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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 computationMon, 09 Nov 2009 05:47:07 -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/09/t1257770864dku908ukws9zwmo.htm/, Retrieved Fri, 29 Mar 2024 13:12:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54777, Retrieved Fri, 29 Mar 2024 13:12:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [workshop 6] [2009-11-09 12:47:07] [e81f30a5c3daacfe71a556c99a478849] [Current]
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Dataseries X:
1145.11
1176.86
1206.41
1192.72
1214.82
1199.07
1157.47
1100.10
1095.63
1105.63
1137.79
1124.72
1152.60
1211.85
1239.62
1244.13
1198.42
1227.99
1304.92
1340.26
1307.32
1356.51
1383.29
1437.87
1494.56
1521.42
1498.76
1488.75
1524.62
1439.27
1423.11
1466.85
1425.83
1363.45
1389.18
1395.89
1368.43
1349.03
1299.88
1365.41
1451.04
1433.75
1464.65
1475.57
1571.16
1429.12
1452.46
1538.09
1631.59
1665.50
1690.60
1711.74
1734.10
1748.09
1703.45
1745.74
1751.01
1795.65
1852.13
1877.10
1989.31
2097.76
2154.87
2152.18
2250.27
2346.90
2525.56
2409.36
2394.36
2401.33
2354.32
2450.41
2504.67
2661.39
2880.40
3064.42
3141.12
3327.70
3564.95
3403.13
3149.90
3006.84
3230.66
3361.13
3484.74
3411.13
3288.18
3280.37
3173.95
3165.26
3092.71
3053.05
3181.96
2999.93
3249.57
3210.52
3030.29
2803.47
2767.63
2882.60
2863.36
2897.06
3012.61
3142.95
3032.93
3045.78
3110.52
3013.24
2987.10
2995.55
2833.18
2848.96
2794.83
2845.26
2915.02
2892.63
2604.42
2641.65
2659.81
2638.53
2720.25
2745.88
2735.70
2811.70
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042.00
1995.37
1946.81
1765.90
1635.25
1833.42
1910.43
1959.67
1969.60
2061.41
2093.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.60
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.10
4138.52
4199.75
4290.89
Dataseries Y:
6.9
6.8
6.7
6.6
6.5
6.5
7.0
7.5
7.6
7.6
7.6
7.8
8.0
8.0
8.0
7.9
7.9
8.0
8.5
9.2
9.4
9.5
9.5
9.6
9.7
9.7
9.6
9.5
9.4
9.3
9.6
10.2
10.2
10.1
9.9
9.8
9.8
9.7
9.5
9.3
9.1
9.0
9.5
10.0
10.2
10.1
10.0
9.9
10.0
9.9
9.7
9.5
9.2
9.0
9.3
9.8
9.8
9.6
9.4
9.3
9.2
9.2
9.0
8.8
8.7
8.7
9.1
9.7
9.8
9.6
9.4
9.4
9.5
9.4
9.3
9.2
9.0
8.9
9.2
9.8
9.9
9.6
9.2
9.1
9.1
9.0
8.9
8.7
8.5
8.3
8.5
8.7
8.4
8.1
7.8
7.7
7.5
7.2
6.8
6.7
6.4
6.3
6.8
7.3
7.1
7.0
6.8
6.6
6.3
6.1
6.1
6.3
6.3
6.0
6.2
6.4
6.8
7.5
7.5
7.6
7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8.0
8.1
8.2
8.3
8.2
8.0
7.9
7.6
7.6
8.3
8.4
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.0
8.2
8.1
8.1
8.0
7.9
7.9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54777&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54777&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54777&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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c9.10022548946042
b-0.000297149059182348

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 9.10022548946042 \tabularnewline
b & -0.000297149059182348 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54777&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]9.10022548946042[/C][/ROW]
[ROW][C]b[/C][C]-0.000297149059182348[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54777&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54777&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]
c9.10022548946042
b-0.000297149059182348







Descriptive Statistics about e[t]
# observations180
minimum-2.25475915733125
Q1-0.833413868051032
median0.291491035098549
mean3.84413668191015e-18
Q30.836784203152581
maximum1.73576433205806

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 180 \tabularnewline
minimum & -2.25475915733125 \tabularnewline
Q1 & -0.833413868051032 \tabularnewline
median & 0.291491035098549 \tabularnewline
mean & 3.84413668191015e-18 \tabularnewline
Q3 & 0.836784203152581 \tabularnewline
maximum & 1.73576433205806 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54777&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]180[/C][/ROW]
[ROW][C]minimum[/C][C]-2.25475915733125[/C][/ROW]
[ROW][C]Q1[/C][C]-0.833413868051032[/C][/ROW]
[ROW][C]median[/C][C]0.291491035098549[/C][/ROW]
[ROW][C]mean[/C][C]3.84413668191015e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.836784203152581[/C][/ROW]
[ROW][C]maximum[/C][C]1.73576433205806[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54777&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54777&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]
# observations180
minimum-2.25475915733125
Q1-0.833413868051032
median0.291491035098549
mean3.84413668191015e-18
Q30.836784203152581
maximum1.73576433205806



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')