e[t]
# observations60
minimum-1283.21060936843
Q1-442.803951639795
median-68.2883217621445
mean1.77635683940025e-14
Q3369.691745747481
maximum1421.54013755964

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1283.21060936843 \tabularnewline
Q1 & -442.803951639795 \tabularnewline
median & -68.2883217621445 \tabularnewline
mean & 1.77635683940025e-14 \tabularnewline
Q3 & 369.691745747481 \tabularnewline
maximum & 1421.54013755964 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53834&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]-1283.21060936843[/C][/ROW]
[ROW][C]Q1[/C][C]-442.803951639795[/C][/ROW]
[ROW][C]median[/C][C]-68.2883217621445[/C][/ROW]
[ROW][C]mean[/C][C]1.77635683940025e-14[/C][/ROW]
[ROW][C]Q3[/C][C]369.691745747481[/C][/ROW]
[ROW][C]maximum[/C][C]1421.54013755964[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53834&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53834&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-1283.21060936843
Q1-442.803951639795
median-68.2883217621445
mean1.77635683940025e-14
Q3369.691745747481
maximum1421.54013755964



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')