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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 computationWed, 04 Nov 2009 13:31:30 -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/t1257366755ujuysie9g3c5d9a.htm/, Retrieved Mon, 29 Apr 2024 10:17:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53843, Retrieved Mon, 29 Apr 2024 10:17:27 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Trivariate Scatterplots] [ws5] [2009-10-28 16:48:35] [757146c69eaf0537be37c7b0c18216d8]
- RMPD    [Bivariate Explorative Data Analysis] [WS 5 Rev1] [2009-11-04 20:31:30] [51118f1042b56b16d340924f16263174] [Current]
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Dataseries X:
26066,71209
27284,35715
23468,63596
17569,48678
18386,10921
299,0147348
1196,834684
831,9365187
-3988,353605
-6242,308346
-9045,288792
12409,07439
16425,02089
16493,8995
12446,60937
6393,58982
7339,105254
5195,536321
6169,581581
2708,764707
1833,691654
2214,942671
-1293,026461
17420,33979
18655,65255
21141,35418
7080,51468
-509,8906811
-5219,817628
-923,8680513
-5615,093362
-14704,27649
-14859,29297
-23144,82279
-33640,81148
-9967,60572
-8086,521352
-13716,06766
-16412,98845
-22166,37118
-17782,91749
-15212,8496
-18459,12841
-25839,97615
-24311,76732
-35008,89387
-34024,08831
-11995,15005
-12507,85168
-13827,37843
-15209,17268
-14177,59243
-4631,119177
5468,32628
9396,261466
13906,25015
15156,79953
8490,379779
12008,25839
32191,57938
34828,90038
32046,77075
Dataseries Y:
52339,13387
52857,89946
54513,76898
44808,30593
43877,74819
-1539,166186
-780,3474886
426,6074601
-5853,923718
-6669,277075
-4528,220486
22960,40885
27396,36728
23116,35574
11275,82457
2849,767977
2846,127101
2354,726405
619,3730493
-5814,178915
-7996,277075
-5566,859073
5517,859176
25186,75525
31253,60975
25979,68364
6840,808357
-3741,200892
-10036,10273
-7205,87757
-13668,70552
-22139,15355
-21982,94341
-31948,23093
-33184,56927
1508,202093
6962,961913
-7956,115461
-15340,48383
-21813,16976
-19399,24713
-15443,27717
-20687,14669
-26276,4169
-24996,37881
-32345,51854
-26129,62824
5820,935265
8439,861371
-5734,159415
-14457,38806
-20251,3257
-15371,34649
-8126,818788
-7979,52202
-9449,183681
-9350,839573
-16076,77722
-10536,78875
17818,46067
23387,7101
9417,303638




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=53843&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=53843&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53843&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]
c-9.8282286248449e-08
b1.00828965373353

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -9.8282286248449e-08 \tabularnewline
b & 1.00828965373353 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53843&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-9.8282286248449e-08[/C][/ROW]
[ROW][C]b[/C][C]1.00828965373353[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53843&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53843&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-9.8282286248449e-08
b1.00828965373353







Descriptive Statistics about e[t]
# observations62
minimum-24637.5393073358
Q1-7234.85578616192
median-878.51911945212
mean4.99843893873819e-13
Q36737.6351651781
maximum30850.5861543915

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 62 \tabularnewline
minimum & -24637.5393073358 \tabularnewline
Q1 & -7234.85578616192 \tabularnewline
median & -878.51911945212 \tabularnewline
mean & 4.99843893873819e-13 \tabularnewline
Q3 & 6737.6351651781 \tabularnewline
maximum & 30850.5861543915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53843&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]62[/C][/ROW]
[ROW][C]minimum[/C][C]-24637.5393073358[/C][/ROW]
[ROW][C]Q1[/C][C]-7234.85578616192[/C][/ROW]
[ROW][C]median[/C][C]-878.51911945212[/C][/ROW]
[ROW][C]mean[/C][C]4.99843893873819e-13[/C][/ROW]
[ROW][C]Q3[/C][C]6737.6351651781[/C][/ROW]
[ROW][C]maximum[/C][C]30850.5861543915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53843&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53843&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]
# observations62
minimum-24637.5393073358
Q1-7234.85578616192
median-878.51911945212
mean4.99843893873819e-13
Q36737.6351651781
maximum30850.5861543915



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')