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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 computationMon, 02 Nov 2009 02:10:28 -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/02/t1257153136qcdtrjdmo0h26x7.htm/, Retrieved Fri, 03 May 2024 21:31:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52455, Retrieved Fri, 03 May 2024 21:31:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordseda
Estimated Impact203

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Trivariate Scatterplots] [Workshop 5 - 1] [2009-10-28 20:27:13] [33b67a4fef396e07351e7d265eba4806]
- RMPD    [Bivariate Explorative Data Analysis] [eda] [2009-11-02 09:10:28] [950726a732ba3ca782ecb1a5307d0f6f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-4305.27
-644.87
-2540.32
-1512.92
-1307.62
-2973.97
-1802.42
340.42
-1597.07
-1779.22
-850.42
-3760.12
-3088.73
-316.68
-1314.97
990.38
123.02
-844.38
-609.18
2823.23
-1186.57
-53.58
745.18
-1426.87
-821.22
1824.68
1466.89
1846.63
-908.92
854.39
683.63
3226.03
287.23
1457.39
2568.19
1111.59
655.84
2277.64
3474.73
2698.27
165.27
1392.87
1633.02
1458.01
2264.26
-518.65
2353.89
-218.96
-1851.00
1250.15
1356.80
47.52
-1823.32
-2457.82
-1837.72
648.05
-894.10
-1050.84
1707.86
564.62
Dataseries Y:
Download CSV
Histogram 
-5170.50
-497.52
-1876.75
-1192.58
-2008.81
-2833.00
-1953.88
555.46
-1245.97
-1986.18
-629.35
-3235.95
-3666.73
-417.52
-877.69
437.22
-1671.54
-1294.54
-1190.94
2369.91
-1462.35
124.86
1882.04
-1498.67
-1616.48
2041.89
1984.77
1598.30
-1359.99
1549.07
860.58
3527.58
672.48
2057.94
3652.74
1591.34
639.43
2854.25
3826.51
2640.07
-1553.31
1778.22
1834.93
1420.19
2381.17
-149.45
2519.81
247.92
-2280.63
1897.08
1763.13
-715.00
-2669.55
-2334.49
-1822.31
421.48
-1048.11
-1109.28
1567.45
671.20

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52455&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52455&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52455&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c6.82671973686948e-05
b1.08192063714612

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 6.82671973686948e-05 \tabularnewline
b & 1.08192063714612 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52455&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]6.82671973686948e-05[/C][/ROW]
[ROW][C]b[/C][C]1.08192063714612[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52455&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52455&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]
c6.82671973686948e-05
b1.08192063714612






Descriptive Statistics about e[t]
# observations60
minimum-1804.63794504891
Q1-279.823814783198
median52.7079664224231
mean-1.29104481734939e-14
Q3385.621529411573
maximum1075.81431134426

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1804.63794504891 \tabularnewline
Q1 & -279.823814783198 \tabularnewline
median & 52.7079664224231 \tabularnewline
mean & -1.29104481734939e-14 \tabularnewline
Q3 & 385.621529411573 \tabularnewline
maximum & 1075.81431134426 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52455&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]-1804.63794504891[/C][/ROW]
[ROW][C]Q1[/C][C]-279.823814783198[/C][/ROW]
[ROW][C]median[/C][C]52.7079664224231[/C][/ROW]
[ROW][C]mean[/C][C]-1.29104481734939e-14[/C][/ROW]
[ROW][C]Q3[/C][C]385.621529411573[/C][/ROW]
[ROW][C]maximum[/C][C]1075.81431134426[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52455&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52455&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]
# observations60
minimum-1804.63794504891
Q1-279.823814783198
median52.7079664224231
mean-1.29104481734939e-14
Q3385.621529411573
maximum1075.81431134426


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')