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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 computationSun, 29 Nov 2009 05:19:29 -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/29/t1259497306gsxd2y2haspie7g.htm/, Retrieved Fri, 26 Apr 2024 05:13:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61565, Retrieved Fri, 26 Apr 2024 05:13:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Totaal levensmidd...] [2009-11-29 09:24:25] [757146c69eaf0537be37c7b0c18216d8]
- RM D    [Bivariate Explorative Data Analysis] [Xt = prijsindex G...] [2009-11-29 12:19:29] [a931a0a30926b49d162330b43e89b999] [Current]
-    D      [Bivariate Explorative Data Analysis] [Xt = prijsindex g...] [2009-12-21 14:08:07] [12f02da0296cb21dc23d82ae014a8b71]
-    D      [Bivariate Explorative Data Analysis] [xt = prijsindex g...] [2009-12-21 14:10:57] [12f02da0296cb21dc23d82ae014a8b71]
-           [Bivariate Explorative Data Analysis] [Bivariate EDA Xt ...] [2009-12-21 14:29:07] [74be16979710d4c4e7c6647856088456]
-           [Bivariate Explorative Data Analysis] [bivariate eda Xt ...] [2009-12-21 14:39:37] [03c44f58d7d4de05d4cfabfda8c46d2c]
-           [Bivariate Explorative Data Analysis] [bivariate eda ] [2009-12-21 14:42:23] [03c44f58d7d4de05d4cfabfda8c46d2c]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
108,2
108,8
110,2
109,5
109,5
116
111,2
112,1
114
119,1
114,1
115,1
115,4
110,8
116
119,2
126,5
127,8
131,3
140,3
137,3
143
134,5
139,9
159,3
170,4
175
175,8
180,9
180,3
169,6
172,3
184,8
177,7
184,6
211,4
215,3
215,9
244,7
259,3
289
310,9
321
315,1
333,2
314,1
284,7
273,9
216
196,4
190,9
206,4
196,3
199,5
198,9
214,4
214,2
187,6
180,6
172,2
187,2
Dataseries Y:
Download CSV
Histogram 
108,5
112,3
116,6
115,5
120,1
132,9
128,1
129,3
132,5
131
124,9
120,8
122
122,1
127,4
135,2
137,3
135
136
138,4
134,7
138,4
133,9
133,6
141,2
151,8
155,4
156,6
161,6
160,7
156
159,5
168,7
169,9
169,9
185,9
190,8
195,8
211,9
227,1
251,3
256,7
251,9
251,2
270,3
267,2
243
229,9
187,2
178,2
175,2
192,4
187
184
194,1
212,7
217,5
200,5
205,9
196,5
206,3

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=61565&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=61565&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61565&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]
c46.8716937828447
b0.686362919272032

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 46.8716937828447 \tabularnewline
b & 0.686362919272032 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61565&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]46.8716937828447[/C][/ROW]
[ROW][C]b[/C][C]0.686362919272032[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61565&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61565&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]
c46.8716937828447
b0.686362919272032






Descriptive Statistics about e[t]
# observations61
minimum-15.2941908691668
Q1-6.40932259889457
median-2.92470012871078
mean-7.99622208155998e-16
Q33.86299967940804
maximum35.0711629966265

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -15.2941908691668 \tabularnewline
Q1 & -6.40932259889457 \tabularnewline
median & -2.92470012871078 \tabularnewline
mean & -7.99622208155998e-16 \tabularnewline
Q3 & 3.86299967940804 \tabularnewline
maximum & 35.0711629966265 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61565&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-15.2941908691668[/C][/ROW]
[ROW][C]Q1[/C][C]-6.40932259889457[/C][/ROW]
[ROW][C]median[/C][C]-2.92470012871078[/C][/ROW]
[ROW][C]mean[/C][C]-7.99622208155998e-16[/C][/ROW]
[ROW][C]Q3[/C][C]3.86299967940804[/C][/ROW]
[ROW][C]maximum[/C][C]35.0711629966265[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61565&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61565&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]
# observations61
minimum-15.2941908691668
Q1-6.40932259889457
median-2.92470012871078
mean-7.99622208155998e-16
Q33.86299967940804
maximum35.0711629966265


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')