FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationMon, 02 Nov 2009 14:05:06 -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/02/t1257195981vmf8n4n16pp0gjj.htm/, Retrieved Sat, 04 May 2024 03:35:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52979, Retrieved Sat, 04 May 2024 03:35:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Partial Correlation] [Workshop 5 correl...] [2009-10-29 15:05:45] [eaf42bcf5162b5692bb3c7f9d4636222]
- RMPD  [Bivariate Explorative Data Analysis] [workshop 5 bivari...] [2009-10-29 15:48:25] [eaf42bcf5162b5692bb3c7f9d4636222]
-  M D      [Bivariate Explorative Data Analysis] [WS5 bivariate EDA...] [2009-11-02 21:05:06] [557d56ec4b06cd0135c259898de8ce95] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,4
1,3
1,3
1,2
1,1
1,4
1,2
1,5
1,1
1,3
1,5
1,1
1,4
1,3
1,5
1,6
1,7
1,1
1,6
1,3
1,7
1,6
1,7
1,9
1,8
1,9
1,6
1,5
1,6
1,6
1,7
2
2
1,9
1,7
1,8
1,9
1,7
2
2,1
2,4
2,5
2,5
2,6
2,2
2,5
2,8
2,8
2,9
3
3,1
2,9
2,7
2,2
2,5
2,3
2,6
2,3
2,2
1,8
Dataseries Y:
Download CSV
Histogram 
10284.5
12792
12823.61538
13845.66667
15335.63636
11188.5
13633.25
12298.46667
15353.63636
12696.15385
12213.93333
13683.72727
11214.14286
13950.23077
11179.13333
11801.875
11188.82353
16456.27273
11110.0625
16530.69231
10038.41176
11681.25
11148.88235
8631
9386.444444
9764.736842
12043.75
12948.06667
10987.125
11648.3125
10633.35294
10219.3
9037.6
10296.31579
11705.41176
10681.94444
9362.947368
11306.35294
10984.45
10062.61905
8118.583333
8867.48
8346.72
8529.307692
10697.18182
8591.84
8695.607143
8125.571429
7009.758621
7883.466667
7527.645161
6763.758621
6682.333333
7855.681818
6738.88
7895.434783
6361.884615
6935.956522
8344.454545
9107.944444

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52979&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52979&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52979&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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Model: Y[t] = c + b X[t] + e[t]
c18022.7363388866
b-3969.45411827332

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 18022.7363388866 \tabularnewline
b & -3969.45411827332 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52979&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]18022.7363388866[/C][/ROW]
[ROW][C]b[/C][C]-3969.45411827332[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52979&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52979&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]
c18022.7363388866
b-3969.45411827332






Descriptive Statistics about e[t]
# observations60
minimum-2181.00057330394
Q1-903.437057028763
median-6.82849964926206
mean7.30027149842272e-14
Q3520.398237089893
maximum3668.24632486874

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -2181.00057330394 \tabularnewline
Q1 & -903.437057028763 \tabularnewline
median & -6.82849964926206 \tabularnewline
mean & 7.30027149842272e-14 \tabularnewline
Q3 & 520.398237089893 \tabularnewline
maximum & 3668.24632486874 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52979&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]-2181.00057330394[/C][/ROW]
[ROW][C]Q1[/C][C]-903.437057028763[/C][/ROW]
[ROW][C]median[/C][C]-6.82849964926206[/C][/ROW]
[ROW][C]mean[/C][C]7.30027149842272e-14[/C][/ROW]
[ROW][C]Q3[/C][C]520.398237089893[/C][/ROW]
[ROW][C]maximum[/C][C]3668.24632486874[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52979&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52979&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-2181.00057330394
Q1-903.437057028763
median-6.82849964926206
mean7.30027149842272e-14
Q3520.398237089893
maximum3668.24632486874


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')