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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 computationWed, 28 Oct 2009 11:34:19 -0600
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/Oct/28/t1256751376zqejfixt8f7yrwo.htm/, Retrieved Sun, 05 May 2024 23:48:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51634, Retrieved Sun, 05 May 2024 23:48:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHWWS4V8
Estimated Impact85

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD    [Bivariate Explorative Data Analysis] [] [2009-10-28 17:34:19] [71596e6a53ccce532e52aaf6113616ef] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6,76
6,25
6,25
2,56
1,96
0,64
1,21
1,69
1,44
1,69
1,21
1,69
1,44
2,56
2,89
2,25
0,81
2,25
1,96
2,56
2,89
1,96
3,24
2,89
1,96
1,44
1
2,89
5,76
4
4,41
4
3,24
7,29
5,29
3,61
4
5,29
7,84
5,76
5,29
7,29
7,29
8,41
9
4,84
5,29
7,84
7,84
7,84
4,84
6,76
7,84
6,25
5,76
5,29
3,61
2,89
4
4,41
Dataseries Y:
Download CSV
Histogram 
63756,25
63051,21
65076,01
66718,89
65178,09
68173,21
64414,44
63958,41
64465,21
65280,25
68644
69063,84
69326,89
68906,25
72468,64
73332,64
75130,81
74529
71449,29
71342,41
71931,24
73008,04
73712,25
78961
78456,01
79242,25
81738,81
83984,04
85790,41
84797,44
85147,24
83984,04
85556,25
84274,09
88506,25
94556,25
92842,09
92781,16
96534,49
96534,49
99666,49
99036,09
97468,84
97843,84
98784,49
102208,09
102336,01
108570,25
106863,61
108702,09
112694,49
113703,84
115396,09
114446,89
115056,64
117306,25
117100,84
114446,89
114921
119646,81

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=51634&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=51634&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51634&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]
c67665.4785869968
b4665.18597024856

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 67665.4785869968 \tabularnewline
b & 4665.18597024856 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51634&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]67665.4785869968[/C][/ROW]
[ROW][C]b[/C][C]4665.18597024856[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51634&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51634&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]
c67665.4785869968
b4665.18597024856






Descriptive Statistics about e[t]
# observations60
minimum-35445.8857458772
Q1-8783.88323447079
median-2558.29095903236
mean4.08680496851351e-13
Q36717.44505660377
maximum33299.0239589848

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -35445.8857458772 \tabularnewline
Q1 & -8783.88323447079 \tabularnewline
median & -2558.29095903236 \tabularnewline
mean & 4.08680496851351e-13 \tabularnewline
Q3 & 6717.44505660377 \tabularnewline
maximum & 33299.0239589848 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51634&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]-35445.8857458772[/C][/ROW]
[ROW][C]Q1[/C][C]-8783.88323447079[/C][/ROW]
[ROW][C]median[/C][C]-2558.29095903236[/C][/ROW]
[ROW][C]mean[/C][C]4.08680496851351e-13[/C][/ROW]
[ROW][C]Q3[/C][C]6717.44505660377[/C][/ROW]
[ROW][C]maximum[/C][C]33299.0239589848[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51634&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51634&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-35445.8857458772
Q1-8783.88323447079
median-2558.29095903236
mean4.08680496851351e-13
Q36717.44505660377
maximum33299.0239589848


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')