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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 computationThu, 05 Nov 2009 03:56:03 -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/05/t1257418643eldgawc0cjzc9mc.htm/, Retrieved Thu, 02 May 2024 23:33:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53977, Retrieved Thu, 02 May 2024 23:33:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsY & Z
Estimated Impact102

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 bivariate Y ...] [2009-11-04 16:51:13] [62d3ced7fb1c10c35a82e9cb1d0d0e2b]
-    D    [Bivariate Explorative Data Analysis] [Ws 5] [2009-11-05 10:56:03] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
62
64
62
64
64
69
69
65
56
58
53
62
55
60
59
58
53
57
57
53
54
53
57
57
55
49
50
49
54
58
58
52
56
52
59
53
52
53
51
50
56
52
46
48
46
48
48
49
53
48
51
48
50
55
52
53
52
55
53
53
56
54
52
55
54
59
56
56
51
53
52
51
46
49
46
55
57
53
52
53
50
54
53
50
51
52
47
51
49
53
52
45
53
51
48
48
48
48
40
43
40
39
39
36
41
39
40
39
46
40
37
37
44
41
40
36
38
43
42
45
46
Dataseries Y:
Download CSV
Histogram 
46
46
41
43
39
36
34
31
27
27
30
28
31
25
26
22
27
38
39
45
48
46
47
55
63
83
100
76
68
63
63
62
62
64
72
67
67
67
69
78
80
85
90
83
84
84
89
82
76
97
82
79
73
72
74
77
78
68
71
68
70
79
78
79
78
77
72
72
84
83
82
78
77
75
77
73
64
64
71
65
68
64
65
56
57
51
52
79
59
54
55
47
52
52
54
49
48
44
47
43
45
40
38
46
51
49
57
61
61
81
97
105
108
113
111
111
110
109
105
97
97

Tables (Output of Computation)





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=53977&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=53977&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53977&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 time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Model: Y[t] = c + b X[t] + e[t]
c139.397283501983
b-1.45390994884179

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 139.397283501983 \tabularnewline
b & -1.45390994884179 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53977&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]139.397283501983[/C][/ROW]
[ROW][C]b[/C][C]-1.45390994884179[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53977&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53977&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]
c139.397283501983
b-1.45390994884179






Descriptive Statistics about e[t]
# observations121
minimum-44.6947954971532
Q1-13.2478761110517
median4.02167363315722
mean2.05700929200952e-16
Q314.0216736331572
maximum33.2982139401065

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 121 \tabularnewline
minimum & -44.6947954971532 \tabularnewline
Q1 & -13.2478761110517 \tabularnewline
median & 4.02167363315722 \tabularnewline
mean & 2.05700929200952e-16 \tabularnewline
Q3 & 14.0216736331572 \tabularnewline
maximum & 33.2982139401065 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53977&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]121[/C][/ROW]
[ROW][C]minimum[/C][C]-44.6947954971532[/C][/ROW]
[ROW][C]Q1[/C][C]-13.2478761110517[/C][/ROW]
[ROW][C]median[/C][C]4.02167363315722[/C][/ROW]
[ROW][C]mean[/C][C]2.05700929200952e-16[/C][/ROW]
[ROW][C]Q3[/C][C]14.0216736331572[/C][/ROW]
[ROW][C]maximum[/C][C]33.2982139401065[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53977&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53977&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]
# observations121
minimum-44.6947954971532
Q1-13.2478761110517
median4.02167363315722
mean2.05700929200952e-16
Q314.0216736331572
maximum33.2982139401065


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')