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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot1.wasp
Title produced by softwareBootstrap Plot - Central Tendency
Date of computationMon, 10 May 2010 20:49:38 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/10/t127352469737yng2d554w5ih6.htm/, Retrieved Mon, 29 Apr 2024 12:21:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75794, Retrieved Mon, 29 Apr 2024 12:21:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W32
Estimated Impact93

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] [opgave7oef2] [2010-05-10 20:49:38] [06ce09a0492afa6d4f67026fd1b7902e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
196.9 
192.1 
201.8 
186.9
  218
214.4
227.5
204.1
225.8
223.7
244.7
243.9
257.3
234.5
251.4
243.8
247.4
245.3
262.5
  270
259.9
262.2
244.9
249.3
268.2
231.2
264.3
252.7
275.5
261.5
275.5
272.3
268.6
270.4
267.7
  275
272.6
248.6
279.4
270.5
292.8
297.8
296.8
290.9
282.8
312.8
303.2
301.4
289.8
279.6
302.2
299.1
319.7
310.9
315.2
338.5
315.6
321.2
318.5
342.7
261.4
  287
331.5
326.9
338.6
  337
358.4
344.5
345.7
344.1
317.4
354.5
345.2
314.1
352.5
361.2
365.9
332.5
  364
359.1
345.6
366.9
370.2
359.9
366.6
336.3
368.5
374.2
384.3
358.9
407.7
433.3
404.7
392.7
409.7
416.5
414.3
404.3
421.4
372.6
404.7
420.2
438.4
449.1
445.8
413.8
420.5
442.3
438.9
394.5
416.8
402.9
424.5
432.3
484.1
492.7
496.3
471.9
491.2
512.9
482.4
407.9
448.5
431.1
498.8
497.1
517.1
487.7
512.5
550.1
532.5
524.1
515.7
  461
529.3
467.4
559.8
536.5
531.9
546.5
547.4
536.1
482.8
  551
532.9
484.1
554.8
  537
  558
511.4
502.9
558.6
545.1
574.3
542.2
  600
588.6
524.4
618.5
580.9
557.2
571.2
597.5
601.7
558.9
600.9
  601
615.7
578.1
495.9
526.8
522.1
605.1
574.4
609.7
580.7
565.1
590.7
571.5
601.3
567.3
467.9
588.9
579.4
502.6
568.7
  616
586.2
575.5
599.9
568.2
  516
493.4
496.8
529.9
491.7
543.2
490.8
554.7
625.7
  605
645.2
645.2
611.8
600.3
549.8
635.5
617.7
643.5
485.7
689.5
  692
677.3
704.7
668.6
717.8
689.8
640.4
675.2
528.1
  538
527.2
655.6
650.6
623.7
748.4
727.4
750.5
678.9
659.5
691.9
639.8
663.8
572.9
592.5
734.8
696.1
589.2
662.9
661.2
672.1
583.7
705.5
  631
733.3
674.9
695.5
634.1
630.6
635.2
554.1
623.9
679.3
565.6
564.1
637.2
650.8
602.7
587.5
619.2
616.5
637.9
557.9
  594
668.7
603.3
674.5
573.4
  706
693.7
627.5
550.7
592.3
660.2
597.3
  641
663.6
595.9
638.4
665.4
671.4
  637
685.7
705.8
704.8
734.4
674.2
748.6
763.4
  658
627.5
528.9
488.3
575.5
735.6
685.3
613.6
629.5
634.7
652.6
728.3
634.3
690.7
676.3
675.4
595.6
712.4
735.8
544.4
  567
  510
  564
630.7
496.7
660.9
601.2
655.2
591.6
606.1
560.7
368.3
371.6
413.9
413.9
  389
399.2
429.8
395.6
  472
  486
  525
  396
  511
  525
  492
  517
  525
  474
  539
  468
  543
  532
  565
  535
  534
  546
  494
  552
  511
  451
  537
  494
  549
  544
  598
  583
  582
  589
  578
  561
  592
  504
  545
  547
  585
  562
  520
  581
  590
  562
  548
  567
  542
  473
  531
  462
  479
  533
  552
  547
  562
  524
  479
  445
  406
  475
  589
  495
  484
  536
  555
  565
  564
  573
  569
  588
  546
  508
  560
  558
  516
  549
  595
  586
  597
  592
  538
  590
  576
  451
  538
  555
  532
  530
  553
  626
  601
  573
  569
  562
  468
  483
  460
  411
  458
  455
  600
  605
  545
  549
  415
  568
  577
  517
  558
  518
  489
  502
  569
  540
  550
  557
  542
  542
  582
  525
  584
  562
  639
  613
  604
  613
  625
  654
  638

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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75794&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]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75794&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75794&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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Estimation Results of Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean504.998021978022508.025934065934512.5410989010995.647971542634097.54307692307685
median538542543.84.324963135386135.79999999999995
midrange469.0875475.15475.154.56834996782996.0625

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 504.998021978022 & 508.025934065934 & 512.541098901099 & 5.64797154263409 & 7.54307692307685 \tabularnewline
median & 538 & 542 & 543.8 & 4.32496313538613 & 5.79999999999995 \tabularnewline
midrange & 469.0875 & 475.15 & 475.15 & 4.5683499678299 & 6.0625 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75794&T=1

[TABLE]
[ROW][C]Estimation Results of 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]504.998021978022[/C][C]508.025934065934[/C][C]512.541098901099[/C][C]5.64797154263409[/C][C]7.54307692307685[/C][/ROW]
[ROW][C]median[/C][C]538[/C][C]542[/C][C]543.8[/C][C]4.32496313538613[/C][C]5.79999999999995[/C][/ROW]
[ROW][C]midrange[/C][C]469.0875[/C][C]475.15[/C][C]475.15[/C][C]4.5683499678299[/C][C]6.0625[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75794&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75794&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 Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean504.998021978022508.025934065934512.5410989010995.647971542634097.54307692307685
median538542543.84.324963135386135.79999999999995
midrange469.0875475.15475.154.56834996782996.0625


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ;
Parameters (R input):
par1 = 50 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
if (par1 < 10) par1 = 10
if (par1 > 5000) par1 = 5000
library(lattice)
library(boot)
boot.stat <- function(s,i)
{
s.mean <- mean(s[i])
s.median <- median(s[i])
s.midrange <- (max(s[i]) + min(s[i])) / 2
c(s.mean, s.median, s.midrange)
}
(r <- boot(x,boot.stat, R=par1, stype='i'))
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$t[,3]))
colnames(z) <- list('mean','median','midrange')
bitmap(file='plot7.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Bootstrap',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$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')