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, 11 Nov 2009 06:41:30 -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/11/t12579469379ps29b0gzwkewg7.htm/, Retrieved Fri, 29 Mar 2024 07:37:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55590, Retrieved Fri, 29 Mar 2024 07:37:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact212
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [3/11/2009] [2009-11-02 22:01:32] [b98453cac15ba1066b407e146608df68]
-   PD    [Bivariate Explorative Data Analysis] [WS6-RSPlot] [2009-11-11 13:41:30] [30970b478e356ce7f8c2e9fca280b230] [Current]
Feedback Forum

Post a new message
Dataseries X:
100
95,06
92,59
93,83
96,30
96,30
96,30
92,59
92,59
87,65
92,59
92,59
93,83
95,06
95,06
97,53
100,00
101,23
101,23
101,23
97,53
90,12
85,19
81,48
82,72
85,19
86,42
87,65
88,89
87,65
85,19
86,42
83,95
79,01
82,72
81,48
79,01
77,78
76,54
80,25
83,95
83,95
79,01
75,31
71,60
75,31
88,89
90,12
85,19
75,31
71,60
76,54
87,65
95,06
97,53
95,06
91,36
92,59
98,77
100,00
Dataseries Y:
100
91.74
84.40
84.40
87.16
88.07
87.16
83.49
81.65
82.57
92.66
94.50
93.58
88.07
84.40
85.32
86.24
86.24
84.40
82.57
82.57
82.57
89.91
91.74
89.91
85.32
82.57
82.57
83.49
83.49
83.49
84.40
80.73
76.15
77.06
74.31
70.64
72.48
72.48
73.39
72.48
69.72
65.14
62.39
59.63
63.30
75.23
79.82
76.15
72.48
68.81
71.56
76.15
77.06
75.23
70.64
66.06
66.97
74.31
77.98




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=55590&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=55590&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55590&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c24.8574048452436
b0.620593710285099

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 24.8574048452436 \tabularnewline
b & 0.620593710285099 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55590&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]24.8574048452436[/C][/ROW]
[ROW][C]b[/C][C]0.620593710285099[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55590&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55590&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]
c24.8574048452436
b0.620593710285099







Descriptive Statistics about e[t]
# observations60
minimum-15.4948462168902
Q1-3.57914130897248
median0.0292215800928616
mean-6.41298357010693e-16
Q33.5444534797161
maximum16.3166196407266

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -15.4948462168902 \tabularnewline
Q1 & -3.57914130897248 \tabularnewline
median & 0.0292215800928616 \tabularnewline
mean & -6.41298357010693e-16 \tabularnewline
Q3 & 3.5444534797161 \tabularnewline
maximum & 16.3166196407266 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55590&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]-15.4948462168902[/C][/ROW]
[ROW][C]Q1[/C][C]-3.57914130897248[/C][/ROW]
[ROW][C]median[/C][C]0.0292215800928616[/C][/ROW]
[ROW][C]mean[/C][C]-6.41298357010693e-16[/C][/ROW]
[ROW][C]Q3[/C][C]3.5444534797161[/C][/ROW]
[ROW][C]maximum[/C][C]16.3166196407266[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55590&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55590&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-15.4948462168902
Q1-3.57914130897248
median0.0292215800928616
mean-6.41298357010693e-16
Q33.5444534797161
maximum16.3166196407266



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')