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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 06:02:20 -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/t1257771778i02e95rkszups4d.htm/, Retrieved Tue, 23 Apr 2024 20:45:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54796, Retrieved Tue, 23 Apr 2024 20:45:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155
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 13:02:20] [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:
2.28
2.26
2.71
2.77
2.77
2.64
2.56
2.07
2.32
2.16
2.23
2.40
2.84
2.77
2.93
2.91
2.69
2.38
2.58
3.19
2.82
2.72
2.53
2.70
2.42
2.50
2.31
2.41
2.56
2.76
2.71
2.44
2.46
2.12
1.99
1.86
1.88
1.82
1.74
1.71
1.38
1.27
1.19
1.28
1.19
1.22
1.47
1.46
1.96
1.88
2.03
2.04
1.90
1.80
1.92
1.92
1.97
2.46
2.36
2.53
2.31
1.98
1.46
1.26
1.58
1.74
1.89
1.85
1.62
1.30
1.42
1.15
0.42
0.74
1.02
1.51
1.86
1.59
1.03
0.44
0.82
0.86
0.58
0.59
0.95
0.98
1.23
1.17
0.84
0.74
0.65
0.91
1.19
1.30
1.53
1.94
1.79
1.95
2.26
2.04
2.16
2.75
2.79
2.88
3.36
2.97
3.10
2.49
2.20
2.25
2.09
2.79
3.14
2.93
2.65
2.67
2.26
2.35
2.13
2.18
2.90
2.63
2.67
1.81
1.33
0.88
1.28
1.26
1.26
1.29
1.10
1.37
1.21
1.74
1.76
1.48
1.04
1.62
1.49
1.79
1.80
1.58
1.86
1.74
1.59
1.26
1.13
1.92
2.61
2.26
2.41
2.26
2.03
2.86
2.55
2.27
2.26
2.57
3.07
2.76
2.51
2.87
3.14
3.11
3.16
2.47
2.57
2.89
2.63
2.38
1.69
1.96
2.19
1.87
1.6
1.63
1.22
1.21
1.49
1.64




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54796&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]4 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=54796&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54796&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 time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c2.32577756822958
b-0.000145427094207378

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 2.32577756822958 \tabularnewline
b & -0.000145427094207378 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54796&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]2.32577756822958[/C][/ROW]
[ROW][C]b[/C][C]-0.000145427094207378[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54796&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54796&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]
c2.32577756822958
b-0.000145427094207378







Descriptive Statistics about e[t]
# observations180
minimum-1.54153068818119
Q1-0.550108544042779
median-0.0229089040319724
mean-6.00482361558395e-18
Q30.501076065718851
maximum1.47529262860480

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 180 \tabularnewline
minimum & -1.54153068818119 \tabularnewline
Q1 & -0.550108544042779 \tabularnewline
median & -0.0229089040319724 \tabularnewline
mean & -6.00482361558395e-18 \tabularnewline
Q3 & 0.501076065718851 \tabularnewline
maximum & 1.47529262860480 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54796&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]-1.54153068818119[/C][/ROW]
[ROW][C]Q1[/C][C]-0.550108544042779[/C][/ROW]
[ROW][C]median[/C][C]-0.0229089040319724[/C][/ROW]
[ROW][C]mean[/C][C]-6.00482361558395e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.501076065718851[/C][/ROW]
[ROW][C]maximum[/C][C]1.47529262860480[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54796&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54796&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-1.54153068818119
Q1-0.550108544042779
median-0.0229089040319724
mean-6.00482361558395e-18
Q30.501076065718851
maximum1.47529262860480



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')