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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 computationFri, 30 Oct 2009 08:56:44 -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/30/t1256914682m382n8j4guwu6hs.htm/, Retrieved Mon, 29 Apr 2024 03:49:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52132, Retrieved Mon, 29 Apr 2024 03:49:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

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: Bivar...] [2009-10-30 14:56:44] [a5c6be3c0aa55fdb2a703a08e16947ef] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.461486645
-0.004084972
-0.022949858
0.314235793
0.719086015
0.519010603
0.214639302
0.724751373
0.947471981
0.942293662
1.06557672
0.290473814
0.466120842
0.844038098
0.614769703
0.262528017
-0.351824955
0.049966352
0.053616259
-0.321937027
-0.471965568
-0.57493886
-0.966618095
-0.889742211
-0.735032602
-0.678409402
-0.695641924
-0.471580389
-0.516139175
-0.668427732
-1.285444229
-1.261260411
-1.324871567
-1.625105921
-1.023530639
-0.655808986
-0.185705033
0.171733303
0.570691931
0.710504447
1.116546865
1.045570694
2.012784886
2.471584571
2.54198808
2.135458622
2.675297587
2.315305706
1.513051716
1.066878896
0.546485598
0.446071879
-0.873384
-1.141009819
-2.342678843
-3.455050932
-4.154431398
-3.353127131
-2.63931828
Dataseries Y:
Download CSV
Histogram 
0.005146
-0.016437
0.006005
0.008702
0.006065
0.016797
0.020605
0.048558
0.041351
0.028252
0.051707
0.037076
0.046126
0.038562
0.043101
0.040678
0.010128
0.028543
0.010615
-0.000725
0.020013
0.009351
0.004490
0.023993
0.009841
0.011276
0.004274
0.009074
0.014261
0.011233
0.013814
0.031786
0.020695
-0.006130
0.024601
0.025193
-0.021078
-0.016113
-0.014245
0.009134
-0.047135
-0.022520
-0.009361
-0.021052
-0.027148
-0.041973
-0.052227
-0.071104
-0.052942
-0.067569
-0.068452
-0.049375
-0.037657
-0.020642
-0.011183
-0.016302
-0.010016
-0.012496
-0.602865

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=52132&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=52132&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52132&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-0.00948842683746882
b0.00905028552391264

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.00948842683746882 \tabularnewline
b & 0.00905028552391264 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52132&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.00948842683746882[/C][/ROW]
[ROW][C]b[/C][C]0.00905028552391264[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52132&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52132&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-0.00948842683746882
b0.00905028552391264






Descriptive Statistics about e[t]
# observations59
minimum-0.569489989140049
Q1-0.0099151938374639
median0.0215882326903807
mean5.71503179055918e-19
Q30.0360036406569305
maximum0.0526891936770262

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 59 \tabularnewline
minimum & -0.569489989140049 \tabularnewline
Q1 & -0.0099151938374639 \tabularnewline
median & 0.0215882326903807 \tabularnewline
mean & 5.71503179055918e-19 \tabularnewline
Q3 & 0.0360036406569305 \tabularnewline
maximum & 0.0526891936770262 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52132&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]59[/C][/ROW]
[ROW][C]minimum[/C][C]-0.569489989140049[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0099151938374639[/C][/ROW]
[ROW][C]median[/C][C]0.0215882326903807[/C][/ROW]
[ROW][C]mean[/C][C]5.71503179055918e-19[/C][/ROW]
[ROW][C]Q3[/C][C]0.0360036406569305[/C][/ROW]
[ROW][C]maximum[/C][C]0.0526891936770262[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52132&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52132&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]
# observations59
minimum-0.569489989140049
Q1-0.0099151938374639
median0.0215882326903807
mean5.71503179055918e-19
Q30.0360036406569305
maximum0.0526891936770262


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')