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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationFri, 12 Nov 2010 16:15:32 +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/12/t1289578467wl5hyrtnwapcjr5.htm/, Retrieved Tue, 30 Apr 2024 13:35:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=94228, Retrieved Tue, 30 Apr 2024 13:35:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Blocked Bootstrap Plot - Central Tendency] [Colombia Coffee] [2008-01-07 10:26:26] [74be16979710d4c4e7c6647856088456]
- RM D      [Blocked Bootstrap Plot - Central Tendency] [] [2010-11-12 16:15:32] [1d094c42a82a95b45a19e32ad4bfff5f] [Current]
-    D        [Blocked Bootstrap Plot - Central Tendency] [] [2010-11-14 16:56:02] [d39e5c40c631ed6c22677d2e41dbfc7d]
-    D          [Blocked Bootstrap Plot - Central Tendency] [] [2010-11-15 15:26:22] [d39e5c40c631ed6c22677d2e41dbfc7d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
90
80
100
96
100
91
81
80
100
94
100
80
100
90
100
100
100
90
97
90
86
100
100
82
90
94
100
95
100
88
80
81
100
100
100
100
95
100
90
90
100
85
98
91
90
70
100
83
100
100
100
100
100
100
86
100
100
100
100
100
76
100
100
100
100
80
100
100
100
89
100
90
90
95
95
99
90
90
100
100
90
100
81
100
100
98
96
90
90
100
100
88
73
85
100
100
99
90
100
100
100
91
96
80
100
85
90
100
94
95
96
80
100
82
90
100
90
100
100
94
90
79
95
100
91
100
100
76
87
95
71
100
100
100
92
93
80
100
80
90
100
100
100
99
85
100
100
85
100
100

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94228&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94228&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94228&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 time9 seconds
R Server'George Udny Yule' @ 72.249.76.132






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean93.3893.7294.00166666666670.4603542324423050.62166666666667
median9697.5991.859284237482673

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 93.38 & 93.72 & 94.0016666666667 & 0.460354232442305 & 0.62166666666667 \tabularnewline
median & 96 & 97.5 & 99 & 1.85928423748267 & 3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94228&T=1

[TABLE]
[ROW][C]Estimation Results of Blocked 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]93.38[/C][C]93.72[/C][C]94.0016666666667[/C][C]0.460354232442305[/C][C]0.62166666666667[/C][/ROW]
[ROW][C]median[/C][C]96[/C][C]97.5[/C][C]99[/C][C]1.85928423748267[/C][C]3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94228&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94228&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 Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean93.3893.7294.00166666666670.4603542324423050.62166666666667
median9697.5991.859284237482673






95% Confidence Intervals
MeanMedian
Lower Bound93.649288757024596.788020755733
Upper Bound93.737377909642197.211979244267

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 93.6492887570245 & 96.788020755733 \tabularnewline
Upper Bound & 93.7373779096421 & 97.211979244267 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=94228&T=2

[TABLE]
[ROW][C]95% Confidence Intervals[/C][/ROW]
[ROW][C][/C][C]Mean[/C][C]Median[/C][/ROW]
[ROW][C]Lower Bound[/C][C]93.6492887570245[/C][C]96.788020755733[/C][/ROW]
[ROW][C]Upper Bound[/C][C]93.7373779096421[/C][C]97.211979244267[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=94228&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=94228&T=2

As an alternative you can also use a QR Code:  
QR Code


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

95% Confidence Intervals
MeanMedian
Lower Bound93.649288757024596.788020755733
Upper Bound93.737377909642197.211979244267


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 12 ;
Parameters (R input):
par1 = 500 ; par2 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1 < 10) par1 = 10
if (par1 > 5000) par1 = 5000
if (par2 < 3) par2 = 3
if (par2 > length(x)) par2 = length(x)
library(lattice)
library(boot)
boot.stat <- function(s)
{
s.mean <- mean(s)
s.median <- median(s)
c(s.mean, s.median)
}
(r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed'))
z <- data.frame(cbind(r$t[,1],r$t[,2]))
colnames(z) <- list('mean','median')
bitmap(file='plot7.png')
b <- boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
b
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Blocked 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.end(a)
table.save(a,file='mytable.tab')

a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'95% Confidence Intervals',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Mean',1,TRUE)
a<-table.element(a,'Median',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lower Bound',1,TRUE)
a<-table.element(a,b$conf[1,1])
a<-table.element(a,b$conf[1,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Upper Bound',1,TRUE)
a<-table.element(a,b$conf[2,1])
a<-table.element(a,b$conf[2,2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')