## 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 07:30:51 -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/t138771554072x7aqowqqwej3g.htm/, Retrieved Sat, 21 May 2022 16:33:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232508, Retrieved Sat, 21 May 2022 16:33:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
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 12:30:51] [54713e3426a13268f2edfca2b563126c] [Current]
Feedback Forum

Post a new message
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
20
20
20
20
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
25
25
25
20
30
25
22
30
20
20
30
25
25
30
20
25
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
20
25
25
35
22
20
25
20
20
18
20
22
25
10
20
25
20
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
40
25
30
20


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 97 seconds R Server 'Sir Maurice George Kendall' @ kendall.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 & 97 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232508&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]97 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232508&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232508&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 97 seconds R Server 'Sir Maurice George Kendall' @ kendall.wessa.net

 Estimation Results of Bootstrap statistic P1 P5 Q1 Estimate Q3 P95 P99 S.D. IQR mean 22.59 22.771 22.982 23.166 23.322 23.548 23.725 0.23994 0.33944 median 22 22 22 22 24.5 25 25 1.2961 2.5 midrange 27.5 27.5 27.5 35 35 35 36.5 3.5615 7.5 mode 25 25 25 25 25 25 25 0 0 mode k.dens 15 20 22.934 25 23 25 30 2.3477 0.066113

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & P1 & P5 & Q1 & Estimate & Q3 & P95 & P99 & S.D. & IQR \tabularnewline
mean & 22.59 & 22.771 & 22.982 & 23.166 & 23.322 & 23.548 & 23.725 & 0.23994 & 0.33944 \tabularnewline
median & 22 & 22 & 22 & 22 & 24.5 & 25 & 25 & 1.2961 & 2.5 \tabularnewline
midrange & 27.5 & 27.5 & 27.5 & 35 & 35 & 35 & 36.5 & 3.5615 & 7.5 \tabularnewline
mode & 25 & 25 & 25 & 25 & 25 & 25 & 25 & 0 & 0 \tabularnewline
mode k.dens & 15 & 20 & 22.934 & 25 & 23 & 25 & 30 & 2.3477 & 0.066113 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232508&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]22.59[/C][C]22.771[/C][C]22.982[/C][C]23.166[/C][C]23.322[/C][C]23.548[/C][C]23.725[/C][C]0.23994[/C][C]0.33944[/C][/ROW]
[ROW][C]median[/C][C]22[/C][C]22[/C][C]22[/C][C]22[/C][C]24.5[/C][C]25[/C][C]25[/C][C]1.2961[/C][C]2.5[/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]36.5[/C][C]3.5615[/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]15[/C][C]20[/C][C]22.934[/C][C]25[/C][C]23[/C][C]25[/C][C]30[/C][C]2.3477[/C][C]0.066113[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232508&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232508&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 22.59 22.771 22.982 23.166 23.322 23.548 23.725 0.23994 0.33944 median 22 22 22 22 24.5 25 25 1.2961 2.5 midrange 27.5 27.5 27.5 35 35 35 36.5 3.5615 7.5 mode 25 25 25 25 25 25 25 0 0 mode k.dens 15 20 22.934 25 23 25 30 2.3477 0.066113

par4 <- 'P1 P5 Q1 Q3 P95 P99'par3 <- '0'par2 <- '5'par1 <- '200'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')