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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 computationMon, 09 Nov 2009 06:37:47 -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/09/t12577739406uc0v2evkdkhrvz.htm/, Retrieved Thu, 28 Mar 2024 11:45:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54817, Retrieved Thu, 28 Mar 2024 11:45:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [Workshop 5 X en Y] [2009-11-04 16:28:52] [986fdfce84f082a54cc17f886bb03ad8]
-    D    [Bivariate Explorative Data Analysis] [Feedback WS 5 (ni...] [2009-11-09 13:37:47] [3d2053c5f7c50d3c075d87ce0bd87294] [Current]
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Dataseries X:
-19,339
-46,346
-40,846
-45,051
-48,151
-43,107
-40,914
-54,37
-47,97
-54,798
-49,898
-46,498
-40,098
-54,156
-55,556
-47,321
-52,421
-39,021
-46,823
-53,123
-59,423
-54,923
-46,523
-44,823
-45,823
-49,523
-36,323
-50,523
-44,223
-41,023
-42,323
-60,723
-62,023
-46,916
-46,802
-48,202
-44,802
-43,66
-44,36
-50,36
-41,16
-43,523
-38,309
-47,016
-51,216
-53,309
-50,209
-48,916
-33,453
-34,086
-48,312
-36,482
-37,008
-50,008
-41,308
-51,464
-40,436
-27,452
-35,48
-32,108
-5,15
Dataseries Y:
-26,293
-49,202
-52,402
-50,437
-54,537
-60,509
-65,018
-64,09
-63,39
-55,226
-62,226
-56,826
-53,926
-60,472
-57,472
-56,927
-63,227
-57,927
-64,601
-62,901
-58,401
-58,201
-65,401
-57,401
-51,401
-61,001
-58,001
-53,701
-58,101
-54,601
-61,501
-52,201
-58,301
-52,992
-59,874
-55,374
-47,174
-44,42
-50,62
-54,22
-41,32
-47,201
-56,983
-54,992
-46,192
-45,783
-43,383
-46,592
-36,411
-53,782
-53,244
-40,134
-33,096
-43,896
-40,996
-41,768
-47,432
-30,924
-30,76
-41,496
-19,35




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=54817&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=54817&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54817&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-20.1585911764024
b0.700620665388705

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -20.1585911764024 \tabularnewline
b & 0.700620665388705 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54817&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-20.1585911764024[/C][/ROW]
[ROW][C]b[/C][C]0.700620665388705[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54817&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54817&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-20.1585911764024
b0.700620665388705







Descriptive Statistics about e[t]
# observations61
minimum-16.1942149198841
Q1-5.8386632464137
median0.762976762661532
mean-7.34698049210833e-17
Q35.58463429111315
maximum14.4473330999667

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -16.1942149198841 \tabularnewline
Q1 & -5.8386632464137 \tabularnewline
median & 0.762976762661532 \tabularnewline
mean & -7.34698049210833e-17 \tabularnewline
Q3 & 5.58463429111315 \tabularnewline
maximum & 14.4473330999667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54817&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]-16.1942149198841[/C][/ROW]
[ROW][C]Q1[/C][C]-5.8386632464137[/C][/ROW]
[ROW][C]median[/C][C]0.762976762661532[/C][/ROW]
[ROW][C]mean[/C][C]-7.34698049210833e-17[/C][/ROW]
[ROW][C]Q3[/C][C]5.58463429111315[/C][/ROW]
[ROW][C]maximum[/C][C]14.4473330999667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54817&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54817&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-16.1942149198841
Q1-5.8386632464137
median0.762976762661532
mean-7.34698049210833e-17
Q35.58463429111315
maximum14.4473330999667



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')