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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 10:19:13 -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/27/t12566604531qb952l5o4omzea.htm/, Retrieved Tue, 07 May 2024 05:43:04 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51038, Retrieved Tue, 07 May 2024 05:43:04 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

187

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] [Bivariate EDA par...] [2009-10-21 15:12:14] [2f74b736c031245eb7b9a6567f4b8492]
-    D      [Bivariate Explorative Data Analysis] [Ln] [2009-10-27 16:19:13] [eeda0e496238f8886c14dbbeff6ff613] [Current]
- RMP         [Kendall tau Rank Correlation] [Kendall tau Rank ...] [2009-10-28 15:55:47] [2f74b736c031245eb7b9a6567f4b8492] 
- RMPD        [Trivariate Scatterplots] [Trivariate Scatte...] [2009-10-28 16:11:45] [2f74b736c031245eb7b9a6567f4b8492] 
- RMPD        [Partial Correlation] [Partial Correlati...] [2009-10-28 16:14:27] [2f74b736c031245eb7b9a6567f4b8492] 
- RMP           [Trivariate Scatterplots] [WS 5 Review ] [2009-11-07 10:22:32] [83058a88a37d754675a5cd22dab372fc] 
-    D        [Bivariate Explorative Data Analysis] [Bivariate EDA WS5] [2009-10-28 16:21:27] [2f74b736c031245eb7b9a6567f4b8492] 
-    D        [Bivariate Explorative Data Analysis] [Bivariate EDA WS5] [2009-10-28 16:26:59] [2f74b736c031245eb7b9a6567f4b8492] 
-    D        [Bivariate Explorative Data Analysis] [Bivariate EDA WS5 ] [2009-10-28 16:30:59] [2f74b736c031245eb7b9a6567f4b8492] 

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Dataseries X:

Download CSV

Histogram

Boxplots

2,2300144
2,116255515
2,079441542
2,140066163
2,341805806
2,406945108
2,388762789
2,302585093
2,219203484
2,219203484
2,251291799
2,261763098
2,251291799
2,208274414
2,186051277
2,197224577
2,312535424
2,332143895
2,32238772
2,261763098
2,219203484
2,2300144
2,240709689
2,240709689
2,219203484
2,197224577
2,197224577
2,197224577
2,282382386
2,302585093
2,282382386
2,2300144
2,197224577
2,197224577
2,208274414
2,208274414
2,208274414
2,219203484
2,174751721
2,116255515
2,128231706
2,091864062
2,041220329
2,066862759
2,066862759
2,079441542
2,066862759
2,028148247
1,960094784
1,916922612
1,871802177
1,931521412
2,104134154
2,163323026
2,116255515
2,066862759
2,014903021
2,054123734
2,116255515
2,128231706
2,104134154

Dataseries Y:

Download CSV

Histogram

2,014903021
1,916922612
1,871802177
1,887069649
2,028148247
2,079441542
2,091864062
2,041220329
2,014903021
2,028148247
2,054123734
2,054123734
2,054123734
2,014903021
2,014903021
1,960094784
2,014903021
2,014903021
2,028148247
2,041220329
2,041220329
2,066862759
2,091864062
2,104134154
2,104134154
2,104134154
2,066862759
1,987874348
1,931521412
1,887069649
1,902107526
1,931521412
1,945910149
1,960094784
1,974081026
1,960094784
1,931521412
1,945910149
1,916922612
1,85629799
1,902107526
1,887069649
1,85629799
1,840549633
1,824549292
1,871802177
1,916922612
1,916922612
1,85629799
1,808288771
1,757857918
1,808288771
1,974081026
1,987874348
1,931521412
1,808288771
1,757857918
1,824549292
1,960094784
2,041220329
2,066862759

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51038&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51038&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51038&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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Model: Y[t] = c + b X[t] + e[t]
c	0.618717005134575
b	0.617238134308283

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.618717005134575 \tabularnewline
b & 0.617238134308283 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51038&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.618717005134575[/C][/ROW]
[ROW][C]b[/C][C]0.617238134308283[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51038&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51038&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	0.618717005134575
b	0.617238134308283

Descriptive Statistics about e[t]
# observations	61
minimum	-0.15289068302396
Q1	-0.0360206047423209
median	-0.00766715847265281
mean	2.07731358867612e-19
Q3	0.039360294008582
maximum	0.149393914316127

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -0.15289068302396 \tabularnewline
Q1 & -0.0360206047423209 \tabularnewline
median & -0.00766715847265281 \tabularnewline
mean & 2.07731358867612e-19 \tabularnewline
Q3 & 0.039360294008582 \tabularnewline
maximum & 0.149393914316127 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51038&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]-0.15289068302396[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0360206047423209[/C][/ROW]
[ROW][C]median[/C][C]-0.00766715847265281[/C][/ROW]
[ROW][C]mean[/C][C]2.07731358867612e-19[/C][/ROW]
[ROW][C]Q3[/C][C]0.039360294008582[/C][/ROW]
[ROW][C]maximum[/C][C]0.149393914316127[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51038&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51038&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	61
minimum	-0.15289068302396
Q1	-0.0360206047423209
median	-0.00766715847265281
mean	2.07731358867612e-19
Q3	0.039360294008582
maximum	0.149393914316127

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

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