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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 10:57:59 -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/t1257357632gelb62rswg584zs.htm/, Retrieved Mon, 29 Apr 2024 12:25:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53767, Retrieved Mon, 29 Apr 2024 12:25:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact205

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] [WS5.5] [2009-11-04 17:57:59] [dd4f17965cad1d38de7a1c062d32d75d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-14592.498
-14749.83
-11156.16
-17184.822
-16545.82
-17444.154
-17099.494
-15654.83
-11063.164
-13154.828
-13161.16
-13948.494
-10852.162
-9392.162
-4035.162
-9891.16
-9131.16
-10197.824
-11863.16
-11729.16
-7285.494
-8177.828
-7750.828
-9981.496
-7517.164
-6005.498
-1075.498
-5927.498
-4997.496
-6932.492
-10592.156
-10866.154
-6412.488
-7672.156
-6610.49
-7920.824
-6428.158
-5585.824
-133.156
-3363.49
-2202.822
-2256.486
-3363.488
-3620.154
783.514
-1380.152
-1259.818
-3304.82
-347.822
1289.178
6757.514
1001.516
745.518
1461.516
2010.842
3153.508
11929.844
14782.516
15136.518
22871.182
32275.176
36322.172
44015.504
41091.172
40859.174
41557.84
41163.17
42609.836
Dataseries Y:
Download CSV
Histogram 
-9627,054
-9879,41
-10788,3
-17642,546
-14437,08
-15375,902
-10005,122
-9551,41
-7988,232
-13723,944
-17598,3
-15783,122
-11085,766
-11790,766
-8022,766
-13348,3
-13524,3
-12618,012
-8935,3
-9100,3
-10968,122
-10056,944
-10411,944
-10946,588
-5283,232
-5128,054
-2249,054
-4387,054
-8762,588
-11380,656
-13290,368
-11371,902
-10899,724
-12171,368
-10352,19
-12691,012
-9346,834
-7929,012
-2859,368
-5897,19
-4573,546
-3579,258
-4843,724
-3116,902
4224,742
-2958,436
940,386
-455,08
3108,454
5254,454
3068,742
1027,208
1686,674
2374,208
5331,166
6855,344
10646,632
18059,208
20561,674
23339,386
38642,988
44831,056
40739,412
42120,056
37655,522
40053,7
41048,59
45168,768

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=53767&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=53767&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53767&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]
c0.0599159214394364
b1.02424464328507

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.0599159214394364 \tabularnewline
b & 1.02424464328507 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53767&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.0599159214394364[/C][/ROW]
[ROW][C]b[/C][C]1.02424464328507[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53767&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53767&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]
c0.0599159214394364
b1.02424464328507






Descriptive Statistics about e[t]
# observations68
minimum-4578.21036351763
Q1-2482.88362252798
median-246.301845947920
mean-2.40134709502747e-14
Q32610.66303695614
maximum7628.20598059968

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 68 \tabularnewline
minimum & -4578.21036351763 \tabularnewline
Q1 & -2482.88362252798 \tabularnewline
median & -246.301845947920 \tabularnewline
mean & -2.40134709502747e-14 \tabularnewline
Q3 & 2610.66303695614 \tabularnewline
maximum & 7628.20598059968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53767&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]68[/C][/ROW]
[ROW][C]minimum[/C][C]-4578.21036351763[/C][/ROW]
[ROW][C]Q1[/C][C]-2482.88362252798[/C][/ROW]
[ROW][C]median[/C][C]-246.301845947920[/C][/ROW]
[ROW][C]mean[/C][C]-2.40134709502747e-14[/C][/ROW]
[ROW][C]Q3[/C][C]2610.66303695614[/C][/ROW]
[ROW][C]maximum[/C][C]7628.20598059968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53767&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53767&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]
# observations68
minimum-4578.21036351763
Q1-2482.88362252798
median-246.301845947920
mean-2.40134709502747e-14
Q32610.66303695614
maximum7628.20598059968


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')