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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 computationTue, 27 Oct 2009 08:45:44 -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/27/t12566550002gvcxmwzfhm1fsi.htm/, Retrieved Tue, 07 May 2024 06:40:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50982, Retrieved Tue, 07 May 2024 06:40:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
-   PD  [Bivariate Data Series] [Reproduction Part 1] [2009-10-26 18:51:43] [96e597a9107bfe8c07649cce3d4f6fec]
- RMPD    [Bivariate Explorative Data Analysis] [JJ Workshop 4, De...] [2009-10-26 19:42:48] [96e597a9107bfe8c07649cce3d4f6fec]
-    D      [Bivariate Explorative Data Analysis] [JJ Workshop 4, de...] [2009-10-27 14:23:10] [96e597a9107bfe8c07649cce3d4f6fec]
-    D          [Bivariate Explorative Data Analysis] [JJ Workshop 4, de...] [2009-10-27 14:45:44] [e31f2fa83f4a5291b9a51009566cf69b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
85
96.1
113.6
116.8
102.7
106.8
124.2
117.8
121.6
117.9
111.4
109.8
92.6
104.9
120.3
109.1
93.1
87.3
106.9
102.1
102.4
113.3
100.6
103.5
93.7
102.6
108.1
105.9
87.1
81.8
103.8
95.8
92.7
101.1
88
92.8
89.7
95.6
95.2
96.9
79.2
73.5
99.7
87.8
91.3
93.9
90
89.8
88.9
104.2
110.8
110.5
87.1
89.2
96.5
95.4
101
107.6
93.8
93.8
Dataseries Y:
Download CSV
Histogram 
8892.49
9880.36
13386.49
13642.24
9960.04
9216
13432.81
11902.81
13759.29
12056.04
12723.84
12254.49
10000
12836.89
14981.76
12656.25
10857.64
8556.25
13735.84
11946.49
11257.21
14113.44
11088.09
11236
10404
12746.41
13572.25
13179.04
10100.25
7293.16
13133.16
12078.01
10140.49
13340.25
10140.49
9801
10465.29
11837.44
11214.81
12814.24
9158.49
6544.81
12973.21
9623.61
10567.84
10962.09
9196.81
8949.16
10322.56
10795.21
12166.09
13018.81
9370.24
7638.76
12409.96
9486.76
10588.41
12701.29
9409
9044.01

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=50982&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=50982&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50982&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]
c-2547.89929546634
b137.989844965015

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -2547.89929546634 \tabularnewline
b & 137.989844965015 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50982&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-2547.89929546634[/C][/ROW]
[ROW][C]b[/C][C]137.989844965015[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50982&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50982&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]
c-2547.89929546634
b137.989844965015






Descriptive Statistics about e[t]
# observations60
minimum-2973.41614679729
Q1-808.63998591806
median39.1258648912016
mean-2.58515431283968e-14
Q3671.023545137633
maximum1990.92331835636

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -2973.41614679729 \tabularnewline
Q1 & -808.63998591806 \tabularnewline
median & 39.1258648912016 \tabularnewline
mean & -2.58515431283968e-14 \tabularnewline
Q3 & 671.023545137633 \tabularnewline
maximum & 1990.92331835636 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50982&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]-2973.41614679729[/C][/ROW]
[ROW][C]Q1[/C][C]-808.63998591806[/C][/ROW]
[ROW][C]median[/C][C]39.1258648912016[/C][/ROW]
[ROW][C]mean[/C][C]-2.58515431283968e-14[/C][/ROW]
[ROW][C]Q3[/C][C]671.023545137633[/C][/ROW]
[ROW][C]maximum[/C][C]1990.92331835636[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50982&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50982&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-2973.41614679729
Q1-808.63998591806
median39.1258648912016
mean-2.58515431283968e-14
Q3671.023545137633
maximum1990.92331835636


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')