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Description of Statistical Computation

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, 28 Oct 2009 13:55:21 -0600
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/Oct/28/t12567597927uojiwq9qo7mz2v.htm/, Retrieved Mon, 06 May 2024 00:07:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51793, Retrieved Mon, 06 May 2024 00:07:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94

Tree of Dependent Computations

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] [WS4P2.2] [2009-10-28 19:55:21] [dd4f17965cad1d38de7a1c062d32d75d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12,46302228
12,46479953
12,48443518
12,46968613
12,47567985
12,47106039
12,46048616
12,46129996
12,4777549
12,47448397
12,47681708
12,47262811
12,48207806
12,48760208
12,50761324
12,48921192
12,4920708
12,49270166
12,48175551
12,48226395
12,49782766
12,49333213
12,49493277
12,48420804
12,4911764
12,4956891
12,5139727
12,49598099
12,50290151
12,50259304
12,49353844
12,49598099
12,51137113
12,50443127
12,50722114
12,50121309
12,50561041
12,50986672
12,53201824
12,51916293
12,52564212
12,5299227
12,52254259
12,52273204
12,54085775
12,53419944
12,53574323
12,52500263
12,53235745
12,53824637
12,56200431
12,54494201
12,54732629
12,54657959
12,53640464
12,53939708
12,57463515
12,59287468
12,5972123
12,61895352
12,64064014
12,64772181
12,67021538
12,66293721
12,66513223
12,66636363
12,6602295
12,66383604
Dataseries Y:
Download CSV
Histogram 
269285
269829
270911
266844
271244
269907
271296
270157
271322
267179
264101
265518
269419
268714
272482
268351
268175
270674
272764
272599
270333
270846
270491
269160
274027
273784
276663
274525
271344
271115
270798
273911
273985
271917
273338
270601
273547
275363
281229
277793
279913
282500
280041
282166
290304
283519
287816
285226
287595
289741
289148
288301
290155
289648
288225
289351
294735
305333
309030
310215
321935
325734
320846
323023
319753
321753
320757
324479

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 5 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51793&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51793&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51793&T=0

As an alternative you can also use a QR Code:  
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 time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Model: Y[t] = c + b X[t] + e[t]
c-3409759.41899268
b294765.467288531

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -3409759.41899268 \tabularnewline
b & 294765.467288531 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51793&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-3409759.41899268[/C][/ROW]
[ROW][C]b[/C][C]294765.467288531[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51793&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51793&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Model: Y[t] = c + b X[t] + e[t]
c-3409759.41899268
b294765.467288531






Descriptive Statistics about e[t]
# observations68
minimum-4571.04236013091
Q1-2704.43852129982
median-107.915351393559
mean-8.7968847892358e-14
Q32951.39763057152
maximum8134.39339801283

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 68 \tabularnewline
minimum & -4571.04236013091 \tabularnewline
Q1 & -2704.43852129982 \tabularnewline
median & -107.915351393559 \tabularnewline
mean & -8.7968847892358e-14 \tabularnewline
Q3 & 2951.39763057152 \tabularnewline
maximum & 8134.39339801283 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51793&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]68[/C][/ROW]
[ROW][C]minimum[/C][C]-4571.04236013091[/C][/ROW]
[ROW][C]Q1[/C][C]-2704.43852129982[/C][/ROW]
[ROW][C]median[/C][C]-107.915351393559[/C][/ROW]
[ROW][C]mean[/C][C]-8.7968847892358e-14[/C][/ROW]
[ROW][C]Q3[/C][C]2951.39763057152[/C][/ROW]
[ROW][C]maximum[/C][C]8134.39339801283[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51793&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51793&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Descriptive Statistics about e[t]
# observations68
minimum-4571.04236013091
Q1-2704.43852129982
median-107.915351393559
mean-8.7968847892358e-14
Q32951.39763057152
maximum8134.39339801283


Figures (Output of Computation)

Input Parameters & R Code

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')