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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_edabi.wasp

Title produced by software

Bivariate Explorative Data Analysis

Date of computation

Tue, 27 Oct 2009 17:20:35 -0600

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/28/t1256685751ai5oi18zbm8v193.htm/, Retrieved Sun, 05 May 2024 23:22:00 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51308, Retrieved Sun, 05 May 2024 23:22:00 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

174

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]
-   PD  [Bivariate Data Series] [Reproduce: part 1] [2009-10-27 19:04:39] [f924a0adda9c1905a1ba8f1c751261ff]
- RMP     [Bivariate Explorative Data Analysis] [Bivariate EDA: Pa...] [2009-10-27 21:03:03] [f924a0adda9c1905a1ba8f1c751261ff]
-    D      [Bivariate Explorative Data Analysis] [Bivariate EDA: Pa...] [2009-10-27 22:45:19] [f924a0adda9c1905a1ba8f1c751261ff]
-    D          [Bivariate Explorative Data Analysis] [Bivariate data: P...] [2009-10-27 23:20:35] [ac86848d66148c9c4c9404e0c9a511eb] [Current]
- RMPD            [Harrell-Davis Quantiles] [Harell-Davis quan...] [2009-10-28 00:09:16] [f924a0adda9c1905a1ba8f1c751261ff] 
- RMPD            [Harrell-Davis Quantiles] [Harell-Davis quan...] [2009-10-28 00:11:39] [f924a0adda9c1905a1ba8f1c751261ff] 
- RMPD            [Harrell-Davis Quantiles] [Harell-Davis quan...] [2009-10-28 00:13:23] [f924a0adda9c1905a1ba8f1c751261ff] 
- RMPD              [Univariate Explorative Data Analysis] [Unvariate EDA: pa...] [2009-10-28 00:50:15] [f924a0adda9c1905a1ba8f1c751261ff] 

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Dataseries X:

Download CSV

Histogram

Boxplots

4.699297849
4.561636184
4.812672041
4.815350071
4.789822358
4.747797584
4.704110134
4.740487483
4.883029169
4.813484323
4.777609743
4.854527144
4.720639436
4.649474112
4.887110808
4.808274282
4.881285622
4.824707242
4.795459912
4.808927024
4.980313534
4.775503503
4.899703733
4.917788744
4.798843731
4.715189831
4.900969227
4.924714232
4.926238677
4.785573237
4.872828107
4.854215375
4.993489135
4.855306142
4.919250732
4.969466017
4.910004317
4.807947751
4.918739279
5.030699325
4.960814599
4.815917217
4.972379449
4.984633492
4.994573661
5.065817683
4.99314998
5.106248458
5.041099835
4.83786795
5.058536174
5.037926154
4.813890217
4.728007096
4.70456293
4.732419387
4.807621114
4.744323247
4.717158688
4.836599317

Dataseries Y:

Download CSV

Histogram

4.379523504
4.423648309
4.732683506
4.726502471
4.644390899
4.699570861
4.59511985
4.666265285
4.85903691
4.710430697
4.633757643
4.86753445
4.465908119
4.471638793
4.767289035
4.638604962
4.707726774
4.723841716
4.629862799
4.722063937
4.909709376
4.654912278
4.849683763
4.919980926
4.510859507
4.505349851
4.80729437
4.81462041
4.822697999
4.787491743
4.771531723
4.779123493
4.960744524
4.817050545
4.864452784
5.021245473
4.704110134
4.597138014
4.871373227
4.914124394
4.865224091
4.852030264
4.80073697
4.911183215
4.968423445
4.993828176
4.914124394
5.053694784
4.81462041
4.649187071
4.94021283
4.916324615
4.71939133
4.774912961
4.547541073
4.627909673
4.713127327
4.597138014
4.475061501
4.751864565

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51308&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51308&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51308&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Model: Y[t] = c + b X[t] + e[t]
c	-1.06746421760812
b	1.19773433786197

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -1.06746421760812 \tabularnewline
b & 1.19773433786197 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51308&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-1.06746421760812[/C][/ROW]
[ROW][C]b[/C][C]1.19773433786197[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51308&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51308&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c	-1.06746421760812
b	1.19773433786197

Descriptive Statistics about e[t]
# observations	60
minimum	-0.181522675980091
Q1	-0.04447953151127
median	0.00496467071608058
mean	-2.83425694480761e-18
Q3	0.0368742432603952
maximum	0.179480730073861

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.181522675980091 \tabularnewline
Q1 & -0.04447953151127 \tabularnewline
median & 0.00496467071608058 \tabularnewline
mean & -2.83425694480761e-18 \tabularnewline
Q3 & 0.0368742432603952 \tabularnewline
maximum & 0.179480730073861 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51308&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]-0.181522675980091[/C][/ROW]
[ROW][C]Q1[/C][C]-0.04447953151127[/C][/ROW]
[ROW][C]median[/C][C]0.00496467071608058[/C][/ROW]
[ROW][C]mean[/C][C]-2.83425694480761e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0368742432603952[/C][/ROW]
[ROW][C]maximum[/C][C]0.179480730073861[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51308&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51308&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations	60
minimum	-0.181522675980091
Q1	-0.04447953151127
median	0.00496467071608058
mean	-2.83425694480761e-18
Q3	0.0368742432603952
maximum	0.179480730073861

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

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PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

Figure 7

PNG link

Postscript link

PDF link

Figure 8

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code