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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 computationMon, 09 Nov 2009 03:46:55 -0700
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/Nov/09/t1257763752eoz8e3fmgcy2enl.htm/, Retrieved Tue, 16 Apr 2024 05:02:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54721, Retrieved Tue, 16 Apr 2024 05:02:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Partial Correlation] [WS5 (Y[t] - g - h...] [2009-11-04 16:27:45] [8733f8ed033058987ec00f5e71b74854]
- RMPD  [Bivariate Explorative Data Analysis] [WS5 (Y[t] - g - h...] [2009-11-04 17:33:33] [8733f8ed033058987ec00f5e71b74854]
-    D      [Bivariate Explorative Data Analysis] [Bivariate EDA - R...] [2009-11-09 10:46:55] [c6e373ff11c42d4585d53e9e88ed5606] [Current]
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Dataseries X:
13399273401
12059745121
10859701126
10005764694
9514380467
9090122822
8572186156
7723105089
5807865939
5209527792
10806609378
12461012345
13208372519
12128558905
10919352536
10176482175
8255073229
7865594107
7207607915
6605156735
4973755371
4662617610
9601525821
10970781285
11456743879
9937330605
8640802605
7618578980
7712820073
7298467535
6714146057
6233231652
4485522296
4319286391
8674260755
9646185232
9644496082
8487272842
7332664121
7186449444
7044907020
6741808938
6167959359
5787829024
4405100393
4204846098
8139113373
8959021072
9091401548
7885004717
7188505382
7234885924
7128689838
7084192626
6976496845
6486423182
4945888429
4780415692
8706455469
9845353820
10248106158
Dataseries Y:
13399312810
12059790361
10859741919
10005804318
9514417076
9090157995
8572220510
7723137889
5807899115
5209566834
10806655595
12461058857
13208416151
12128594650
10919384986
10176514004
8255106257
7865623363
7207634042
6605180508
4973779442
4662647930
9601565784
10970825642
11456779195
9937361218
8640828695
7618604532
7712842581
7298488037
6714167334
6233250865
4485541220
4319314309
8674299005
9646227837
9644528413
8487298626
7332687123
7186469492
7044926860
6741826421
6167977821
5787845097
4405118642
4204870000
8139145884
8959057996
9091425555
7885020695
7188514722
7234890535
7128689422
7084188570
6976487075
6486411791
4945877166
4780407920
8706456619
9845358652
10248100083




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54721&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54721&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54721&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c-3313.4291198844
b1.00000339997328

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -3313.4291198844 \tabularnewline
b & 1.00000339997328 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54721&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-3313.4291198844[/C][/ROW]
[ROW][C]b[/C][C]1.00000339997328[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54721&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54721&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-3313.4291198844
b1.00000339997328







Descriptive Statistics about e[t]
# observations61
minimum-37604.8580101972
Q1-2125.54114271183
median1762.51191373586
mean8.05534145762127e-13
Q38274.400699006
maximum24643.1738146999

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -37604.8580101972 \tabularnewline
Q1 & -2125.54114271183 \tabularnewline
median & 1762.51191373586 \tabularnewline
mean & 8.05534145762127e-13 \tabularnewline
Q3 & 8274.400699006 \tabularnewline
maximum & 24643.1738146999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54721&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]-37604.8580101972[/C][/ROW]
[ROW][C]Q1[/C][C]-2125.54114271183[/C][/ROW]
[ROW][C]median[/C][C]1762.51191373586[/C][/ROW]
[ROW][C]mean[/C][C]8.05534145762127e-13[/C][/ROW]
[ROW][C]Q3[/C][C]8274.400699006[/C][/ROW]
[ROW][C]maximum[/C][C]24643.1738146999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54721&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54721&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]
# observations61
minimum-37604.8580101972
Q1-2125.54114271183
median1762.51191373586
mean8.05534145762127e-13
Q38274.400699006
maximum24643.1738146999



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')