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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 09:04:45 -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/t1257350729wfsh8goi8m4ku03.htm/, Retrieved Mon, 29 Apr 2024 09:10:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53684, Retrieved Mon, 29 Apr 2024 09:10:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128

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 e] [2009-11-04 16:04:45] [b406b824746c89e17d2637b66f6fb2ee] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-9,122
-0,1328
2,1672
1,6288
4,1716
7,1856
2,0096
-0,7332
0,6508
0,7672
-1,4704
-0,7492
0,2124
2,8372
4,0488
3,2124
4,318
4,0624
5,8284
6,4044
6,6204
4,5496
-0,1492
2,6424
1,5908
2,4748
1,1604
-4,578
2,7388
6,1556
5,5796
6,9016
5,604
6,768
3,314
2,7268
3,5708
3,5372
5,4188
2,344
-0,964
-0,3252
1,6556
0,6368
-6,6752
-8,808
-11,5384
-10,5732
-12,8804
-7,756
-7,2176
-13,2612
-15,1764
-14,1912
-20,34
-20,2924
-17,6652
-15,494
-18,6892
-18,4544
-13,7072
Dataseries Y:
Download CSV
Histogram 
-28,232
-13,6128
-14,4528
-12,7712
-15,2384
-16,7344
-18,3704
-16,0232
-11,6492
-14,7028
-10,8104
-7,5492
-5,5476
-2,2228
-1,4812
-3,5976
-8,312
-7,4576
-2,8216
-2,5256
-2,4896
-6,3904
-12,4092
-5,4076
-6,1492
-7,8852
-11,7896
-18,908
-5,7212
2,8656
1,6096
2,4216
-2,976
-3,442
-4,746
-5,6232
-4,1092
-3,9728
-1,9512
-7,706
-14,754
-21,7552
-18,6744
-21,0932
-31,2252
-33,948
-41,6084
-36,5632
-33,9704
-26,056
-30,1576
-40,3312
-50,2164
-47,2612
-57,94
-65,2624
-64,9752
-68,884
-69,8192
-60,0244
-52,6772

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=53684&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=53684&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53684&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-14.9242018658762
b2.35723214003397

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -14.9242018658762 \tabularnewline
b & 2.35723214003397 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53684&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-14.9242018658762[/C][/ROW]
[ROW][C]b[/C][C]2.35723214003397[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53684&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53684&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-14.9242018658762
b2.35723214003397






Descriptive Statistics about e[t]
# observations61
minimum-18.7483253995519
Q1-2.50430065569844
median1.11495461152631
mean2.94789238556977e-16
Q33.2844887288834
maximum11.3158947223698

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -18.7483253995519 \tabularnewline
Q1 & -2.50430065569844 \tabularnewline
median & 1.11495461152631 \tabularnewline
mean & 2.94789238556977e-16 \tabularnewline
Q3 & 3.2844887288834 \tabularnewline
maximum & 11.3158947223698 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53684&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]-18.7483253995519[/C][/ROW]
[ROW][C]Q1[/C][C]-2.50430065569844[/C][/ROW]
[ROW][C]median[/C][C]1.11495461152631[/C][/ROW]
[ROW][C]mean[/C][C]2.94789238556977e-16[/C][/ROW]
[ROW][C]Q3[/C][C]3.2844887288834[/C][/ROW]
[ROW][C]maximum[/C][C]11.3158947223698[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53684&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53684&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-18.7483253995519
Q1-2.50430065569844
median1.11495461152631
mean2.94789238556977e-16
Q33.2844887288834
maximum11.3158947223698


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')