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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 11:33:00 -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/t1257273257gobe752f93qazz2.htm/, Retrieved Wed, 01 May 2024 16:37:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53315, Retrieved Wed, 01 May 2024 16:37:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsshwws5v1
Estimated Impact107

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 18:33:00] [efdfe680cd785c4af09f858b30f777ec] [Current]
-    D            [Bivariate Explorative Data Analysis] [workshop 5 bivari...] [2009-11-04 11:34:19] [af8eb90b4bf1bcfcc4325c143dbee260]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5 Bivari...] [2009-11-04 11:34:29] [b6394cb5c2dcec6d17418d3cdf42d699]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5, Bivar...] [2009-11-04 11:44:07] [aba88da643e3763d32ff92bd8f92a385]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-7887,38628
-8153,249971
-8050,245702
-7820,43309
-7961,598309
-7877,474807
-7781,108569
-7891,555768
-7847,376918
-7683,962074
-7692,226978
-7972,697994
-8108,607671
-8343,945823
-8250,612764
-8239,157028
-8155,088873
-8234,545434
-7982,266075
-8149,727729
-8170,722635
-8101,449194
-8179,134035
-8421,929572
-8617,979002
-8766,284799
-8618,868306
-8608,777983
-8748,581233
-8692,242257
-8515,081307
-8576,701438
-8642,645266
-8530,422903
-8659,69717
-8624,979149
-8743,290039
-8905,048128
-8742,865833
-8725,697994
-8765,611115
-8648,052397
-8673,760231
-8610,19215
-8534,813106
-8483,389724
-8580,503864
-8700,645266
-8816,079659
-8924,674177
-8917,935636
-8883,476455
-8807,16639
-8829,066705
-8768,618682
-8721,75499
-8748,015626
-8776,99855
-8954,624599
-9053,98065
Dataseries Y:
Download CSV
Histogram 
-26899,91791
-27221,72575
-27317,12474
-27344,50896
-27823,97196
-27724,58281
-27255,01638
-27091,98191
-26630,7997
-26910,7898
-26887,88832
-27413,60748
-27971,09017
-28096,30197
-28082,60737
-28558,43982
-28738,84374
-28804,92749
-28397,19356
-28720,79451
-28500,2773
-28755,97677
-28718,6024
-29299,81415
-28936,17381
-28881,42998
-28321,58768
-28861,07037
-28646,56793
-28114,43993
-27536,57794
-27082,29229
-26368,58303
-26969,47456
-27154,69128
-26624,19383
-26836,9672
-26906,70611
-26991,83909
-27604,60748
-27551,77498
-26686,30711
-26767,77016
-25811,18409
-25771,81463
-26344,60272
-26401,87366
-26360,58303
-26672,74555
-27176,85386
-27699,26757
-28752,41521
-28974,55803
-29436,92251
-29195,04078
-28833,23294
-28995,73045
-29580,32643
-29882,47418
-29891,00621

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53315&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53315&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53315&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 time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Model: Y[t] = c + b X[t] + e[t]
c-23228.3994120390
b0.54073784021611

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -23228.3994120390 \tabularnewline
b & 0.54073784021611 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53315&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-23228.3994120390[/C][/ROW]
[ROW][C]b[/C][C]0.54073784021611[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53315&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53315&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-23228.3994120390
b0.54073784021611






Descriptive Statistics about e[t]
# observations60
minimum-1811.97040235165
Q1-928.971230406177
median119.312988345074
mean6.45779725990299e-15
Q3848.641845714408
maximum2073.07202907574

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1811.97040235165 \tabularnewline
Q1 & -928.971230406177 \tabularnewline
median & 119.312988345074 \tabularnewline
mean & 6.45779725990299e-15 \tabularnewline
Q3 & 848.641845714408 \tabularnewline
maximum & 2073.07202907574 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53315&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]-1811.97040235165[/C][/ROW]
[ROW][C]Q1[/C][C]-928.971230406177[/C][/ROW]
[ROW][C]median[/C][C]119.312988345074[/C][/ROW]
[ROW][C]mean[/C][C]6.45779725990299e-15[/C][/ROW]
[ROW][C]Q3[/C][C]848.641845714408[/C][/ROW]
[ROW][C]maximum[/C][C]2073.07202907574[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53315&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53315&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-1811.97040235165
Q1-928.971230406177
median119.312988345074
mean6.45779725990299e-15
Q3848.641845714408
maximum2073.07202907574


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')