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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 computationThu, 29 Oct 2009 09:36:56 -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/29/t1256830732j1z8w3rs4tzdy14.htm/, Retrieved Sun, 28 Apr 2024 23:39:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52011, Retrieved Sun, 28 Apr 2024 23:39:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHWWS5
Estimated Impact136

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] [Bivariate EDA ana...] [2009-10-27 11:17:50] [4395c69e961f9a13a0559fd2f0a72538]
- RMPD    [Trivariate Scatterplots] [Trivariate Scatte...] [2009-10-29 14:00:50] [4395c69e961f9a13a0559fd2f0a72538]
- RMP       [Partial Correlation] [Partial Correlati...] [2009-10-29 14:05:54] [4395c69e961f9a13a0559fd2f0a72538]
- RMPD        [Bivariate Explorative Data Analysis] [Bivariate EDA Y[t] Z] [2009-10-29 14:14:40] [4395c69e961f9a13a0559fd2f0a72538]
-    D          [Bivariate Explorative Data Analysis] [Bivariate EDA Y[t...] [2009-10-29 15:03:23] [4395c69e961f9a13a0559fd2f0a72538]
-    D            [Bivariate Explorative Data Analysis] [Bivariate EDA X[t...] [2009-10-29 15:21:11] [4395c69e961f9a13a0559fd2f0a72538]
-    D                [Bivariate Explorative Data Analysis] [Bivariate EDA e[t...] [2009-10-29 15:36:56] [d1081bd6cdf1fed9ed45c42dbd523bf1] [Current]
-  M D                  [Bivariate Explorative Data Analysis] [Paper Bivariate E...] [2009-12-17 15:39:37] [4395c69e961f9a13a0559fd2f0a72538]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-1.0346
0.1433
0.4943
0.496
0.1586
0.1062
0.3858
0.9603
0.8042
0.2821
-0.5836
-0.7663
-0.3258
1.5997
2.2742
2.0351
1.2762
0.4235
0.3759
0.6742
0.8269
0.8119
0.3592
0.1167
0.2779
1.4238
1.6187
1.5272
0.8099
0.4269
0.5813
0.6371
0.5946
0.2773
0.1232
0.1623
0.1079
0.862
1.0671
0.7974
0.2957
0.0433
0.0688
0.1722
0.1909
0.1994
0.2926
-0.1924
-0.6907
-0.5771
-0.9196
-1.2533
-0.9292
-0.8102
-0.6847
-0.7218
-0.9912
-1.3637
-1.7045
-1.8243
-1.324
-0.0053
0.4063
0.0182
-0.5076
-1.1762
-0.9629
-0.5156
-0.4819
-0.9046
-1.408
-2.0729
-2.097
Dataseries Y:
Download CSV
Histogram 
-0.0446
0.2333
0.1843
0.286
0.5486
0.5962
0.7758
0.8503
0.5942
0.0721
-0.4936
-0.6763
-0.6358
0.3897
0.7642
0.8251
0.5662
0.3135
0.3659
0.5642
0.6169
0.7019
0.3492
0.3067
-0.0321
0.4138
0.4087
0.5172
0.4999
0.5169
0.7713
0.9271
0.9846
0.8673
0.9132
0.6523
-0.0021
-0.448
-0.7429
-0.7126
-0.5143
-0.3667
-0.2412
-0.1378
-0.2191
-0.4106
-0.3174
-0.6024
-1.0007
-0.6871
-0.8296
-0.9633
-0.9392
-0.9202
-0.5947
-0.2318
-0.2012
-0.4737
-0.8145
-0.9343
-0.534
0.5847
0.5963
0.2082
-0.7176
-1.2862
-0.9729
-0.1256
0.4081
0.3854
0.182
-0.2829
-0.307

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52011&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52011&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52011&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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Model: Y[t] = c + b X[t] + e[t]
c0.000253986526723375
b0.40771026482133

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.000253986526723375 \tabularnewline
b & 0.40771026482133 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52011&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.000253986526723375[/C][/ROW]
[ROW][C]b[/C][C]0.40771026482133[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52011&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52011&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]
c0.000253986526723375
b0.40771026482133






Descriptive Statistics about e[t]
# observations73
minimum-1.17822161011756
Q1-0.364125610594138
median0.00555440409671764
mean1.78923062629217e-17
Q30.370626049464839
maximum0.862716108847289

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 73 \tabularnewline
minimum & -1.17822161011756 \tabularnewline
Q1 & -0.364125610594138 \tabularnewline
median & 0.00555440409671764 \tabularnewline
mean & 1.78923062629217e-17 \tabularnewline
Q3 & 0.370626049464839 \tabularnewline
maximum & 0.862716108847289 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52011&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]73[/C][/ROW]
[ROW][C]minimum[/C][C]-1.17822161011756[/C][/ROW]
[ROW][C]Q1[/C][C]-0.364125610594138[/C][/ROW]
[ROW][C]median[/C][C]0.00555440409671764[/C][/ROW]
[ROW][C]mean[/C][C]1.78923062629217e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.370626049464839[/C][/ROW]
[ROW][C]maximum[/C][C]0.862716108847289[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52011&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52011&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]
# observations73
minimum-1.17822161011756
Q1-0.364125610594138
median0.00555440409671764
mean1.78923062629217e-17
Q30.370626049464839
maximum0.862716108847289


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')