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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 computationTue, 10 Nov 2009 03:44:04 -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/10/t125785005798lyz5phzgzxsrm.htm/, Retrieved Mon, 06 May 2024 01:15:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55152, Retrieved Mon, 06 May 2024 01:15:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

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] [3/11/2009] [2009-11-02 22:01:32] [b98453cac15ba1066b407e146608df68]
-   PD    [Bivariate Explorative Data Analysis] [ws2] [2009-11-10 10:44:04] [94ba0ef70f5b330d175ff4daa1c9cd40] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
395.3
395.1
403.5
403.3
405.7
406.7
407.2
412.4
415.9
414
411.8
409.9
412.4
415.9
416.3
417.2
421.8
421.4
415.1
412.4
411.8
408.8
404.5
402.5
409.4
410.7
413.4
415.2
417.7
417.8
417.9
418.4
418.2
416.6
418.9
421
423.5
432.3
432.3
428.6
426.7
427.3
428.5
437
442
444.9
441.4
440.3
447.1
455.3
478.6
486.5
487.8
485.9
483.8
488.4
494
493.6
487.3
482.1
484.2
496.8
501.1
499.8
495.5
498.1
503.8
516.2
526.1
527.1
525.1
528.9
540.1
549
556
568.9
589.1
590.3
603.3
638.8
643
656.7
656.1
654.1
659.9
662.1
669.2
673.1
678.3
677.4
678.5
672.4
665.3
667.9
672.1
662.5
682.3
692.1
702.7
721.4
733.2
747.7
737.6
729.3
706.1
674.3
659
645.7
Dataseries Y:
Download CSV
Histogram 
798.6
798.4
806.8
806.6
809
810
810.5
815.7
819.2
817.3
815.1
813.2
815.7
819.2
819.6
820.5
825.1
824.7
818.4
815.7
815.1
812.1
807.8
805.8
812.7
814
816.7
818.5
821
821.1
821.2
821.7
821.5
819.9
822.2
824.3
826.8
835.6
835.6
831.9
830
830.6
831.8
840.3
845.3
848.2
844.7
843.6
850.4
858.6
881.9
889.8
891.1
889.2
887.1
891.7
897.3
896.9
890.6
885.4
887.5
900.1
904.4
903.1
898.8
901.4
907.1
919.5
929.4
930.4
928.4
932.2
943.4
952.3
959.3
972.2
992.4
993.6
1006.6
1042.1
1046.3
1060
1059.4
1057.4
1063.2
1065.4
1072.5
1076.4
1081.6
1080.7
1081.8
1075.7
1068.6
1071.2
1075.4
1065.8
1085.6
1095.4
1106
1124.7
1136.5
1151
1140.9
1132.6
1109.4
1077.6
1062.3
1049

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55152&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]2 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=55152&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55152&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c403.3
b1

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 403.3 \tabularnewline
b & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55152&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]403.3[/C][/ROW]
[ROW][C]b[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55152&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55152&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]
c403.3
b1






Descriptive Statistics about e[t]
# observations108
minimum-1.17459228727696e-13
Q1-7.00878417205867e-14
median-3.87445729094983e-14
mean9.35034422832727e-29
Q39.09490893834297e-15
maximum2.96004919451264e-12

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 108 \tabularnewline
minimum & -1.17459228727696e-13 \tabularnewline
Q1 & -7.00878417205867e-14 \tabularnewline
median & -3.87445729094983e-14 \tabularnewline
mean & 9.35034422832727e-29 \tabularnewline
Q3 & 9.09490893834297e-15 \tabularnewline
maximum & 2.96004919451264e-12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55152&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]108[/C][/ROW]
[ROW][C]minimum[/C][C]-1.17459228727696e-13[/C][/ROW]
[ROW][C]Q1[/C][C]-7.00878417205867e-14[/C][/ROW]
[ROW][C]median[/C][C]-3.87445729094983e-14[/C][/ROW]
[ROW][C]mean[/C][C]9.35034422832727e-29[/C][/ROW]
[ROW][C]Q3[/C][C]9.09490893834297e-15[/C][/ROW]
[ROW][C]maximum[/C][C]2.96004919451264e-12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55152&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55152&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]
# observations108
minimum-1.17459228727696e-13
Q1-7.00878417205867e-14
median-3.87445729094983e-14
mean9.35034422832727e-29
Q39.09490893834297e-15
maximum2.96004919451264e-12


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = red ; par2 = blue ; par3 = TRUE ; par4 = HK ; par5 = VI ;
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')