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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 computationTue, 18 Aug 2009 16:21:11 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Aug/19/t1250634137gdj58vsieuvtba7.htm/, Retrieved Tue, 07 May 2024 15:17:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42904, Retrieved Tue, 07 May 2024 15:17:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [opgave 7 - oefeni...] [2009-05-13 06:33:26] [92e5d5bf28178acf91a63035e9cc5b92]
-   P   [Bootstrap Plot - Central Tendency] [opgave 7 - oefeni...] [2009-06-01 12:09:11] [74be16979710d4c4e7c6647856088456]
-   PD      [Bootstrap Plot - Central Tendency] [] [2009-08-18 22:21:11] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- RMPD        [Variability] [] [2009-08-18 22:50:36] [3277f4fd1367f73c9bc433502ffbb1d3]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6430
5124
4836
4629
4597
4490
4517
4560
4135
4559
4739
4886
5605
4616
4997
4607
4882
4555
4462
4476
4277
4369
4492
5183
6039
4923
4953
4892
4614
4363
4675
4556
4217
4664
4601
5428
5607
4869
5174
5031
4671
4491
4504
4615
4582
4800
4775
5791
5818
4714
4915
4598
4407
4383
4412
4274
4236
4637
4534
5271
5467
5204
5752
4724
4623
4451
4138
4140
4169
4603
4434
5185

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42904&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42904&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42904&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Estimation Results of Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean4741.461805555564777.041666666674814.2916666666755.152165318987672.8298611111113
median4610.54619.54650.539.787893135254340
midrange50875282.55284122.526974276917197

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 4741.46180555556 & 4777.04166666667 & 4814.29166666667 & 55.1521653189876 & 72.8298611111113 \tabularnewline
median & 4610.5 & 4619.5 & 4650.5 & 39.7878931352543 & 40 \tabularnewline
midrange & 5087 & 5282.5 & 5284 & 122.526974276917 & 197 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42904&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]4741.46180555556[/C][C]4777.04166666667[/C][C]4814.29166666667[/C][C]55.1521653189876[/C][C]72.8298611111113[/C][/ROW]
[ROW][C]median[/C][C]4610.5[/C][C]4619.5[/C][C]4650.5[/C][C]39.7878931352543[/C][C]40[/C][/ROW]
[ROW][C]midrange[/C][C]5087[/C][C]5282.5[/C][C]5284[/C][C]122.526974276917[/C][C]197[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42904&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42904&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
mean4741.461805555564777.041666666674814.2916666666755.152165318987672.8298611111113
median4610.54619.54650.539.787893135254340
midrange50875282.55284122.526974276917197


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')