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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 11:44:23 -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/t1257274015nt3n88nw012pg43.htm/, Retrieved Wed, 01 May 2024 15:55:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53330, Retrieved Wed, 01 May 2024 15:55:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

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] [ws 5 5] [2009-11-03 18:44:23] [84778c3520b84fd5786bccf2e25a5aef] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-14.93885623
-14.10024254
-12.58373114
-12.41083342
-12.30703798
-12.45414026
-12.10503798
-11.81373114
-10.91762886
-9.083424295
-9.381140261
-9.745242542
-10.28924254
-10.45203798
-10.1709357
-7.19103798
-7.558242542
-8.461242542
-8.294140261
-8.92003798
-7.585833418
-5.324526576
-4.674731137
-5.936628857
-6.521628857
-6.744526576
-7.084424295
-6.733424295
-7.128526576
-7.083526576
-6.282424295
-5.699526576
-4.542219733
-2.373708329
-2.485015172
-4.68681061
-5.586503768
-5.590503768
-7.861503768
-6.118708329
-6.91581061
-5.512606048
-5.302299206
-4.137890083
-3.44158324
-2.512992363
-5.411219733
-7.727424295
-7.594015172
-5.972401487
-6.162094644
-5.730401487
-8.911219733
-6.882526576
-6.272526576
-4.744219733
-3.38281061
-0.850912891
-2.682628857
-4.422833418
-3.983731137
Dataseries Y:
Download CSV
Histogram 
-3.509688829
-4.431724902
-4.38242163
-3.916082284
-3.225403593
-3.079064248
-3.023403593
-3.61242163
-3.009760975
-1.762439666
-0.006064248
-0.076724902
-0.620724902
-1.370403593
-1.382742939
1.890596407
2.110275098
1.207275098
1.080935752
0.161596407
0.908917716
2.289899679
3.52657837
1.971239025
1.386239025
0.869899679
0.236560334
0.587560334
0.485899679
0.530899679
1.038560334
1.914899679
2.191881643
2.893184915
3.662202952
0.873524261
-0.906493776
-0.910493776
-3.181493776
-0.851815085
-1.355475739
-0.53915443
-1.209172467
-1.218529849
-1.402547885
0.699809497
1.322881643
-0.406439666
-1.446797048
-1.585833121
-2.655851158
-1.343833121
-2.177118357
0.731899679
1.341899679
1.989881643
2.177524261
5.002863606
5.225239025
4.071917716
4.21757837

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=53330&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=53330&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53330&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]
c4.16697632023306
b0.580628182330685

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 4.16697632023306 \tabularnewline
b & 0.580628182330685 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53330&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]4.16697632023306[/C][/ROW]
[ROW][C]b[/C][C]0.580628182330685[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53330&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53330&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]
c4.16697632023306
b0.580628182330685






Descriptive Statistics about e[t]
# observations61
minimum-3.57124398425211
Q1-1.16998936131193
median0.330199923034068
mean1.29819879800559e-17
Q31.14649006472365
maximum2.61587262187470

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -3.57124398425211 \tabularnewline
Q1 & -1.16998936131193 \tabularnewline
median & 0.330199923034068 \tabularnewline
mean & 1.29819879800559e-17 \tabularnewline
Q3 & 1.14649006472365 \tabularnewline
maximum & 2.61587262187470 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53330&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]-3.57124398425211[/C][/ROW]
[ROW][C]Q1[/C][C]-1.16998936131193[/C][/ROW]
[ROW][C]median[/C][C]0.330199923034068[/C][/ROW]
[ROW][C]mean[/C][C]1.29819879800559e-17[/C][/ROW]
[ROW][C]Q3[/C][C]1.14649006472365[/C][/ROW]
[ROW][C]maximum[/C][C]2.61587262187470[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53330&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53330&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-3.57124398425211
Q1-1.16998936131193
median0.330199923034068
mean1.29819879800559e-17
Q31.14649006472365
maximum2.61587262187470


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')