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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 08:09:38 -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/t1257347431qwah5poldhqdghb.htm/, Retrieved Mon, 29 Apr 2024 10:42:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53622, Retrieved Mon, 29 Apr 2024 10:42:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

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 5.6] [2009-11-04 15:09:38] [29af64a72952b0c5025d716b5179273f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,8261
0,6698
0,5298
-0,3941
-0,8222
-0,3989
0,0482
0,6652
1,1634
0,6756
0,3273
0,3746
0,4142
0,4450
0,6470
0,3020
0,1949
0,1592
-0,2003
0,1388
0,6420
0,5751
0,6404
0,6916
0,8162
0,9539
1,2953
0,9542
0,8657
0,3737
-0,6978
-0,6497
-0,2217
0,0179
0,0356
-0,1155
0,0767
-0,0401
0,0712
-0,1210
-0,2479
-0,4653
-0,7343
-0,5642
-0,5734
-0,4474
-0,7552
-0,7610
-0,2143
-0,1667
-0,6350
-0,7647
-1,2518
-0,7948
-0,1537
0,0351
0,0250
-0,7998
-1,4750
-1,1927
Dataseries Y:
Download CSV
Histogram 
0,6112
0,5840
0,6842
-0,6891
-1,2026
-0,1637
0,8145
1,8764
2,3402
1,2938
0,2466
0,1588
0,1913
0,3426
0,5795
0,1044
-0,2742
0,4333
0,2669
1,0323
1,6045
0,7263
0,4351
0,2871
0,2614
0,3243
0,6935
-0,0753
0,2773
0,4574
0,1379
0,9182
1,2651
0,8310
0,3938
-0,0247
0,2290
0,2010
0,7199
0,3328
0,0547
-0,1410
-0,9896
-0,8393
-0,9211
-0,3444
-0,6909
-1,1006
-0,7894
-1,0100
-1,6239
-1,6399
-2,2518
-1,5901
-1,0551
-0,4071
-0,1571
-0,5985
-1,6240
-1,5202

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53622&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53622&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53622&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'George Udny Yule' @ 72.249.76.132






Model: Y[t] = c + b X[t] + e[t]
c-8.07077443241707e-05
b1.08429940263473

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -8.07077443241707e-05 \tabularnewline
b & 1.08429940263473 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53622&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-8.07077443241707e-05[/C][/ROW]
[ROW][C]b[/C][C]1.08429940263473[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53622&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53622&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-8.07077443241707e-05
b1.08429940263473






Descriptive Statistics about e[t]
# observations60
minimum-1.10985778224973
Q1-0.344525792879091
median-0.130896766094237
mean3.94175252334261e-17
Q30.331503809495737
maximum1.62275002963611

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1.10985778224973 \tabularnewline
Q1 & -0.344525792879091 \tabularnewline
median & -0.130896766094237 \tabularnewline
mean & 3.94175252334261e-17 \tabularnewline
Q3 & 0.331503809495737 \tabularnewline
maximum & 1.62275002963611 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53622&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]-1.10985778224973[/C][/ROW]
[ROW][C]Q1[/C][C]-0.344525792879091[/C][/ROW]
[ROW][C]median[/C][C]-0.130896766094237[/C][/ROW]
[ROW][C]mean[/C][C]3.94175252334261e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.331503809495737[/C][/ROW]
[ROW][C]maximum[/C][C]1.62275002963611[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53622&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53622&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-1.10985778224973
Q1-0.344525792879091
median-0.130896766094237
mean3.94175252334261e-17
Q30.331503809495737
maximum1.62275002963611


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')