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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 10:07:46 -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/t1257268170s9n6vhj1kwq2e1a.htm/, Retrieved Wed, 01 May 2024 16:44:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53252, Retrieved Wed, 01 May 2024 16:44:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

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] [WS5] [2009-11-03 17:07:46] [612b7913d2a3b4fa79d126829bd148db] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-12,35
-12,432
-11,474
-10,58
-9,906
-9,214
-8,868
-8,886
-9,268
-8,876
-8,83
-11,082
-11,31
-11,31
-11,018
-10,298
-9,87
-8,85
-8,604
-8,048
-7,984
-7,856
-8,156
-11,072
-11,746
-11,5
-10,288
-9,158
-8,256
-7,992
-7,828
-8,092
-9,058
-8,784
-8,628
-10,542
-10,25
-9,402
-8,582
-7,68
-7,562
-7,708
-7,416
-6,486
-6,066
-5,628
-6,786
-11,162
-12,274
-11,444
-9,83
-7,752
-8,026
-9,276
-10,124
-10,37
-9,932
-9,102
-9,412
-11,91
-12,12
Dataseries Y:
Download CSV
Histogram 
-13,65
-13,632
-12,474
-11,28
-10,606
-9,914
-9,668
-9,586
-9,968
-9,476
-9,63
-12,182
-12,51
-12,41
-11,818
-10,998
-10,47
-9,45
-9,104
-8,448
-8,284
-8,256
-8,856
-12,372
-13,246
-12,9
-11,388
-10,058
-9,056
-8,792
-8,728
-9,092
-10,058
-9,684
-9,428
-11,342
-10,95
-10,002
-9,282
-8,48
-8,262
-8,208
-7,716
-6,886
-6,366
-5,928
-7,186
-11,662
-12,874
-12,044
-10,63
-8,552
-8,726
-9,876
-10,424
-10,47
-9,932
-9,002
-9,312
-12,01
-12,32

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=53252&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=53252&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53252&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]
c0.0244061390917008
b1.07502650899089

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.0244061390917008 \tabularnewline
b & 1.07502650899089 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53252&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.0244061390917008[/C][/ROW]
[ROW][C]b[/C][C]1.07502650899089[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53252&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53252&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]
c0.0244061390917008
b1.07502650899089






Descriptive Statistics about e[t]
# observations61
minimum-0.643144764484711
Q1-0.237313369753134
median-0.0290604537641353
mean1.12330454591941e-18
Q30.121121944265913
maximum0.781743363530554

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -0.643144764484711 \tabularnewline
Q1 & -0.237313369753134 \tabularnewline
median & -0.0290604537641353 \tabularnewline
mean & 1.12330454591941e-18 \tabularnewline
Q3 & 0.121121944265913 \tabularnewline
maximum & 0.781743363530554 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53252&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]-0.643144764484711[/C][/ROW]
[ROW][C]Q1[/C][C]-0.237313369753134[/C][/ROW]
[ROW][C]median[/C][C]-0.0290604537641353[/C][/ROW]
[ROW][C]mean[/C][C]1.12330454591941e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.121121944265913[/C][/ROW]
[ROW][C]maximum[/C][C]0.781743363530554[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53252&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53252&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]
# observations61
minimum-0.643144764484711
Q1-0.237313369753134
median-0.0290604537641353
mean1.12330454591941e-18
Q30.121121944265913
maximum0.781743363530554


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')