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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, 24 May 2010 19:28:28 +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/24/t12747297211yas57ukhjtg3ed.htm/, Retrieved Sat, 04 May 2024 02:29:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76347, Retrieved Sat, 04 May 2024 02:29:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W32
Estimated Impact136

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Uitvoer van België] [2010-02-04 08:24:53] [2ee36997fb1be82ef07372b18c1a823d]
- RMPD    [Bootstrap Plot - Central Tendency] [eigen reeks oef 7] [2010-05-24 19:28:28] [ea4db07d8da34007b79212461ea6aa7b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
18288.3
16049
16764.5
17880.2
16555.9
16087.1
16373.5
17842.2
22321.5
22786.7
18274.1
22392.9
23899.3
21343.5
22952.3
21374.4
21164.1
20906.5
17877.4
20664.3
22160
19813.6
17735.4
19640.2
20844.4
19823.1
18594.6
21350.6
18574.1
18924.2
17343.4
19961.2
19932.1
19464.6
16165.4
17574.9
19795.4
19439.5
17170
21072.4
17751.8
17515.5
18040.3
19090.1
17746.5
19202.1
15141.6
16258.1
18586.5
17209.4
17838.7
19123.5
16583.6
15991.2
16704.5
17422
17872
17823.2
13866.5
15912.8
17870.5
15420.3
16379.4
17903.9
15305.8
14583.3
14861
14968.9
16726.5
16283.6
11703.7
15101.8
15469.7
14956.9
15370.6
15998.1
14725.1
14768.9
13659.6
15070.3
16942.6
15761.3
12083
15023.6
15106.5

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76347&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76347&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76347&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Estimation Results of Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean17537.468529411817704.724705882417900.8676470588278.319241214082363.399117647059
median1742217735.417823.2332.986558239795401.200000000001
midrange17517.6517801.517991.15451.70887708373473.5

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 17537.4685294118 & 17704.7247058824 & 17900.8676470588 & 278.319241214082 & 363.399117647059 \tabularnewline
median & 17422 & 17735.4 & 17823.2 & 332.986558239795 & 401.200000000001 \tabularnewline
midrange & 17517.65 & 17801.5 & 17991.15 & 451.70887708373 & 473.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76347&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]17537.4685294118[/C][C]17704.7247058824[/C][C]17900.8676470588[/C][C]278.319241214082[/C][C]363.399117647059[/C][/ROW]
[ROW][C]median[/C][C]17422[/C][C]17735.4[/C][C]17823.2[/C][C]332.986558239795[/C][C]401.200000000001[/C][/ROW]
[ROW][C]midrange[/C][C]17517.65[/C][C]17801.5[/C][C]17991.15[/C][C]451.70887708373[/C][C]473.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76347&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76347&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
mean17537.468529411817704.724705882417900.8676470588278.319241214082363.399117647059
median1742217735.417823.2332.986558239795401.200000000001
midrange17517.6517801.517991.15451.70887708373473.5


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 750 ;
Parameters (R input):
par1 = 750 ;
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')