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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 computationMon, 22 Dec 2008 13:20:16 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/22/t1229977281f69u5v1374rong6.htm/, Retrieved Thu, 25 Apr 2024 08:07:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36207, Retrieved Thu, 25 Apr 2024 08:07:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact211

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]
-    D    [Blocked Bootstrap Plot - Central Tendency] [Notched Plot - Ma...] [2008-12-21 15:20:06] [33f4701c7363e8b81858dafbf0350eed]
-    D        [Blocked Bootstrap Plot - Central Tendency] [notched plot - ma...] [2008-12-22 20:20:16] [77ff908fa699164c8765f2430a4f222b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.1
100.7
100
100
100.8
101.9
102.7
103.1
103.5
103.9
104.4
105.2
106
107
108.2
109
109.1
109.3
110.1
110.7
110.8
110.7
110.9
111.3
111.6
111.8
112.1
112.3
112.5
113
113.6
114.4
114.9
115.2
116
117
118
119.4
121.1
123.1
125
126.3
127.4
129
131
133.3
135.9
138.4
140.3
141.7
143.1
144.5
146
147.7
149
149.7
150.2
150.5
150.7
150.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36207&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36207&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36207&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean116.670416666667119.95124.1516666666675.535918153807537.48125
median111.1113.3120.258.305490360614519.15

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 116.670416666667 & 119.95 & 124.151666666667 & 5.53591815380753 & 7.48125 \tabularnewline
median & 111.1 & 113.3 & 120.25 & 8.30549036061451 & 9.15 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36207&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]116.670416666667[/C][C]119.95[/C][C]124.151666666667[/C][C]5.53591815380753[/C][C]7.48125[/C][/ROW]
[ROW][C]median[/C][C]111.1[/C][C]113.3[/C][C]120.25[/C][C]8.30549036061451[/C][C]9.15[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36207&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36207&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
mean116.670416666667119.95124.1516666666675.535918153807537.48125
median111.1113.3120.258.305490360614519.15






95% Confidence Intervals
MeanMedian
Lower Bound119.867637681273112.653463304986
Upper Bound120.932362318727113.946536695014

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 119.867637681273 & 112.653463304986 \tabularnewline
Upper Bound & 120.932362318727 & 113.946536695014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36207&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]119.867637681273[/C][C]112.653463304986[/C][/ROW]
[ROW][C]Upper Bound[/C][C]120.932362318727[/C][C]113.946536695014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36207&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36207&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 Bound119.867637681273112.653463304986
Upper Bound120.932362318727113.946536695014


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')