## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_bootstrapplot1.wasp
Title produced by softwareBootstrap Plot - Central Tendency
Date of computationSun, 22 Dec 2013 11:48:04 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/22/t1387730941r63i1jgz9sxrilz.htm/, Retrieved Fri, 21 Jan 2022 16:32:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232545, Retrieved Fri, 21 Jan 2022 16:32:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
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Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bootstrap Plot - Central Tendency] [] [2013-12-22 16:48:04] [20efb5145ec2a2ddd8dcd418764211fa] [Current]
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Dataseries X:
20
25
15
15
25
25
25
21
30
25
20
40
13
30
25
20
25
20
25
20
20
15
15
12
20
5
20
15
25
22
20
22
25
20
20
35
30
25
20
20
20
25
25
15
20
35
25
25
30
23
10
22
25
25
22
30
20
25
25
22
25
25
25
22
25
12
18
20
20
22
30
25
22
20
50
30
25
20
30
22
25
30
22
25
22
22
25
25
25
20
22
15
20
30
20
25
30
35
22
12
30
15
10
30
9
25
20
20
35
25
35
30
12
25
15
25
25
20
20
6
15
40
20
40
25
25
20
15
15
22
24
22
20
25
25
25
35
40
20
22
22
20
25
25
18
25
20
25
30
20
22
35
22
25
25
25
25
22
23
35
15
25
18
22
25
25
28
30
20
25
25
30
22
30
10
10
25
20
22
25
25
15
22
25
25
28
22
30
25
20
25
25
20
30
20
30
50
19
20
28
20
25
35
25
25
15
16
20
20
25
30
20
25
25
25
20
20
25
25
30
22
20
25
25
18
18
20
25
25
30
25
20
25
20
20
20
22
18
22
20
15
25
25
20
25
15
22
25
25
15
12
25
30
22
15
22
25
12
18
30
25
25
40
24
25
15
25
20
25
25
25
20
30
20
25
30
22
25
25
25
50
19
50
25
35
20
20
20
20
20
25
25
25
20
20
20
20
25
18
25
22
22
30
30
8
20
25
30
50
22
20
10
25
25
25
25
18
25
20
25
30
18
20
25
22
22
20
20
25
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20
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25
20
10
20
25
30
25
50
30
30
50
15
25
25
22
20
22
30
25
18
22
22
30
40
25
20
10
20
9
15
20
15
20
30
12
15
12
20
15
12
25
20
25
25
25
30
20
25
15
15
22
10
15
10
20
25
20
20
38
20
20
20
40
25
25
30
25
10
20
25
12
15
25
20
22
22
20
25
25
25
15
40
20
20
16
25
15
20
25
20
30
50
20
25
20
30
30
25
25
12
25
25
25
20
20
20
15
20
25
15
25
50
30
20
20
25
12
15
20
20
35
22
15
18
30
22
12
12
20
20
15
25
15
20
20
25
18
30
20
25
25
25
20
20
25
20
22
15
15
22
20
10
25
20
20
15
12
20
5
20
15
15
25
25
25
15
25
22
25
20
18
22
25
35
25
25
25
35
30
22
30
50
15
25
24
20
25
25
25
12
15
22
25
25
25
25
15
20
20
15
35
30
20
22
65
20
25
22
20
25
25
20
25
15
20
12
15
10
25
15
30
35
25
25
25
25
25
40
40
25
25
20
25
25
22
25
30
25
25
30
25
25
30
25
25
20
22
22
20
25
22
25
22
40
25
25
25
22
20
35
20
35
25
22
25
25
25
25
25
40
25
30
25
20
25
25
30
22
22
20
15
15
25
25
20
20
15
25
15
20
22
25
15
15
18
5
15
25
18
40
25
25
20
30
20
25
25
25
22
22
25
25
30
25
25
25
25
20
20
25
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22
30
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30
25
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20
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25
24
25
30
18
15
22
22
25
22
22
25
15
20
