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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 computationWed, 04 Nov 2009 11:42:24 -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/04/t1257360400p6tdig2haj5c73u.htm/, Retrieved Mon, 29 Apr 2024 08:49:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53794, Retrieved Mon, 29 Apr 2024 08:49:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsRob_WS5
Estimated Impact169

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] [Workshop 5] [2009-10-28 17:21:02] [03557919bc1ce1475f4920f6a43c36b0]
-    D  [Bivariate Explorative Data Analysis] [SHW_W5.3] [2009-10-30 14:41:18] [f966872135bb25240f339c0c372beeec]
-  M D      [Bivariate Explorative Data Analysis] [] [2009-11-04 18:42:24] [9002751dd674b8c934bf183fdf4510e9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.3
101.9
102.1
103.2
103.7
106.2
107.7
109.9
111.7
114.9
116.0
118.3
120.4
126.0
128.1
130.1
130.8
133.6
134.2
135.5
136.2
139.1
139.0
139.6
138.7
140.9
141.3
141.8
142.0
144.5
144.6
145.5
146.8
149.5
149.9
150.1
150.9
152.8
153.1
154.0
154.9
156.9
158.4
159.7
160.2
163.2
163.7
164.4
163.7
165.5
165.6
166.8
167.5
170.6
170.9
172.0
171.8
173.9
174.0
173.8
173.9
176.0
176.6
178.2
179.2
181.3
181.8
182.9
183.8
186.3
187.4
189.2
189.7
191.9
192.6
193.7
194.2
197.6
199.3
201.4
203.0
206.3
207.1
209.8
211.1
215.3
217.4
215.5
210.9
212.6
Dataseries Y:
Download CSV
Histogram 
106370
109375
116476
123297
114813
117925
126466
131235
120546
123791
129813
133463
122987
125418
130199
133016
121454
122044
128313
131556
120027
123001
130111
132524
123742
124931
133646
136557
127509
128945
137191
139716
129083
131604
139413
143125
133948
137116
144864
149277
138796
143258
150034
154708
144888
148762
156500
161088
152772
158011
163318
169969
162269
165765
170600
174681
166364
170240
176150
182056
172218
177856
182253
188090
176863
183273
187969
194650
183036
189516
193805
200499
188142
193732
197126
205140
191751
196700
199784
207360
196101
200824
205743
212489
200810
203683
207286
210910
194915
217920

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=53794&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=53794&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53794&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]
c7117.57957043553
b942.117029576953

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 7117.57957043553 \tabularnewline
b & 942.117029576953 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53794&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]7117.57957043553[/C][/ROW]
[ROW][C]b[/C][C]942.117029576953[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53794&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53794&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]
c7117.57957043553
b942.117029576953






Descriptive Statistics about e[t]
# observations90
minimum-16360.0754921900
Q1-6304.28180115707
median-110.242482755296
mean7.31237292939113e-13
Q36725.43714345181
maximum20578.7588790573

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 90 \tabularnewline
minimum & -16360.0754921900 \tabularnewline
Q1 & -6304.28180115707 \tabularnewline
median & -110.242482755296 \tabularnewline
mean & 7.31237292939113e-13 \tabularnewline
Q3 & 6725.43714345181 \tabularnewline
maximum & 20578.7588790573 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53794&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]90[/C][/ROW]
[ROW][C]minimum[/C][C]-16360.0754921900[/C][/ROW]
[ROW][C]Q1[/C][C]-6304.28180115707[/C][/ROW]
[ROW][C]median[/C][C]-110.242482755296[/C][/ROW]
[ROW][C]mean[/C][C]7.31237292939113e-13[/C][/ROW]
[ROW][C]Q3[/C][C]6725.43714345181[/C][/ROW]
[ROW][C]maximum[/C][C]20578.7588790573[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53794&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53794&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]
# observations90
minimum-16360.0754921900
Q1-6304.28180115707
median-110.242482755296
mean7.31237292939113e-13
Q36725.43714345181
maximum20578.7588790573


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')