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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 10:01:32 -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/t1256745813naeppc2p5fdk8s6.htm/, Retrieved Mon, 06 May 2024 09:40:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51484, Retrieved Mon, 06 May 2024 09:40:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90

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] [WS 5.6] [2009-10-28 16:01:32] [eba9f01697e64705b70041e6f338cb22] [Current]
- RMP     [Bivariate Kernel Density Estimation] [WS 5.7] [2009-11-03 20:57:11] [83058a88a37d754675a5cd22dab372fc]
- RMPD      [Kendall tau Rank Correlation] [WS 5.8] [2009-11-03 20:59:58] [83058a88a37d754675a5cd22dab372fc]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2,366550914
-2,784331965
11,17687724
-13,08690014
-3,702416453
13,53551828
9,502773534
2,81572168
0,60106142
-7,213545194
-6,130773624
2,389932679
0,66061216
-3,473042289
12,52091167
-20,54891176
-6,198884935
11,12267743
3,776128477
6,474416363
-0,522105764
-4,597921587
-3,270313182
11,43658892
-4,449553233
3,353978285
8,860826741
-21,06844013
-5,968440133
8,548788298
9,837605911
6,268638544
-4,941687785
-0,980478576
-1,983046747
10,82647717
-2,982939457
0,162753436
8,784262151
-16,11744996
-3,633875981
4,70491481
14,16269979
5,551463759
-7,174432532
1,213636315
2,506787859
-1,385400337
5,889613074
-2,333661401
4,590469131
-15,42590324
-10,26046739
8,260131619
10,20132965
-4,500489758
-8,71605972
-11,09283889
-8,636819669
1,076984534
Dataseries Y:
Download CSV
Histogram 
-0,3160103
-6,358448377
12,27737808
-13,46500204
-12,99867146
9,566650862
6,96160958
1,918725333
-1,176092864
-2,333737351
-2,125109214
12,64884125
3,499204854
-1,09186136
14,07900638
-17,46250601
-12,86891915
9,203882529
-0,057125727
3,885171829
-3,922249573
-3,325720513
-1,493786564
17,69419692
-4,072662393
5,117089915
11,37789969
-17,20456299
-12,32456299
7,746808873
10,81456927
6,481908112
-5,881480264
-1,385653811
-4,382207478
8,629503386
-5,827860058
0,624296976
10,00992495
-10,98777749
-9,827471845
4,766701702
13,85712327
5,457709958
-7,776521546
0,226735053
-2,474074724
-2,690066305
5,981727122
-3,608777006
4,190578344
-9,771942297
-15,91903344
10,5005696
18,89977568
-0,392274179
-2,763117308
-12,47978689
-8,764241479
1,111725495

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=51484&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=51484&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51484&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]
c8.88653429420784e-11
b0.972339865688065

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 8.88653429420784e-11 \tabularnewline
b & 0.972339865688065 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51484&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]8.88653429420784e-11[/C][/ROW]
[ROW][C]b[/C][C]0.972339865688065[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51484&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51484&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]
c8.88653429420784e-11
b0.972339865688065






Descriptive Statistics about e[t]
# observations60
minimum-9.39866434345756
Q1-1.9927129690318
median-0.106558681128845
mean4.20933587826656e-17
Q31.99959763449000
maximum10.3250144298088

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -9.39866434345756 \tabularnewline
Q1 & -1.9927129690318 \tabularnewline
median & -0.106558681128845 \tabularnewline
mean & 4.20933587826656e-17 \tabularnewline
Q3 & 1.99959763449000 \tabularnewline
maximum & 10.3250144298088 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51484&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]-9.39866434345756[/C][/ROW]
[ROW][C]Q1[/C][C]-1.9927129690318[/C][/ROW]
[ROW][C]median[/C][C]-0.106558681128845[/C][/ROW]
[ROW][C]mean[/C][C]4.20933587826656e-17[/C][/ROW]
[ROW][C]Q3[/C][C]1.99959763449000[/C][/ROW]
[ROW][C]maximum[/C][C]10.3250144298088[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51484&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51484&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-9.39866434345756
Q1-1.9927129690318
median-0.106558681128845
mean4.20933587826656e-17
Q31.99959763449000
maximum10.3250144298088


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')