22
18
35
20
20
20
25
25
30
15
25
22
26
25
20
25
25
25
22
25
25
20
22
30
15
30
25
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25
25
35
22
20
25
20
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18
20
22
25
10
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25
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20
30
25
20
15
20
25
10
20
25
22
22
25
25
15
25
20
10
25
16
25
35
25
15
25
25
30
25
10
22
20
25
20
20
25
22
18
30
19
25
20
25
20
25
20
22
12
30
12
22
25
25
25
25
30
30
10
22
22
25
20
22
20
25
20
15
25
20
25
20
30
15
40
25
20
22
22
30
20
40
20
25
20
25
20
50
50
25
25
40
30
22
30
20
25
25
30
25
25
20
18
18
28
25
22
15
40
40
12
12
18
12
25
26
18
25
22
15
25
15
15
15
25
15
12
22
20
20
25
20
12
9
15
12
15
25
20
20
15
15
30
21
25
22
22
50
15
25
15
25
22
18
50
20
50
20
20
30
25
20
22
25
50
40
25
25
25
25
30
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25
30
20


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 51 seconds R Server 'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 51 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232545&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]51 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232545&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232545&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 51 seconds R Server 'Herman Ole Andreas Wold' @ wold.wessa.net

 Estimation Results of Bootstrap statistic P1 P5 Q1 Estimate Q3 P95 P99 S.D. IQR mean 22.618 22.768 22.986 23.166 23.329 23.54 23.718 0.23994 0.34278 median 22 22 22 22 24.375 25 25 1.2919 2.375 midrange 27.5 27.5 27.5 35 35 35 35.5 3.6578 7.5 mode 25 25 25 25 25 25 25 0 0 mode k.dens 12 20 22.933 25 23 25 30 2.5267 0.066668

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & P1 & P5 & Q1 & Estimate & Q3 & P95 & P99 & S.D. & IQR \tabularnewline
mean & 22.618 & 22.768 & 22.986 & 23.166 & 23.329 & 23.54 & 23.718 & 0.23994 & 0.34278 \tabularnewline
median & 22 & 22 & 22 & 22 & 24.375 & 25 & 25 & 1.2919 & 2.375 \tabularnewline
midrange & 27.5 & 27.5 & 27.5 & 35 & 35 & 35 & 35.5 & 3.6578 & 7.5 \tabularnewline
mode & 25 & 25 & 25 & 25 & 25 & 25 & 25 & 0 & 0 \tabularnewline
mode k.dens & 12 & 20 & 22.933 & 25 & 23 & 25 & 30 & 2.5267 & 0.066668 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232545&T=1

[TABLE]
[ROW][C]Estimation Results of Bootstrap[/C][/ROW]
[ROW][C]statistic[/C][C]P1[/C][C]P5[/C][C]Q1[/C][C]Estimate[/C][C]Q3[/C][C]P95[/C][C]P99[/C][C]S.D.[/C][C]IQR[/C][/ROW]
[ROW][C]mean[/C][C]22.618[/C][C]22.768[/C][C]22.986[/C][C]23.166[/C][C]23.329[/C][C]23.54[/C][C]23.718[/C][C]0.23994[/C][C]0.34278[/C][/ROW]
[ROW][C]median[/C][C]22[/C][C]22[/C][C]22[/C][C]22[/C][C]24.375[/C][C]25[/C][C]25[/C][C]1.2919[/C][C]2.375[/C][/ROW]
[ROW][C]midrange[/C][C]27.5[/C][C]27.5[/C][C]27.5[/C][C]35[/C][C]35[/C][C]35[/C][C]35.5[/C][C]3.6578[/C][C]7.5[/C][/ROW]
