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Description of Statistical Computation

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 computationTue, 03 Nov 2009 12:58:27 -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/03/t1257278402a5sbvni9kszg91h.htm/, Retrieved Thu, 12 Feb 2026 20:44:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53377, Retrieved Thu, 12 Feb 2026 20:44:01 +0000
QR Codes:

Original text written by user:WS 5
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact357

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [WS 5 Y[t] - g - h...] [2009-11-03 19:58:27] [9b6f46453e60f88d91cef176fe926003] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-9063,91
-9110,33
-9062,71
-9155,95
-9063,71
-9155,85
-9688,93
-9738,65
-9710,89
-9664,17
-9480,59
-9665,97
-9851,55
-9897,17
-9940,89
-9803,43
-9781,27
-9871,41
-10197,65
-10384,93
-10450,51
-10682,01
-10520,39
-10660,05
-10660,75
-10706,47
-10680,81
-10543,15
-10520,59
-10542,35
-10915,21
-10916,41
-10889,15
-10751,69
-10611,33
-10751,39
-10821,37
-10797,91
-10701,97
-10636,39
-10680,51
-10656,95
-11006,55
-11007,95
-10888,85
-10471,57
-10239,87
-10219,41
-10264,13
-10125,47
-9867,91
-9801,23
-9614,75
-9382,15
-9962,35
-10033,73
-9661,07
-9519,71
-9335,93
-9454,53
-9521,01
-9381,75
-9196,27
-9171,51
-8895,29
-9008,49
-9542,67
-9546,77
-9264,35
-9172,21
-9176,71
-9456,03
-9688,03
-9803,43
-9894,77
-9942,19
-9803,63
-10009,97
Dataseries Y:
Download CSV
Histogram 
-10095,16
-10146,94
-10094,36
-10198,42
-10095,96
-10198,62
-10792,49
-10845,67
-10817,18
-10764,6
-10559,78
-10765,3
-10972,32
-11023,5
-11072,48
-10919,54
-10894,85
-10994,81
-11358,87
-11565,29
-11640,46
-11898,26
-11717,83
-11872,27
-11873,47
-11924,35
-11896,56
-11743,32
-11717,93
-11741,92
-12157,76
-12157,16
-12128,97
-11975,53
-11818,69
-11973,33
-12051,6
-12026,11
-11919,25
-11846,28
-11896,26
-11870,17
-12259,62
-12259,12
-12128,47
-11663,55
-11405,55
-11381,56
-11432,14
-11277,9
-10991,91
-10916,84
-10709,02
-10450,82
-11096,27
-11175,04
-10761
-10603,46
-10398,04
-10528,59
-10603,26
-10449,82
-10242,2
-10215,11
-9907,63
-10033,78
-10628,45
-10630,95
-10318,07
-10215,31
-10219,01
-10530,09
-10788,69
-10918,14
-11019,9
-11073,18
-10918,94
-11148,65

Tables (Output of Computation)





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=53377&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=53377&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53377&T=0

As an alternative you can also use a QR Code:  
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-0.00281415642803096
b1.11378155249600

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.00281415642803096 \tabularnewline
b & 1.11378155249600 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53377&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.00281415642803096[/C][/ROW]
[ROW][C]b[/C][C]1.11378155249600[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53377&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53377&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c-0.00281415642803096
b1.11378155249600






Descriptive Statistics about e[t]
# observations78
minimum-1.36704552573386
Q1-0.592779968677823
median-0.212324322927075
mean9.22405848283822e-18
Q30.408626058614193
maximum2.06912607862401

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 78 \tabularnewline
minimum & -1.36704552573386 \tabularnewline
Q1 & -0.592779968677823 \tabularnewline
median & -0.212324322927075 \tabularnewline
mean & 9.22405848283822e-18 \tabularnewline
Q3 & 0.408626058614193 \tabularnewline
maximum & 2.06912607862401 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53377&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]78[/C][/ROW]
[ROW][C]minimum[/C][C]-1.36704552573386[/C][/ROW]
[ROW][C]Q1[/C][C]-0.592779968677823[/C][/ROW]
[ROW][C]median[/C][C]-0.212324322927075[/C][/ROW]
[ROW][C]mean[/C][C]9.22405848283822e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.408626058614193[/C][/ROW]
[ROW][C]maximum[/C][C]2.06912607862401[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53377&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53377&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations78
minimum-1.36704552573386
Q1-0.592779968677823
median-0.212324322927075
mean9.22405848283822e-18
Q30.408626058614193
maximum2.06912607862401


Figures (Output of Computation)

Input Parameters & R Code

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')