FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationFri, 13 Nov 2009 06:07:31 -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/13/t1258117799zjvl2fcysptfdy0.htm/, Retrieved Sun, 05 May 2024 18:40:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56568, Retrieved Sun, 05 May 2024 18:40:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

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] [3/11/2009] [2009-11-02 22:01:32] [b98453cac15ba1066b407e146608df68]
-   PD    [Bivariate Explorative Data Analysis] [] [2009-11-13 13:07:31] [5858ea01c9bd81debbf921a11363ad90] [Current]
-   PD      [Bivariate Explorative Data Analysis] [] [2009-12-15 13:25:14] [2f674a53c3d7aaa1bcf80e66074d3c9b]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.5
104.1
101.9
102
100.7
99
96.5
101.8
100.5
103.3
102.3
100.4
103
99
104.8
104.5
104.8
103.8
106.3
105.2
108.2
106.2
103.9
104.9
106.2
107.9
106.9
110.3
109.8
108.3
110.9
109.8
109.3
109
107.9
108.4
107.2
109.5
109.9
108
114.7
115.6
107.6
115.9
111.8
110
109.2
108
105.6
103
99.6
97.9
97.6
96.2
97.9
94.5
95.4
94.4
96.3
95.1
Dataseries Y:
Download CSV
Histogram 
115.8
112.2
115.8
120.7
118.4
113.1
116.1
114.4
115.6
113.6
109.2
114.2
115
110.1
114.1
111.8
118.5
120.3
120.6
116.9
122.4
118.2
114.2
119.5
117.6
120.3
120.8
117
121.4
121
120.7
118.2
121.2
121.6
122.6
122.9
111.2
121.7
122.1
117.8
123.8
123.5
119.1
125.5
118.9
119.3
123
115.2
119.2
118.4
113.7
119.7
114.5
113
115.2
113.5
112.9
113.4
112.2
113.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56568&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56568&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56568&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c62.7532477303506
b0.522721572954807

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 62.7532477303506 \tabularnewline
b & 0.522721572954807 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56568&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]62.7532477303506[/C][/ROW]
[ROW][C]b[/C][C]0.522721572954807[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56568&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56568&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]
c62.7532477303506
b0.522721572954807






Descriptive Statistics about e[t]
# observations60
minimum-7.58900035110598
Q1-1.40380699202488
median0.316686311882429
mean-1.96041822821587e-17
Q31.822347895872
maximum5.77231027737373

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -7.58900035110598 \tabularnewline
Q1 & -1.40380699202488 \tabularnewline
median & 0.316686311882429 \tabularnewline
mean & -1.96041822821587e-17 \tabularnewline
Q3 & 1.822347895872 \tabularnewline
maximum & 5.77231027737373 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56568&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]-7.58900035110598[/C][/ROW]
[ROW][C]Q1[/C][C]-1.40380699202488[/C][/ROW]
[ROW][C]median[/C][C]0.316686311882429[/C][/ROW]
[ROW][C]mean[/C][C]-1.96041822821587e-17[/C][/ROW]
[ROW][C]Q3[/C][C]1.822347895872[/C][/ROW]
[ROW][C]maximum[/C][C]5.77231027737373[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56568&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56568&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]
# observations60
minimum-7.58900035110598
Q1-1.40380699202488
median0.316686311882429
mean-1.96041822821587e-17
Q31.822347895872
maximum5.77231027737373


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')