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Description of Statistical Computation

Author's title

bootstrap plot 200 Prijsindexcijfers van ijzererts en schroot Karen De Maer...

Author*Unverified author*
R Software Modulerwasp_bootstrapplot1.wasp
Title produced by softwareBootstrap Plot - Central Tendency
Date of computationMon, 05 May 2008 14:09:49 -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/2008/May/05/t1210018231h4a0tmjeln52hj9.htm/, Retrieved Wed, 15 May 2024 14:40:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=11601, Retrieved Wed, 15 May 2024 14:40:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [bootstrap plot 20...] [2008-05-05 20:09:49] [e1b1b3318b3a8a01c97d416cfdcee2a5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
229.7
231.5
226.4
242.1
228.3
209.9
209.3
220.8
239.6
241.1
241.9
240.8
179.9
190.8
174.2
170
170.3
159.3
147.9
154.2
164.5
173.9
163.6
149.7
128.2
124.7
125.1
120.9
117.5
114
113.4
118.9
121.7
121.9
120.3
115.6
105.7
105.1
104.6
105
104.9
105.1
103.9
101.9
99
97
95.8
94.7
97.6
97.9
99.3
99.7
99.7
100
99.1
98.2
98.1
98.6
100.2
101.9
97.5
97.1
98.1
98.5
98.3
99.3
100.9
100.4
101.7
102
103.2
103.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=11601&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]5 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=11601&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=11601&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 time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Estimation Results of Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean132.6125136.319444444444140.6309027777786.038519080610028.0184027777778
median105109.55115.73756.6007775114967610.7375000000000
midrange168.3168.4168.950.8152916286203920.649999999999977

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 132.6125 & 136.319444444444 & 140.630902777778 & 6.03851908061002 & 8.0184027777778 \tabularnewline
median & 105 & 109.55 & 115.7375 & 6.60077751149676 & 10.7375000000000 \tabularnewline
midrange & 168.3 & 168.4 & 168.95 & 0.815291628620392 & 0.649999999999977 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=11601&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]132.6125[/C][C]136.319444444444[/C][C]140.630902777778[/C][C]6.03851908061002[/C][C]8.0184027777778[/C][/ROW]
[ROW][C]median[/C][C]105[/C][C]109.55[/C][C]115.7375[/C][C]6.60077751149676[/C][C]10.7375000000000[/C][/ROW]
[ROW][C]midrange[/C][C]168.3[/C][C]168.4[/C][C]168.95[/C][C]0.815291628620392[/C][C]0.649999999999977[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=11601&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=11601&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
mean132.6125136.319444444444140.6309027777786.038519080610028.0184027777778
median105109.55115.73756.6007775114967610.7375000000000
midrange168.3168.4168.950.8152916286203920.649999999999977


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 200 ;
Parameters (R input):
par1 = 200 ;
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')