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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 05:15:37 -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/t1257164207i9fjyns26d1672l.htm/, Retrieved Sat, 04 May 2024 03:35:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52515, Retrieved Sat, 04 May 2024 03:35:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [WS5-Bivariate EDA...] [2009-11-02 12:15:37] [0cc924834281808eda7297686c82928f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
286.1
307
358.1
341.8
378.8
375.2
295.6
362.7
409.6
336.8
389.1
389.3
355.9
542
648.4
452
582.4
506.5
555.5
530.4
609.4
543.9
616.2
634.6
541.7
549.8
627.6
797.4
689.8
1576.6
1572.1
1626.4
1972.4
1509.6
1584.9
1880
1324
1777.7
2172.4
1780.3
2134.9
1838.4
1557
1755.2
1702
1577.5
1485.9
2179.1
1740.9
1724.5
2328.1
1774.1
2224.2
1536.3
1521.2
2051.8
2483.1
1929.8
1808.6
2584.9
1997.9
1639.9
2379.1
1715
2750.9
1865.4
1647.4
2180.4
2593
2057.2
2635.8
2315.4
1863.6
2038
2235.8
2222.1
2636.9
2076.8
1935.5
2086.3
2470.9
1854.6
2041.3
2170.8
1905.5
2130.2
2791.2
2539.7
2661.3
1764.9
2176.9
2458.5
2179
2242.5
2089.6
2661.6
2112
2367.3
2543
2603.9
3146.7
1789.2
2114.8
2236.3
2288.1
2173.2
1877.7
2807.4
2357.4
2107.7
2856.8
2510.8
2875
2229.7
2055.1
2545.4
2775.1
2252.2
2091.7
2433
Dataseries Y:
Download CSV
Histogram 
423.4
404.1
500
472.6
496.1
562
434.8
538.2
577.6
518.1
625.2
561.2
523.3
536.1
607.3
637.3
606.9
652.9
617.2
670.4
729.9
677.2
710
844.3
748.2
653.9
742.6
854.2
808.4
1819
1936.5
1966.1
2083.1
1620.1
1527.6
1795
1685.1
1851.8
2164.4
1981.8
1726.5
2144.6
1758.2
1672.9
1837.3
1596.1
1446
1898.4
1964.1
1755.9
2255.3
1881.2
2117.9
1656.5
1544.1
2098.9
2133.3
1963.5
1801.2
2365.4
1936.5
1667.6
1983.5
2058.6
2448.3
1858.1
1625.4
2130.6
2515.7
2230.2
2086.9
2235
2100.2
2288.6
2490
2573.7
2543.8
2004.7
2390
2338.4
2724.5
2292.5
2386
2477.9
2337
2605.1
2560.8
2839.3
2407.2
2085.2
2735.6
2798.7
3053.2
2405
2471.9
2727.3
2790.7
2385.4
3206.6
2705.6
3518.4
1954.9
2584.3
2535.8
2685.9
2866
2236.6
2934.9
2668.6
2371.2
3165.9
2887.2
3112.2
2671.2
2432.6
2812.3
3095.7
2862.9
2607.3
2862.5

Tables (Output of Computation)





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=52515&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=52515&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52515&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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Model: Y[t] = c + b X[t] + e[t]
c144.612372140974
b1.00922004304304

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 144.612372140974 \tabularnewline
b & 1.00922004304304 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52515&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]144.612372140974[/C][/ROW]
[ROW][C]b[/C][C]1.00922004304304[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52515&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52515&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]
c144.612372140974
b1.00922004304304






Descriptive Statistics about e[t]
# observations120
minimum-717.814561593806
Q1-132.958715949945
median-2.83532130362549
mean6.13398221105399e-16
Q3144.691200143876
maximum709.497154068252

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 120 \tabularnewline
minimum & -717.814561593806 \tabularnewline
Q1 & -132.958715949945 \tabularnewline
median & -2.83532130362549 \tabularnewline
mean & 6.13398221105399e-16 \tabularnewline
Q3 & 144.691200143876 \tabularnewline
maximum & 709.497154068252 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52515&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]120[/C][/ROW]
[ROW][C]minimum[/C][C]-717.814561593806[/C][/ROW]
[ROW][C]Q1[/C][C]-132.958715949945[/C][/ROW]
[ROW][C]median[/C][C]-2.83532130362549[/C][/ROW]
[ROW][C]mean[/C][C]6.13398221105399e-16[/C][/ROW]
[ROW][C]Q3[/C][C]144.691200143876[/C][/ROW]
[ROW][C]maximum[/C][C]709.497154068252[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52515&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52515&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]
# observations120
minimum-717.814561593806
Q1-132.958715949945
median-2.83532130362549
mean6.13398221105399e-16
Q3144.691200143876
maximum709.497154068252


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')