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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 computationTue, 03 Nov 2009 18:08:28 -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/04/t1257296942qoxv1vcz4abcytq.htm/, Retrieved Mon, 29 Apr 2024 08:47:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53476, Retrieved Mon, 29 Apr 2024 08:47:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact192
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [Y[t]= g + h Z[t] ...] [2009-10-28 17:00:14] [214e6e00abbde49700521a7ef1d30da2]
- RM D    [Bivariate Explorative Data Analysis] [WorkShop5 (SHW)] [2009-11-04 01:08:28] [2d9a0b3c2f25bb8f387fafb994d0d852] [Current]
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Dataseries X:
111632
106707
108827
108413
106249
104861
102382
100320
100228
117089
121523
114948
112831
107605
108928
101993
102850
99925
101536
99450
98305
110159
109483
106810
96279
91982
90276
90999
86622
83117
80367
77550
77443
92844
92175
84822
81632
78872
81485
80651
78192
76844
76335
71415
73899
86822
86371
83469
82662
82880
89406
95378
97657
100247
99180
97493
101628
114585
115669
111311
Dataseries Y:
282965
276610
277838
277051
277026
274960
270073
267063
264916
287182
291109
292223
288109
281400
282579
280113
280331
276759
275139
274275
271234
289725
290649
292223
278429
269749
265784
268957
264099
255121
253276
245980
235295
258479
260916
254586
250566
243345
247028
248464
244962
237003
237008
225477
226762
247857
248256
246892
245021
246186
255688
264242
268270
272969
273886
267353
271916
292633
295804
293222




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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=53476&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=53476&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53476&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c138124.290747780
b1.33798563205369

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 138124.290747780 \tabularnewline
b & 1.33798563205369 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53476&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]138124.290747780[/C][/ROW]
[ROW][C]b[/C][C]1.33798563205369[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53476&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53476&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]
c138124.290747780
b1.33798563205369







Descriptive Statistics about e[t]
# observations60
minimum-10238.0909709153
Q1-3886.28624195771
median-527.534999787705
mean-1.66829513167007e-14
Q33438.18047392428
maximum11484.7905837231

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -10238.0909709153 \tabularnewline
Q1 & -3886.28624195771 \tabularnewline
median & -527.534999787705 \tabularnewline
mean & -1.66829513167007e-14 \tabularnewline
Q3 & 3438.18047392428 \tabularnewline
maximum & 11484.7905837231 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53476&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]-10238.0909709153[/C][/ROW]
[ROW][C]Q1[/C][C]-3886.28624195771[/C][/ROW]
[ROW][C]median[/C][C]-527.534999787705[/C][/ROW]
[ROW][C]mean[/C][C]-1.66829513167007e-14[/C][/ROW]
[ROW][C]Q3[/C][C]3438.18047392428[/C][/ROW]
[ROW][C]maximum[/C][C]11484.7905837231[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53476&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53476&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]
# observations60
minimum-10238.0909709153
Q1-3886.28624195771
median-527.534999787705
mean-1.66829513167007e-14
Q33438.18047392428
maximum11484.7905837231



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')