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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 computationThu, 21 May 2009 07:20:04 -0600
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/May/21/t12429120393bs5z5ifgmkpnja.htm/, Retrieved Mon, 06 May 2024 16:42:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40257, Retrieved Mon, 06 May 2024 16:42:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

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] [Opgave 7 oefening...] [2009-05-21 12:49:43] [98301858a407264bfb04a3efba7def1a]
-    D    [Bootstrap Plot - Central Tendency] [Opgave 7, oefenin...] [2009-05-21 13:20:04] [20170a44ccda5b3788507d09fd8ffa1a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11310
64305
15310
37299
21302
61308
72300
26303
18301
54305
66309
50301
31298
52291
87286
81288
14293
90302
50306
15310
44310
26314
98313
76310
25313
48309
95307
10320
87327
63328
34333
90333
81332
7342
30424
13344
88347
40339
23330
1339
10341
46342
81342
2342
76350
35368
93367
88377
39376
41366
77375
56382
79397
26385
73397
28404
98413
73414
47423
52431
24441
92439
90441
441
13448
18458
18459
69477
41491
10492
73508
82515
13525
55533
19550
85558
57563
60570
49568
51570
26561
61558
78548
77537
539
18540
47542
86542
81544
16543
22538
25538
99527
63518
95508
65496
5488
96475
81465
5463
81458
74445
21434
67427
27418
81407
82395
97359

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=40257&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=40257&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40257&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






Estimation Results of Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean49472.247685185251417.527777777853207.45138888892657.697840877973735.20370370371
median49659.62551930.555237.3754726.452378456425577.75
midrange494274998449984400.099924253623557

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 49472.2476851852 & 51417.5277777778 & 53207.4513888889 & 2657.69784087797 & 3735.20370370371 \tabularnewline
median & 49659.625 & 51930.5 & 55237.375 & 4726.45237845642 & 5577.75 \tabularnewline
midrange & 49427 & 49984 & 49984 & 400.099924253623 & 557 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40257&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]49472.2476851852[/C][C]51417.5277777778[/C][C]53207.4513888889[/C][C]2657.69784087797[/C][C]3735.20370370371[/C][/ROW]
[ROW][C]median[/C][C]49659.625[/C][C]51930.5[/C][C]55237.375[/C][C]4726.45237845642[/C][C]5577.75[/C][/ROW]
[ROW][C]midrange[/C][C]49427[/C][C]49984[/C][C]49984[/C][C]400.099924253623[/C][C]557[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40257&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40257&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
mean49472.247685185251417.527777777853207.45138888892657.697840877973735.20370370371
median49659.62551930.555237.3754726.452378456425577.75
midrange494274998449984400.099924253623557


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')