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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 computationWed, 24 Nov 2010 16:09:01 +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/24/t1290615749pglg8ag6yjkx7c1.htm/, Retrieved Fri, 03 May 2024 10:23:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=100382, Retrieved Fri, 03 May 2024 10:23:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140

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]
- RMPD      [Blocked Bootstrap Plot - Central Tendency] [] [2010-11-24 16:09:01] [b7dd4adfab743bef2d672ff51f950617] [Current]
-    D        [Blocked Bootstrap Plot - Central Tendency] [mini-tutorial link 2] [2010-11-26 14:14:10] [cc4c09289ddf8962388fdbedfd8171c3]
- R  D        [Blocked Bootstrap Plot - Central Tendency] [mini-tutorial] [2010-11-26 14:18:33] [2db53827eae1799a3d605fb62e1e92dc]
- RMPD        [Percentiles] [mini-tutorial] [2010-11-26 14:31:38] [2db53827eae1799a3d605fb62e1e92dc]
- R PD        [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2011-11-17 14:17:42] [9c3137400ced3280b419f1e434c29e1d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
22631
23956
23284
24334
24319
25252
24427
25434
25496
26681
25624
26706
25834
26513
26005
27158
26521
27652
26566
27597
27605
28621
27090
27652
28440
29076
27326
28477
29303
29301
27972
29247
29871
30079
28873
30897
30902
31321
29714
32006
31338
32562
31024
32678
33031
34115
32574
33984
34795
35680
34342
36136
36226
36226
34736
36588
45176
38351
36629
38146
39232
39257
37869
38394
40681
40797
39500
41366
42270
43536
42109
45262
46406
46275
44171
47037

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100382&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]1 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=100382&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100382&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean31328.453947368432556.078947368434005.25986842112085.38850124282676.80592105263
median2927430963339843058.813417992044710

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 31328.4539473684 & 32556.0789473684 & 34005.2598684211 & 2085.3885012428 & 2676.80592105263 \tabularnewline
median & 29274 & 30963 & 33984 & 3058.81341799204 & 4710 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100382&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]31328.4539473684[/C][C]32556.0789473684[/C][C]34005.2598684211[/C][C]2085.3885012428[/C][C]2676.80592105263[/C][/ROW]
[ROW][C]median[/C][C]29274[/C][C]30963[/C][C]33984[/C][C]3058.81341799204[/C][C]4710[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100382&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100382&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
mean31328.453947368432556.078947368434005.25986842112085.38850124282676.80592105263
median2927430963339843058.813417992044710






95% Confidence Intervals
MeanMedian
Lower Bound32393.37063502230988.1925865008
Upper Bound32771.681996556931653.8074134992

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 32393.370635022 & 30988.1925865008 \tabularnewline
Upper Bound & 32771.6819965569 & 31653.8074134992 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100382&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]32393.370635022[/C][C]30988.1925865008[/C][/ROW]
[ROW][C]Upper Bound[/C][C]32771.6819965569[/C][C]31653.8074134992[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100382&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100382&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 Bound32393.37063502230988.1925865008
Upper Bound32771.681996556931653.8074134992


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 4 ;
Parameters (R input):
par1 = 500 ; par2 = 4 ;
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')