## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software Modulerwasp_bootstrapplot1.wasp
Title produced by softwareBootstrap Plot - Central Tendency
Date of computationWed, 22 Dec 2010 17:51:05 +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/Dec/22/t1293040140cqttp5id2y3otzk.htm/, Retrieved Wed, 29 Nov 2023 00:00:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114440, Retrieved Wed, 29 Nov 2023 00:00:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Arabica Price in ...] [2008-01-05 23:43:18] [74be16979710d4c4e7c6647856088456]
- RMPD  [Histogram] [histogram inflatie] [2010-12-22 13:21:55] [96348ef82925ade81ab3c243141d80f1]
-    D    [Histogram] [Historgram Inflatie] [2010-12-22 14:20:36] [30b3e197115d238a51c18bcedc33a6a5]
- RMPD      [Bootstrap Plot - Central Tendency] [blocked bootstrap] [2010-12-22 14:35:50] [30b3e197115d238a51c18bcedc33a6a5]
-    D          [Bootstrap Plot - Central Tendency] [notched boxplots ...] [2010-12-22 17:51:05] [03bcd8c83ef1a42b4029a16ba47a4880] [Current]
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Dataseries X:
192,37
192,65
193,77
194,54
198,63
202,3
206,05
210,94
220,57
228,55
235,61
239,86
243,05
241,37
249,31
259,98
262,85
273,13
278,37
288,19
299,13
301,26
305,36
307,75
317,2
323,6
332,31
341,59
344,3
335,17


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 4 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=114440&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=114440&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114440&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 4 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk

 Estimation Results of Bootstrap statistic Q1 Estimate Q3 S.D. IQR mean 255.101333333333 260.658666666667 266.83 9.63566524635776 11.7286666666666 median 243.05 254.645 267.99 16.86277304835 24.94 midrange 266.98 268.335 268.335 2.3039851310432 1.35500000000002

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 255.101333333333 & 260.658666666667 & 266.83 & 9.63566524635776 & 11.7286666666666 \tabularnewline
median & 243.05 & 254.645 & 267.99 & 16.86277304835 & 24.94 \tabularnewline
midrange & 266.98 & 268.335 & 268.335 & 2.3039851310432 & 1.35500000000002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114440&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]255.101333333333[/C][C]260.658666666667[/C][C]266.83[/C][C]9.63566524635776[/C][C]11.7286666666666[/C][/ROW]
[ROW][C]median[/C][C]243.05[/C][C]254.645[/C][C]267.99[/C][C]16.86277304835[/C][C]24.94[/C][/ROW]
[ROW][C]midrange[/C][C]266.98[/C][C]268.335[/C][C]268.335[/C][C]2.3039851310432[/C][C]1.35500000000002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114440&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114440&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 Q1 Estimate Q3 S.D. IQR mean 255.101333333333 260.658666666667 266.83 9.63566524635776 11.7286666666666 median 243.05 254.645 267.99 16.86277304835 24.94 midrange 266.98 268.335 268.335 2.3039851310432 1.35500000000002

par1 <- as.numeric(par1)if (par1 < 10) par1 = 10if (par1 > 5000) par1 = 5000library(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])) / 2c(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')