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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, 03 Nov 2009 11:19:20 -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/03/t1257272405tq1ktt079kmz8c1.htm/, Retrieved Wed, 01 May 2024 18:46:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53292, Retrieved Wed, 01 May 2024 18:46:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsshwws5v1
Estimated Impact246

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] [] [2009-10-28 15:16:32] [5482608004c1d7bbf873930172393a2d]
-    D    [Bivariate Explorative Data Analysis] [] [2009-10-28 16:44:36] [5482608004c1d7bbf873930172393a2d]
- RMPD      [Trivariate Scatterplots] [] [2009-11-03 17:57:36] [5482608004c1d7bbf873930172393a2d]
- RMPD          [Bivariate Explorative Data Analysis] [] [2009-11-03 18:19:20] [efdfe680cd785c4af09f858b30f777ec] [Current]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5 Bivari...] [2009-11-04 10:59:12] [b6394cb5c2dcec6d17418d3cdf42d699]
-    D            [Bivariate Explorative Data Analysis] [workshop 5 bivari...] [2009-11-04 10:59:07] [af8eb90b4bf1bcfcc4325c143dbee260]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5, Bivar...] [2009-11-04 10:59:59] [aba88da643e3763d32ff92bd8f92a385]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6675
6539
6699
6962
6981
7024
6940
6774
6671
6965
6969
6822
6878
6691
6837
7018
7167
7076
7171
7093
6971
7142
7047
6999
6650
6475
6437
6639
6422
6272
6232
6003
5673
6050
5977
5796
5752
5609
5839
6069
6006
5809
5797
5502
5568
5864
5764
5615
5615
5681
5915
6334
6494
6620
6578
6495
6538
6737
6651
6530
Dataseries Y:
Download CSV
Histogram 
10898
11078
11157
11203
11425
11368
11118
11041
10837
11018
11035
11220
11486
11553
11626
11861
11951
11935
11717
11841
11701
11842
11818
12088
11876
11839
11582
11848
11741
11455
11154
10922
10556
10923
11001
10702
10805
10831
10925
11220
11188
10752
10771
10274
10261
10600
10596
10556
10716
10958
11273
11806
11922
12127
11985
11805
11901
12217
12344
12314

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=53292&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=53292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53292&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]
c6699.86124224317
b0.721464951130117

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 6699.86124224317 \tabularnewline
b & 0.721464951130117 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53292&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]6699.86124224317[/C][/ROW]
[ROW][C]b[/C][C]0.721464951130117[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53292&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]
c6699.86124224317
b0.721464951130117






Descriptive Statistics about e[t]
# observations60
minimum-706.864626864437
Q1-274.640931938505
median-10.8105891811746
mean1.65885823596075e-14
Q3254.970043454745
maximum902.972626877164

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -706.864626864437 \tabularnewline
Q1 & -274.640931938505 \tabularnewline
median & -10.8105891811746 \tabularnewline
mean & 1.65885823596075e-14 \tabularnewline
Q3 & 254.970043454745 \tabularnewline
maximum & 902.972626877164 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53292&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]-706.864626864437[/C][/ROW]
[ROW][C]Q1[/C][C]-274.640931938505[/C][/ROW]
[ROW][C]median[/C][C]-10.8105891811746[/C][/ROW]
[ROW][C]mean[/C][C]1.65885823596075e-14[/C][/ROW]
[ROW][C]Q3[/C][C]254.970043454745[/C][/ROW]
[ROW][C]maximum[/C][C]902.972626877164[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53292&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53292&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-706.864626864437
Q1-274.640931938505
median-10.8105891811746
mean1.65885823596075e-14
Q3254.970043454745
maximum902.972626877164


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')