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 12:19:26 -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/t1257189608y8ls6obj0j2g4m3.htm/, Retrieved Sat, 04 May 2024 01:45:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52893, Retrieved Sat, 04 May 2024 01:45:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

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] [2009-11-02 19:19:26] [9f6463b67b1eb7bae5c03a796abf0348] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101,01
100,88
100,55
100,82
101,5
102,16
102,39
102,54
102,85
103,47
103,57
103,69
103,5
103,47
103,45
103,48
103,93
103,89
104,4
104,79
104,77
105,13
105,26
104,96
104,75
105,01
105,15
105,2
105,77
105,78
106,26
106,13
106,12
106,57
106,44
106,54
107,1
108,1
108,4
108,84
109,62
110,42
110,67
111,66
112,28
112,87
112,18
112,36
112,16
111,49
111,25
111,36
111,74
111,1
111,33
111,25
111,04
110,97
111,31
111,02
Dataseries Y:
Download CSV
Histogram 
1076.7
1035.9
1037
1154
1237.2
996.6
1238.2
1153.4
1268.1
1156
1144.5
1232.9
1055.2
1109.7
1079.8
1126.3
1196.8
1130.4
1183.6
1200.9
1426.6
1080.4
1325.4
1230
1125.9
1174.5
1151.9
1439.3
1344.3
1319.1
1257.6
1249.1
1397.1
1348
1548.2
1377.6
1402.9
1167.6
1392.9
1547
1420
1266.4
1280.8
1128.6
1449.5
1511.7
1548.3
1652
1650.5
1370.8
1653.3
1474.3
1418.8
1554.1
1156.6
1223.4
1337.5
1098.9
1037.6
1202.5

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52893&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52893&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52893&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'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c-1607.0254626449
b26.9991926824565

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -1607.0254626449 \tabularnewline
b & 26.9991926824565 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52893&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-1607.0254626449[/C][/ROW]
[ROW][C]b[/C][C]26.9991926824565[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52893&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52893&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-1607.0254626449
b26.9991926824565






Descriptive Statistics about e[t]
# observations60
minimum-360.654674839332
Q1-80.2180097268778
median-6.1902534035579
mean3.80528941690272e-15
Q391.7730438225164
maximum281.431393524231

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -360.654674839332 \tabularnewline
Q1 & -80.2180097268778 \tabularnewline
median & -6.1902534035579 \tabularnewline
mean & 3.80528941690272e-15 \tabularnewline
Q3 & 91.7730438225164 \tabularnewline
maximum & 281.431393524231 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52893&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]-360.654674839332[/C][/ROW]
[ROW][C]Q1[/C][C]-80.2180097268778[/C][/ROW]
[ROW][C]median[/C][C]-6.1902534035579[/C][/ROW]
[ROW][C]mean[/C][C]3.80528941690272e-15[/C][/ROW]
[ROW][C]Q3[/C][C]91.7730438225164[/C][/ROW]
[ROW][C]maximum[/C][C]281.431393524231[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52893&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52893&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-360.654674839332
Q1-80.2180097268778
median-6.1902534035579
mean3.80528941690272e-15
Q391.7730438225164
maximum281.431393524231


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')