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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 computationFri, 30 Oct 2009 08:20:32 -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/30/t1256912548bx5ijgz2k3clzpk.htm/, Retrieved Mon, 29 Apr 2024 03:17:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52115, Retrieved Mon, 29 Apr 2024 03:17:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Gemiddelde renden...] [2008-10-13 19:42:56] [86c69698417c3ad89592e76776a2c65b]
-   PD  [Univariate Data Series] [Bouwvergunningen ...] [2009-10-11 20:54:46] [5c968c05ca472afa314d272082b56b09]
- RMPD      [Bivariate Explorative Data Analysis] [WS5, zuivering van Z] [2009-10-30 14:20:32] [b8ce264f75295a954feffaf60221d1b0] [Current]
-  M D        [Bivariate Explorative Data Analysis] [Workshop 5 Bivari...] [2009-11-04 15:54:37] [f924a0adda9c1905a1ba8f1c751261ff]
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Dataseries X:
-1813.130876
-2101.143684
-2058.137618
-2267.706355
-2101.007565
-2368.612017
-2303.984657
-1874.249475
-2271.114711
-1868.681416
-1534.283836
-1863.492063
-1977.995434
-1826.136941
-2331.23331
-2358.156491
-2133.800693
-2364.103257
-2322.073607
-1858.604597
-2322.26296
-2088.771043
-1712.609985
-2362.32226
-2426.8728
-2251.227245
-2975.922001
-2422.926035
-2397.760266
-3206.088446
-2168.055411
-2180.274414
-2151.108645
-2596.63089
-2038.688158
-2154.002177
-2272.937488
-2554.003531
-2789.306095
-2918.99882
-3094.833728
-3074.804078
-2330.919969
-2594.956362
-2631.636955
-2755.382914
-2500.914581
-2961.141004
-3669.374169
-2764.087092
-3128.461087
-2273.937488
-2966.51971
-2613.09248
-2491.0507
-2299.564848
-2404.47051
-2541.405821
-2049.498805
-2315.724551
-2398.168622
-2314.967138
-2649.471187
-2370.594497
-2247.765654
-2880.986689
-2478.96175
-2156.025761
-1885.391659
-2651.388302
-2101.58169
-2090.634924
Dataseries Y:
-1700.130876
-1990.143684
-1951.137618
-2164.706355
-2003.007565
-2269.612017
-2166.984657
-1727.249475
-2124.114711
-1729.681416
-1404.283836
-1735.492063
-1850.995434
-1703.136941
-2213.23331
-2245.156491
-2024.800693
-2253.103257
-2172.073607
-1699.604597
-2164.26296
-1941.771043
-1575.609985
-2225.32226
-2290.8728
-2118.227245
-2850.922001
-2302.926035
-2283.760266
-3090.088446
-2015.055411
-2018.274414
-1990.108645
-2447.63089
-1899.688158
-2020.002177
-2142.937488
-2428.003531
-2667.306095
-2801.99882
-2982.833728
-2961.804078
-2181.919969
-2437.956362
-2474.636955
-2608.382914
-2364.914581
-2829.141004
-3544.374169
-2641.087092
-3011.461087
-2159.937488
-2855.51971
-2501.09248
-2347.0507
-2149.564848
-2255.47051
-2406.405821
-1926.498805
-2200.724551
-2281.168622
-2203.967138
-2544.471187
-2268.594497
-2152.765654
-2787.986689
-2354.96175
-2025.025761
-1761.391659
-2536.388302
-1995.58169
-1985.634924




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time17 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 & 17 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52115&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]17 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=52115&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52115&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 time17 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c144.728481651060
b1.00751097461082

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 144.728481651060 \tabularnewline
b & 1.00751097461082 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52115&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]144.728481651060[/C][/ROW]
[ROW][C]b[/C][C]1.00751097461082[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52115&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52115&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]
c144.728481651060
b1.00751097461082







Descriptive Statistics about e[t]
# observations72
minimum-32.8455708927942
Q1-12.8146264722410
median-2.4204514820107
mean-2.43762379108996e-15
Q310.0251017174449
maximum33.647504117113

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 72 \tabularnewline
minimum & -32.8455708927942 \tabularnewline
Q1 & -12.8146264722410 \tabularnewline
median & -2.4204514820107 \tabularnewline
mean & -2.43762379108996e-15 \tabularnewline
Q3 & 10.0251017174449 \tabularnewline
maximum & 33.647504117113 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52115&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]72[/C][/ROW]
[ROW][C]minimum[/C][C]-32.8455708927942[/C][/ROW]
[ROW][C]Q1[/C][C]-12.8146264722410[/C][/ROW]
[ROW][C]median[/C][C]-2.4204514820107[/C][/ROW]
[ROW][C]mean[/C][C]-2.43762379108996e-15[/C][/ROW]
[ROW][C]Q3[/C][C]10.0251017174449[/C][/ROW]
[ROW][C]maximum[/C][C]33.647504117113[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52115&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52115&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]
# observations72
minimum-32.8455708927942
Q1-12.8146264722410
median-2.4204514820107
mean-2.43762379108996e-15
Q310.0251017174449
maximum33.647504117113



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')