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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 computationMon, 29 Nov 2010 20:36:56 +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/29/t129106298773fbaefw7xpad41.htm/, Retrieved Mon, 29 Apr 2024 08:55:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=103101, Retrieved Mon, 29 Apr 2024 08:55:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W22
Estimated Impact120

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] [Bootstrap plot op...] [2010-11-29 20:36:56] [bf26e49ed6e1a435b77b49c7144b8136] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
96,1
96,5
96,9
97,8
98,9
100,2
101,2
101
101,6
102,4
103,7
103,7
104,6
104,5
104,5
105,6
106,1
107,6
107,7
108,3
108,1
108,1
108
108,2
108,9
109,8
109,9
109,8
110,9
111,1
112,2
112,7
114,6
114,2
114,7
114,7
116
116,3
116,4
116,6
118,1
117,2
108,3
109,5
110,5
110,6
111,2
111,1
111
112,4
112,5
112,4
111,8
111,6
112,9
112,8
113,7
113,8
114
113,8
113,9
114,4
114,4
114,5
113,8
114,3
115
115,4
115,3
114,9
114,3
114,5
115,5
115,8
115,8
116
114,9
114,1
114,1
113,5
115
114,7
115,4
116,1
116,6
117,2
118,2
118
117,7
118,5
117,5
118
117,7
116,3
115
115,7
113,6
114,8
114,9
117,3
117,3
117,7
120
119,6
119,2
117,3
117,5
119
112,5
118,9
118,4
119,4
120,6
118,6
122
122,6
120,6
117,4
116,4
122,2
121
122,4
124,9
126,1
124,5
123,2
126,4
123,9
116
126,6
125,9
126,6
116,7
126,4
129
128,7
128,4
129,2
133,3
128,9
132,7
127,7
131,8
133,9

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'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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103101&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103101&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103101&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Estimation Results of Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean114.495659722222115.092361111111115.3743055555560.6403144448025430.878645833333323
median114.7114.951150.4053771234849080.299999999999997
midrange114.7115115.20.3333564617826470.5

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 114.495659722222 & 115.092361111111 & 115.374305555556 & 0.640314444802543 & 0.878645833333323 \tabularnewline
median & 114.7 & 114.95 & 115 & 0.405377123484908 & 0.299999999999997 \tabularnewline
midrange & 114.7 & 115 & 115.2 & 0.333356461782647 & 0.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103101&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]114.495659722222[/C][C]115.092361111111[/C][C]115.374305555556[/C][C]0.640314444802543[/C][C]0.878645833333323[/C][/ROW]
[ROW][C]median[/C][C]114.7[/C][C]114.95[/C][C]115[/C][C]0.405377123484908[/C][C]0.299999999999997[/C][/ROW]
[ROW][C]midrange[/C][C]114.7[/C][C]115[/C][C]115.2[/C][C]0.333356461782647[/C][C]0.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103101&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103101&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
mean114.495659722222115.092361111111115.3743055555560.6403144448025430.878645833333323
median114.7114.951150.4053771234849080.299999999999997
midrange114.7115115.20.3333564617826470.5


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ;
Parameters (R input):
par1 = 50 ;
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')