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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationFri, 25 May 2012 04:58:17 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/25/t1337936323ikkdb0njr2u85b5.htm/, Retrieved Sat, 04 May 2024 00:31:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167445, Retrieved Sat, 04 May 2024 00:31:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [maximumprijs stud...] [2012-05-25 08:42:57] [65d089efb1547052afcdc66fb34b47a2]
- RMPD    [Blocked Bootstrap Plot - Central Tendency] [werkloosheid in B...] [2012-05-25 08:58:17] [50083fea611f0183deb36cab794727ad] [Current]
- R P       [Blocked Bootstrap Plot - Central Tendency] [werkloosheid in B...] [2012-05-25 09:02:05] [65d089efb1547052afcdc66fb34b47a2]
- RMPD      [Variability] [maximumprijs stud...] [2012-05-25 09:43:05] [65d089efb1547052afcdc66fb34b47a2]
- RMPD      [Standard Deviation Plot] [aantal nieuwe ins...] [2012-05-25 09:47:41] [65d089efb1547052afcdc66fb34b47a2]
- RMPD      [Standard Deviation-Mean Plot] [maximumprijs stud...] [2012-05-25 09:59:13] [65d089efb1547052afcdc66fb34b47a2]
- RMP       [Variability] [werkloosheid in B...] [2012-05-25 10:08:02] [65d089efb1547052afcdc66fb34b47a2]
- RMP       [Standard Deviation Plot] [werkloosheid in B...] [2012-05-25 10:11:25] [65d089efb1547052afcdc66fb34b47a2]
- RMP       [Standard Deviation-Mean Plot] [werkloosheid in B...] [2012-05-25 10:17:23] [65d089efb1547052afcdc66fb34b47a2]
- RMPD      [Classical Decomposition] [nieuwe personenwa...] [2012-05-25 10:52:22] [65d089efb1547052afcdc66fb34b47a2]
- RMPD      [Classical Decomposition] [nieuwe personenwa...] [2012-05-25 10:56:23] [65d089efb1547052afcdc66fb34b47a2]
- RMP       [Classical Decomposition] [Werkloosheid in B...] [2012-05-25 11:08:46] [65d089efb1547052afcdc66fb34b47a2]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516
528
533
536
537
524
536
587
597
581
564
558
575
580
575
563
552
537
545
601
604
586
564
549
551
556
548
540
531
521
519
572
581
563
548
539
541

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' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167445&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167445&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167445&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' @ jenkins.wessa.net






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean546.660714285714555.797619047619564.93452380952411.785314999469718.2738095238096
median541.125556.5565.87514.404279409471424.75
midrange548.625549562.510.279740328650813.875

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 546.660714285714 & 555.797619047619 & 564.934523809524 & 11.7853149994697 & 18.2738095238096 \tabularnewline
median & 541.125 & 556.5 & 565.875 & 14.4042794094714 & 24.75 \tabularnewline
midrange & 548.625 & 549 & 562.5 & 10.2797403286508 & 13.875 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167445&T=1

[TABLE]
[ROW][C]Estimation Results of Blocked Bootstrap[/C][/ROW]
[ROW][C]statistic[/C][C]Q1[/C][C]Estimate[/C][C]Q3[/C][C]S.D.[/C][C]IQR[/C][/ROW]
[ROW][C]mean[/C][C]546.660714285714[/C][C]555.797619047619[/C][C]564.934523809524[/C][C]11.7853149994697[/C][C]18.2738095238096[/C][/ROW]
[ROW][C]median[/C][C]541.125[/C][C]556.5[/C][C]565.875[/C][C]14.4042794094714[/C][C]24.75[/C][/ROW]
[ROW][C]midrange[/C][C]548.625[/C][C]549[/C][C]562.5[/C][C]10.2797403286508[/C][C]13.875[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167445&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167445&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:

Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean546.660714285714555.797619047619564.93452380952411.785314999469718.2738095238096
median541.125556.5565.87514.404279409471424.75
midrange548.625549562.510.279740328650813.875


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 12 ;
Parameters (R input):
par1 = 50 ; par2 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1 < 10) par1 = 10
if (par1 > 5000) par1 = 5000
if (par2 < 3) par2 = 3
if (par2 > length(x)) par2 = length(x)
library(lattice)
library(boot)
boot.stat <- function(s)
{
s.mean <- mean(s)
s.median <- median(s)
s.midrange <- (max(s) + min(s)) / 2
c(s.mean, s.median, s.midrange)
}
(r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed'))
bitmap(file='plot1.png')
plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
grid()
dev.off()
bitmap(file='plot2.png')
plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
grid()
dev.off()
bitmap(file='plot3.png')
plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
grid()
dev.off()
bitmap(file='plot4.png')
densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
dev.off()
bitmap(file='plot5.png')
densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
dev.off()
bitmap(file='plot6.png')
densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
dev.off()
z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3]))
colnames(z) <- list('mean','median','midrange')
bitmap(file='plot7.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$t[,1],0.25)[[1]]
q3 <- quantile(r$t[,1],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[1])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,1])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
q1 <- quantile(r$t[,2],0.25)[[1]]
q3 <- quantile(r$t[,2],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[2])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,2])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'midrange',header=TRUE)
q1 <- quantile(r$t[,3],0.25)[[1]]
q3 <- quantile(r$t[,3],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[3])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,3])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')