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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 computationFri, 23 Oct 2009 03:35:21 -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/23/t1256290579t31i6vfnhmbpjou.htm/, Retrieved Thu, 02 May 2024 11:07:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49864, Retrieved Thu, 02 May 2024 11:07:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186

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]
- RMPD  [Bivariate Explorative Data Analysis] [WS4 Part2 Vraag1] [2009-10-23 09:15:48] [42ad1186d39724f834063794eac7cea3]
-   PD      [Bivariate Explorative Data Analysis] [WS4 Part2 Vraag3 TVD] [2009-10-23 09:35:21] [37de18e38c1490dd77c2b362ed87f3bb] [Current]
-   P         [Bivariate Explorative Data Analysis] [BDM 6] [2009-10-27 14:59:24] [f5d341d4bbba73282fc6e80153a6d315]
-   P         [Bivariate Explorative Data Analysis] [TG 6] [2009-10-27 15:07:56] [a21bac9c8d3d56fdec8be4e719e2c7ed]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7974.49
8154.09
8299.21
8118.01
7516.89
7242.01
6955.56
6724
6464.16
6707.61
8798.44
8987.04
8519.29
7656.25
6922.24
6724
6448.09
6691.24
7242.01
7089.64
7123.36
7140.25
8704.89
8686.24
10060.09
12409.96
13202.01
11990.25
12078.01
11193.64
12276.64
11837.44
13479.21
12056.04
12950.44
12950.44
13782.76
14280.25
15030.76
14568.49
14161
15901.21
17929.21
19071.61
19712.16
21963.24
21963.24
24304.81
29275.21
29549.61
35645.44
46182.01
52212.25
48400
50805.16
48708.49
48268.09
53870.41
49952.25
47917.21
Dataseries Y:
Download CSV
Histogram 
10261.69
11299.69
8836
10567.84
10404
11046.01
8537.76
6625.96
11193.64
14472.09
10140.49
7885.44
8892.49
9980.01
10691.56
10670.89
9761.44
10857.64
8317.44
5580.09
11772.25
13110.25
9389.61
8028.16
9428.41
10060.09
15030.76
13317.16
11881
16666.81
10567.84
9254.44
16307.29
16615.21
16002.25
14352.04
12814.24
13018.81
17982.81
16900
14835.24
17450.41
11088.09
10609
13712.41
15951.69
19071.61
14280.25
19044
18360.25
31897.96
26308.84
31293.61
41984.01
17476.84
20306.25
26994.49
30590.01
30765.16
20449

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=49864&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=49864&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49864&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]
c7371.37421949468
b0.415152314774139

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 7371.37421949468 \tabularnewline
b & 0.415152314774139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49864&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]7371.37421949468[/C][/ROW]
[ROW][C]b[/C][C]0.415152314774139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49864&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49864&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]
c7371.37421949468
b0.415152314774139






Descriptive Statistics about e[t]
# observations60
minimum-10986.4139959652
Q1-1989.52964215024
median-280.061000009591
mean8.5805436829863e-14
Q31747.83067020478
maximum14519.2637454370

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -10986.4139959652 \tabularnewline
Q1 & -1989.52964215024 \tabularnewline
median & -280.061000009591 \tabularnewline
mean & 8.5805436829863e-14 \tabularnewline
Q3 & 1747.83067020478 \tabularnewline
maximum & 14519.2637454370 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49864&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]-10986.4139959652[/C][/ROW]
[ROW][C]Q1[/C][C]-1989.52964215024[/C][/ROW]
[ROW][C]median[/C][C]-280.061000009591[/C][/ROW]
[ROW][C]mean[/C][C]8.5805436829863e-14[/C][/ROW]
[ROW][C]Q3[/C][C]1747.83067020478[/C][/ROW]
[ROW][C]maximum[/C][C]14519.2637454370[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49864&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49864&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-10986.4139959652
Q1-1989.52964215024
median-280.061000009591
mean8.5805436829863e-14
Q31747.83067020478
maximum14519.2637454370


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = colombia ; par2 = www.ico.org ; par3 = Prices paid to growers in exporting Member countries in US cents per lb (Arabica, 1977/1 - 2006/12) ; par4 = usa ; par5 = www.ico.org ; par6 = Retail prices in importing Member countries in US cents per lb (Arabica, 1977/1 - 2006/12) ;
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')