[ROW][C]mode[/C][C]25[/C][C]25[/C][C]25[/C][C]25[/C][C]25[/C][C]25[/C][C]25[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]mode k.dens[/C][C]12[/C][C]20[/C][C]22.933[/C][C]25[/C][C]23[/C][C]25[/C][C]30[/C][C]2.5267[/C][C]0.066668[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232545&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232545&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Estimation Results of Bootstrap statistic P1 P5 Q1 Estimate Q3 P95 P99 S.D. IQR mean 22.618 22.768 22.986 23.166 23.329 23.54 23.718 0.23994 0.34278 median 22 22 22 22 24.375 25 25 1.2919 2.375 midrange 27.5 27.5 27.5 35 35 35 35.5 3.6578 7.5 mode 25 25 25 25 25 25 25 0 0 mode k.dens 12 20 22.933 25 23 25 30 2.5267 0.066668

par4 <- 'P1 P5 Q1 Q3 P95 P99'par3 <- '0'par2 <- '5'par1 <- '50'par1 <- as.numeric(par1)par2 <- as.numeric(par2)if (par3 == '0') bw <- NULLif (par3 != '0') bw <- as.numeric(par3)if (par1 < 10) par1 = 10if (par1 > 5000) par1 = 5000library(modeest)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])) / 2s.mode <- mlv(s[i], method='mfv')$Ms.kernelmode <- mlv(s[i], method='kernel', bw=bw)$Mc(s.mean, s.median, s.midrange, s.mode, s.kernelmode)}(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$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')grid()dev.off()bitmap(file='plot7.png')plot(r$t[,4],type='p',ylab='simulated values',main='Simulation of Mode')grid()dev.off()bitmap(file='plot8.png')plot(r$t[,5],type='p',ylab='simulated values',main='Simulation of Mode of Kernel Density')grid()dev.off()bitmap(file='plot4.png')densityplot(~r$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()bitmap(file='plot9.png')densityplot(~r$t[,4],col='black',main='Density Plot',xlab='mode')dev.off()bitmap(file='plot10.png')densityplot(~r$t[,5],col='black',main='Density Plot',xlab='mode of kernel dens.')dev.off()z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3],r$t[,4],r$t[,5]))colnames(z) <- list('mean','median','midrange','mode','mode k.dens')bitmap(file='plot11.png')boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')grid()dev.off()load(file='createtable')a<-table.start()a<-table.row.start(a)a<-table.element(a,'Estimation Results of Bootstrap',10,TRUE)a<-table.row.end(a)if (par4 == 'P1 P5 Q1 Q3 P95 P99') {myq.1 <- 0.01myq.2 <- 0.05myq.3 <- 0.95myq.4 <- 0.99myl.1 <- 'P1'myl.2 <- 'P5'myl.3 <- 'P95'myl.4 <- 'P99'}if (par4 == 'P0.5 P2.5 Q1 Q3 P97.5 P99.5') {myq.1 <- 0.005myq.2 <- 0.025myq.3 <- 0.975myq.4 <- 0.995myl.1 <- 'P0.5'myl.2 <- 'P2.5'myl.3 <- 'P97.5'myl.4 <- 'P99.5'}if (par4 == 'P10 P20 Q1 Q3 P80 P90') {myq.1 <- 0.10myq.2 <- 0.20myq.3 <- 0.80myq.4 <- 0.90myl.1 <- 'P10'myl.2 <- 'P20'myl.3 <- 'P80'myl.4 <- 'P90'}a<-table.row.start(a)a<-table.element(a,'statistic',header=TRUE)a<-table.element(a,myl.1,header=TRUE)a<-table.element(a,myl.2,header=TRUE)a<-table.element(a,'Q1',header=TRUE)a<-table.element(a,'Estimate',header=TRUE)a<-table.element(a,'Q3',header=TRUE)a<-table.element(a,myl.3,header=TRUE)a<-table.element(a,myl.4,header=TRUE)a<-table.element(a,'S.D.',header=TRUE)a<-table.element(a,'IQR',header=TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'mean',header=TRUE)q1 <- quantile(r$t[,1],0.25)[[1]]q3 <- quantile(r$t[,1],0.75)[[1]]p01 <- quantile(r$t[,1],myq.1)[[1]]p05 <- quantile(r$t[,1],myq.2)[[1]]p95 <- quantile(r$t[,1],myq.3)[[1]]p99 <- quantile(r$t[,1],myq.4)[[1]]a<-table.element(a,signif(p01,par2))a<-table.element(a,signif(p05,par2))a<-table.element(a,signif(q1,par2))a<-table.element(a,signif(r$t0[1],par2))a<-table.element(a,signif(q3,par2))a<-table.element(a,signif(p95,par2))a<-table.element(a,signif(p99,par2))a<-table.element( a,signif( sqrt(var(r$t[,1])),par2 ) )a<-table.element(a,signif(q3-q1,par2))a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'median',header=TRUE)q1 <- quantile(r$t[,2],0.25)[[1]]q3 <- quantile(r$t[,2],0.75)[[1]]p01 <- quantile(r$t[,2],myq.1)[[1]]p05 <- quantile(r$t[,2],myq.2)[[1]]p95 <- quantile(r$t[,2],myq.3)[[1]]p99 <- quantile(r$t[,2],myq.4)[[1]]a<-table.element(a,signif(p01,par2))a<-table.element(a,signif(p05,par2))a<-table.element(a,signif(q1,par2))a<-table.element(a,signif(r$t0[2],par2))a<-table.element(a,signif(q3,par2))a<-table.element(a,signif(p95,par2))a<-table.element(a,signif(p99,par2))a<-table.element(a,signif(sqrt(var(r$t[,2])),par2))a<-table.element(a,signif(q3-q1,par2))a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'midrange',header=TRUE)q1 <- quantile(r$t[,3],0.25)[[1]]q3 <- quantile(r$t[,3],0.75)[[1]]p01 <- quantile(r$t[,3],myq.1)[[1]]p05 <- quantile(r$t[,3],myq.2)[[1]]p95 <- quantile(r$t[,3],myq.3)[[1]]p99 <- quantile(r$t[,3],myq.4)[[1]]a<-table.element(a,signif(p01,par2))a<-table.element(a,signif(p05,par2))a<-table.element(a,signif(q1,par2))a<-table.element(a,signif(r$t0[3],par2))a<-table.element(a,signif(q3,par2))a<-table.element(a,signif(p95,par2))a<-table.element(a,signif(p99,par2))a<-table.element(a,signif(sqrt(var(r$t[,3])),par2))a<-table.element(a,signif(q3-q1,par2))a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'mode',header=TRUE)q1 <- quantile(r$t[,4],0.25)[[1]]q3 <- quantile(r$t[,4],0.75)[[1]]p01 <- quantile(r$t[,4],myq.1)[[1]]p05 <- quantile(r$t[,4],myq.2)[[1]]p95 <- quantile(r$t[,4],myq.3)[[1]]p99 <- quantile(r$t[,4],myq.4)[[1]]a<-table.element(a,signif(p01,par2))a<-table.element(a,signif(p05,par2))a<-table.element(a,signif(q1,par2))a<-table.element(a,signif(r$t0[4],par2))a<-table.element(a,signif(q3,par2))a<-table.element(a,signif(p95,par2))a<-table.element(a,signif(p99,par2))a<-table.element(a,signif(sqrt(var(r$t[,4])),par2))a<-table.element(a,signif(q3-q1,par2))a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'mode k.dens',header=TRUE)q1 <- quantile(r$t[,5],0.25)[[1]]q3 <- quantile(r$t[,5],0.75)[[1]]p01 <- quantile(r$t[,5],myq.1)[[1]]p05 <- quantile(r$t[,5],myq.2)[[1]]p95 <- quantile(r$t[,5],myq.3)[[1]]p99 <- quantile(r$t[,5],myq.4)[[1]]a<-table.element(a,signif(p01,par2))a<-table.element(a,signif(p05,par2))a<-table.element(a,signif(q1,par2))a<-table.element(a,signif(r$t0[5],par2))a<-table.element(a,signif(q3,par2))a<-table.element(a,signif(p95,par2))a<-table.element(a,signif(p99,par2))a<-table.element(a,signif(sqrt(var(r\$t[,5])),par2))a<-table.element(a,signif(q3-q1,par2))a<-table.row.end(a)a<-table.end(a)table.save(a,file='mytable.tab')