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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bootstrapplot1.wasp
Title produced by softwareBootstrap Plot - Central Tendency
Date of computationSun, 19 Dec 2010 16:42:19 +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/Dec/19/t1292777644xjlw1vlg2r8anht.htm/, Retrieved Sat, 04 May 2024 22:52:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112617, Retrieved Sat, 04 May 2024 22:52:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99

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] [Kijkcijfers- mean...] [2010-12-19 16:42:19] [0605ea080d54454c99180f574351b8e4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15561600
14917500
14805920
16958000
17605000
17131200
18474600
17286700
18574400
18056000
19701600
19061700
19681900
34521200
19922700
20177900
19759900
23076700
22532000
22029400
22587000
23256600
22680300
21916400
19640200
18813100
18730000
18154700
17848800
18077500
17133100
16602600
15878900
15789100
15422000
14661400
15879200
14339300
13169600
14528900
13375800
12309900
11933900
10061900
12609600
11156500
12187200
11284300
10177000
10970720
10820680
11492390
14573750
13992820
14727070
15685360
16736210
17950180
17002730
17415160
17929810
17865790
19202360
19085000
18188880
18466410
18520400
20025500
20636100
20672000
22589100
21864800
22750100
22548746
21325495
21556563
21415269
20401054
19062253
19085706
19279967
18552045
17800733
17142490
17593173
17633859
17336613
17008347
17951965
14520929
16941217
15436824
14744261
14248004
11540953
12881661
15185757
13554339
13575106
12238400
13303614
14151478
14172009
14022320

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112617&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]6 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=112617&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112617&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 time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Estimation Results of Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean16917148.329326917167453.7517393159.53125371790.215184187476011.201923076
median1713310017375886.517619429.5402353.721319155486329.5
midrange1671680022291550222915502691184.46978625574750

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 16917148.3293269 & 17167453.75 & 17393159.53125 & 371790.215184187 & 476011.201923076 \tabularnewline
median & 17133100 & 17375886.5 & 17619429.5 & 402353.721319155 & 486329.5 \tabularnewline
midrange & 16716800 & 22291550 & 22291550 & 2691184.4697862 & 5574750 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112617&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]16917148.3293269[/C][C]17167453.75[/C][C]17393159.53125[/C][C]371790.215184187[/C][C]476011.201923076[/C][/ROW]
[ROW][C]median[/C][C]17133100[/C][C]17375886.5[/C][C]17619429.5[/C][C]402353.721319155[/C][C]486329.5[/C][/ROW]
[ROW][C]midrange[/C][C]16716800[/C][C]22291550[/C][C]22291550[/C][C]2691184.4697862[/C][C]5574750[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112617&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112617&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
mean16917148.329326917167453.7517393159.53125371790.215184187476011.201923076
median1713310017375886.517619429.5402353.721319155486329.5
midrange1671680022291550222915502691184.46978625574750


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ;
Parameters (R input):
par1 = 500 ;
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')