Free Statistics

of Irreproducible Research!

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, 28 Oct 2009 11:48:13 -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/28/t1256752140c6oa0794conqe3q.htm/, Retrieved Mon, 06 May 2024 07:57:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51651, Retrieved Mon, 06 May 2024 07:57:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWorkshop 4 Part 2.2
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [shw-ws4p2] [2009-10-28 17:48:13] [5b5bced41faf164488f2c271c918b21f] [Current]
Feedback Forum

Post a new message
Dataseries X:
7,8356
7,6944
8,0715
7,9077
7,9113
7,7639
7,8999
7,8827
7,6339
7,8789
7,8395
7,7381
7,9054
7,7467
8,0366
7,8925
7,9420
7,8891
7,9858
7,8698
7,7102
7,8164
7,7919
7,7866
7,8478
7,6497
8,1062
7,9377
7,7845
8,0143
7,8268
7,9997
7,7012
7,8124
7,8610
7,8047
7,7107
7,7719
8,0478
7,9381
7,8789
7,9327
7,8705
7,9395
7,6930
7,7506
7,8356
7,7882
7,7240
7,6751
8,0802
7,7385
7,9065
7,9132
7,7480
7,9121
7,5564
7,7790
7,8176
7,5807
Dataseries Y:
13,0733
13,0702
13,0614
13,0417
13,0274
13,0294
13,1555
13,1715
13,1673
13,1589
13,1407
13,1465
13,1600
13,1558
13,1420
13,1405
13,1241
13,1362
13,2522
13,2703
13,2673
13,2454
13,2128
13,2263
13,2398
13,2372
13,2273
13,2060
13,1931
13,2044
13,2938
13,3225
13,3255
13,3234
13,2949
13,2971
13,2893
13,2868
13,2784
13,2588
13,2489
13,2517
13,3387
13,3517
13,3507
13,3247
13,2970
13,2999
13,2936
13,2880
13,2704
13,2607
13,2582
13,2585
13,3368
13,3468
13,3373
13,2838
13,2459
13,2308




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=51651&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=51651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51651&T=0

As an alternative you can also use a 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]
c14.2411363822260
b-0.129131753228255

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 14.2411363822260 \tabularnewline
b & -0.129131753228255 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51651&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]14.2411363822260[/C][/ROW]
[ROW][C]b[/C][C]-0.129131753228255[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51651&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c14.2411363822260
b-0.129131753228255







Descriptive Statistics about e[t]
# observations60
minimum-0.209170363337130
Q1-0.0622221536028103
median0.0234875248993157
mean2.17535001513849e-18
Q30.0639655437125154
maximum0.135805172529750

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.209170363337130 \tabularnewline
Q1 & -0.0622221536028103 \tabularnewline
median & 0.0234875248993157 \tabularnewline
mean & 2.17535001513849e-18 \tabularnewline
Q3 & 0.0639655437125154 \tabularnewline
maximum & 0.135805172529750 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51651&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]-0.209170363337130[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0622221536028103[/C][/ROW]
[ROW][C]median[/C][C]0.0234875248993157[/C][/ROW]
[ROW][C]mean[/C][C]2.17535001513849e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0639655437125154[/C][/ROW]
[ROW][C]maximum[/C][C]0.135805172529750[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51651&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51651&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations60
minimum-0.209170363337130
Q1-0.0622221536028103
median0.0234875248993157
mean2.17535001513849e-18
Q30.0639655437125154
maximum0.135805172529750



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')