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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 09:10:24 -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/t1256742739nuw2nc00w6b8i0a.htm/, Retrieved Mon, 06 May 2024 07:28:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51393, Retrieved Mon, 06 May 2024 07:28:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordscvm
Estimated Impact130

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] [Workshop 4: Part ...] [2009-10-28 14:53:34] [03d5b865e91ca35b5a5d21b8d6da5aba]
-    D  [Bivariate Explorative Data Analysis] [Workshop 4: Part ...] [2009-10-28 14:57:24] [03d5b865e91ca35b5a5d21b8d6da5aba]
-    D      [Bivariate Explorative Data Analysis] [Workshop 4: Part ...] [2009-10-28 15:10:24] [a5ada8bd39e806b5b90f09589c89554a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-6,576671224
0,544388556
-5,24887234
-4,718885922
-5,117676676
-7,341712002
-7,504891342
-7,420326126
-7,584157658
-4,470489174
-5,220326126
-0,13134516
-10,56983698
-0,0998234
-5,313260926
-2,81381798
-6,218885922
-6,869606024
-3,788573408
-6,87434787
0,177255382
-4,367513628
-1,016793526
-0,418885922
-4,474578828
3,788600512
1,984089624
1,405149404
3,274605932
-1,548220148
2,451779852
2,435461918
9,70635865
5,666331486
6,66335594
6,814959192
-0,413165788
5,893342358
3,178464628
2,29148092
3,750570606
0,325978226
6,468097786
8,720027134
4,88441572
4,863912994
5,247921156
10,60459235
-3,674021774
7,874374974
5,8072418
6,682323324
3,904035296
0,475258124
2,188926608
-0,70070655
2,210543442
-2,155611444
-3,771929378
-0,544361452
-3,248451106
Dataseries Y:
Download CSV
Histogram 
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
116.8
115.7
99.4
94.3
91
93.2
103.1
94.1
91.8
102.7
82.6

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=51393&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=51393&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51393&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]
c104.377604949310
b1.00000003116751

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 104.377604949310 \tabularnewline
b & 1.00000003116751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51393&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]104.377604949310[/C][/ROW]
[ROW][C]b[/C][C]1.00000003116751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51393&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51393&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]
c104.377604949310
b1.00000003116751






Descriptive Statistics about e[t]
# observations61
minimum-18.5291537420644
Q1-6.0709474909913
median-0.297632355092036
mean-2.11977521146412e-16
Q35.2477890166282
maximum15.7309140592698

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -18.5291537420644 \tabularnewline
Q1 & -6.0709474909913 \tabularnewline
median & -0.297632355092036 \tabularnewline
mean & -2.11977521146412e-16 \tabularnewline
Q3 & 5.2477890166282 \tabularnewline
maximum & 15.7309140592698 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51393&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]-18.5291537420644[/C][/ROW]
[ROW][C]Q1[/C][C]-6.0709474909913[/C][/ROW]
[ROW][C]median[/C][C]-0.297632355092036[/C][/ROW]
[ROW][C]mean[/C][C]-2.11977521146412e-16[/C][/ROW]
[ROW][C]Q3[/C][C]5.2477890166282[/C][/ROW]
[ROW][C]maximum[/C][C]15.7309140592698[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51393&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51393&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-18.5291537420644
Q1-6.0709474909913
median-0.297632355092036
mean-2.11977521146412e-16
Q35.2477890166282
maximum15.7309140592698


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')