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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, 08 Dec 2009 13:28:08 -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/Dec/08/t12603041224ymh1mtqgis6340.htm/, Retrieved Sat, 27 Apr 2024 14:07:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64847, Retrieved Sat, 27 Apr 2024 14:07:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154

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] [Workshop 4] [2009-10-29 12:50:48] [1646a2766cb8c4a6f9d3b2fffef409b3]
- RM D  [Bivariate Explorative Data Analysis] [] [2009-12-08 20:18:56] [74be16979710d4c4e7c6647856088456]
-    D      [Bivariate Explorative Data Analysis] [] [2009-12-08 20:28:08] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
543,058008
541,7453276
539,031539
533,6065967
530,8653313
536,5202699
562,3726523
570,448946
570,9737297
572,9589863
563,4536361
563,5059893
560,1223081
558,8166068
556,2292693
550,4089389
548,0109488
551,3936888
577,4738089
581,1178882
579,5964113
569,1493653
560,2918882
560,7896219
559,6588246
556,4746176
550,4207482
546,7988661
546,2810632
549,2094318
574,251687
578,8635418
572,3774978
555,984712
543,9816173
539,8268241
539,9462936
533,5522467
525,8089006
522,0785382
514,7630523
513,1179202
544,7990455
550,9972777
535,7182095
525,7632547
516,162765
516,8684552
518,0550164
512,3690076
505,511622
503,1480895
493,7641137
500,7404517
529,5705808
534,0945609
520,5535515
510,9559668
505,5719533
510,2705165
513,7149015
514,0924041
513,1042779
512,4177983
506,1294301
514,0243185
542,0885537
Dataseries Y:
Download CSV
Histogram 
517,1199087
517,0744627
514,5648647
508,7858096
504,8207603
504,8445305
526,5614874
534,1825531
535,3522205
532,016917
526,0104562
527,1764411
526,4294825
526,4057371
524,439701
519,7595598
516,8558793
514,774708
535,965484
539,6165305
540,6477596
536,8295819
530,5440604
531,6540228
529,3297649
529,5356456
526,1520693
524,6103316
523,7862159
520,875225
538,3326109
539,1901334
540,6477596
527,7366768
519,4477837
515,617106
518,6848754
513,9805444
505,1712581
503,3418322
496,0413289
485,1515227
508,4840214
510,87474
504,6414569
500,6425871
493,3781511
497,0965701
498,5388651
495,0141412
486,9086157
486,9137501
474,9252573
476,2761804
497,9297139
498,3302118
496,9597569
495,0737319
496,2489295
505,7321425
514,1196359
518,0222003
522,5380369
523,4147495
517,1363457
521,5294814
541,0268016

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=64847&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=64847&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64847&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]
c194.106221428094
b0.595386919836408

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 194.106221428094 \tabularnewline
b & 0.595386919836408 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64847&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]194.106221428094[/C][/ROW]
[ROW][C]b[/C][C]0.595386919836408[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64847&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64847&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]
c194.106221428094
b0.595386919836408






Descriptive Statistics about e[t]
# observations67
minimum-15.9643562032483
Q1-4.64722475640127
median-0.479680445329828
mean3.30633116242147e-16
Q32.72590383263867
maximum24.2216734727156

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 67 \tabularnewline
minimum & -15.9643562032483 \tabularnewline
Q1 & -4.64722475640127 \tabularnewline
median & -0.479680445329828 \tabularnewline
mean & 3.30633116242147e-16 \tabularnewline
Q3 & 2.72590383263867 \tabularnewline
maximum & 24.2216734727156 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64847&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]67[/C][/ROW]
[ROW][C]minimum[/C][C]-15.9643562032483[/C][/ROW]
[ROW][C]Q1[/C][C]-4.64722475640127[/C][/ROW]
[ROW][C]median[/C][C]-0.479680445329828[/C][/ROW]
[ROW][C]mean[/C][C]3.30633116242147e-16[/C][/ROW]
[ROW][C]Q3[/C][C]2.72590383263867[/C][/ROW]
[ROW][C]maximum[/C][C]24.2216734727156[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64847&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64847&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]
# observations67
minimum-15.9643562032483
Q1-4.64722475640127
median-0.479680445329828
mean3.30633116242147e-16
Q32.72590383263867
maximum24.2216734727156


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')