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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 07:51:24 -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/t1257346340229yhylndg3rlnu.htm/, Retrieved Mon, 29 Apr 2024 09:29:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53606, Retrieved Mon, 29 Apr 2024 09:29:40 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWorkshop 5 Part 3 : X = f(Z)
Estimated Impact143
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [shw-ws5p3] [2009-11-04 14:51:24] [5b5bced41faf164488f2c271c918b21f] [Current]
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Dataseries X:
1178
2141
2238
2685
4341
5376
4478
6404
4617
3024
1897
2075
1351
2211
2453
3042
4765
4992
4601
6266
4812
3159
1916
2237
1595
2453
2226
3597
4706
4974
5756
5493
5004
3225
2006
2291
1588
2105
2191
3591
4668
4885
5822
5599
5340
3082
2010
2301
1514
1979
2480
3499
4676
5585
5610
5796
6199
3030
1930
2552
Dataseries Y:
2529
2196
3202
2718
2728
2354
2697
2651
2067
2641
2539
2294
2712
2314
3092
2677
2813
2668
2939
2617
2231
2481
2421
2408
2560
2100
3315
2801
2403
3024
2507
2980
2211
2471
2594
2452
2232
2373
3127
2802
2641
2787
2619
2806
2193
2323
2529
2412
2262
2154
3230
2295
2715
2733
2317
2730
1913
2390
2484
1960




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53606&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]6 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=53606&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53606&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 time6 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c2526.07506403858
b0.00875162631103777

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 2526.07506403858 \tabularnewline
b & 0.00875162631103777 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53606&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]2526.07506403858[/C][/ROW]
[ROW][C]b[/C][C]0.00875162631103777[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53606&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53606&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]
c2526.07506403858
b0.00875162631103777







Descriptive Statistics about e[t]
# observations60
minimum-667.326395540707
Q1-230.391909699974
median-5.53068949180524
mean3.0568140611346e-15
Q3165.057299437971
maximum769.443815793046

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -667.326395540707 \tabularnewline
Q1 & -230.391909699974 \tabularnewline
median & -5.53068949180524 \tabularnewline
mean & 3.0568140611346e-15 \tabularnewline
Q3 & 165.057299437971 \tabularnewline
maximum & 769.443815793046 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53606&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]-667.326395540707[/C][/ROW]
[ROW][C]Q1[/C][C]-230.391909699974[/C][/ROW]
[ROW][C]median[/C][C]-5.53068949180524[/C][/ROW]
[ROW][C]mean[/C][C]3.0568140611346e-15[/C][/ROW]
[ROW][C]Q3[/C][C]165.057299437971[/C][/ROW]
[ROW][C]maximum[/C][C]769.443815793046[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53606&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53606&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-667.326395540707
Q1-230.391909699974
median-5.53068949180524
mean3.0568140611346e-15
Q3165.057299437971
maximum769.443815793046



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')