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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationSat, 27 Nov 2010 14:31:45 +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/Nov/27/t1290868317yfyagacclkg5ys1.htm/, Retrieved Mon, 29 Apr 2024 08:07:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=102393, Retrieved Mon, 29 Apr 2024 08:07:00 +0000
QR Codes:

Original text written by user:Bootstrap plot voor 200 simulaties
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W22 - Natasha Van Linden
Estimated Impact96

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [Bootstrap plot co...] [2010-11-27 14:31:45] [85d6e4146de3ee96ae2a9c7dd566a647] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97
100.7
101.4
101.5
101.8
101.5
102.2
101.8
98.5
98.4
97.5
97.7
98.3
99.6
99.4
96.7
96.9
96.1
97.9
99.2
97.8
94.9
93.3
91.5
89.1
92.3
91.8
92.1
94.4
92.8
92.6
92.3
92.1
89.8
87.4
87.7
86.3
89.1
90.4
87.1
86.7
84.4
88.4
88.9
88.5
87.2
86.2
83.4
87.5
85.7
87.4
86.8
87.9
85.9
87.7
87
86.8
86.2
86.1
87.5
85.7
88.9
89.8
91.4
95.2
94.1
96.8
96.1
96.6
94.2
93.9
96.5
93.4
95
95.2
94
97
96.9
96.3
96.3
97.3
95.7
96.4
95.1
94.6
95.9
96.2
94.3
98.3
95.9
92.1
94.6
94.7
96.7
97.5
96.2
97.1
95.9
94.5
99.4
101.3
101.4
100.9
101.4
103.1
102.4
101.1
102
103.9
101.7
101.2
101.9
101.1
103.1
103.3
101.4
102.8
103
102.6
102.2

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=102393&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=102393&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102393&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 Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean93.730833333333394.90595.78833333333331.621213611927502.05750000000000
median94.387595.996.41252.165226031813822.02499999999999
midrange93.3593.6593.850.7130863980299140.5

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 93.7308333333333 & 94.905 & 95.7883333333333 & 1.62121361192750 & 2.05750000000000 \tabularnewline
median & 94.3875 & 95.9 & 96.4125 & 2.16522603181382 & 2.02499999999999 \tabularnewline
midrange & 93.35 & 93.65 & 93.85 & 0.713086398029914 & 0.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102393&T=1

[TABLE]
[ROW][C]Estimation Results of Blocked 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]93.7308333333333[/C][C]94.905[/C][C]95.7883333333333[/C][C]1.62121361192750[/C][C]2.05750000000000[/C][/ROW]
[ROW][C]median[/C][C]94.3875[/C][C]95.9[/C][C]96.4125[/C][C]2.16522603181382[/C][C]2.02499999999999[/C][/ROW]
[ROW][C]midrange[/C][C]93.35[/C][C]93.65[/C][C]93.85[/C][C]0.713086398029914[/C][C]0.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102393&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102393&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 Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean93.730833333333394.90595.78833333333331.621213611927502.05750000000000
median94.387595.996.41252.165226031813822.02499999999999
midrange93.3593.6593.850.7130863980299140.5


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 200 ; par2 = 12 ;
Parameters (R input):
par1 = 200 ; par2 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1 < 10) par1 = 10
if (par1 > 5000) par1 = 5000
if (par2 < 3) par2 = 3
if (par2 > length(x)) par2 = length(x)
library(lattice)
library(boot)
boot.stat <- function(s)
{
s.mean <- mean(s)
s.median <- median(s)
s.midrange <- (max(s) + min(s)) / 2
c(s.mean, s.median, s.midrange)
}
(r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed'))
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$t[,3]))
colnames(z) <- list('mean','median','midrange')
bitmap(file='plot7.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$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')