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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 computationSat, 06 Nov 2010 16:42:34 +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/06/t1289061838b2t7bqwuzt1lak5.htm/, Retrieved Tue, 30 Apr 2024 13:46:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=92465, Retrieved Tue, 30 Apr 2024 13:46:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact191
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] [Bootstrap Car Sales] [2010-11-06 16:12:15] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
-    D        [Blocked Bootstrap Plot - Central Tendency] [Blocked bootstrap...] [2010-11-06 16:42:34] [9ea95e194e0eb2a674315798620d5bc6] [Current]
- R  D          [Blocked Bootstrap Plot - Central Tendency] [] [2011-11-15 16:54:29] [06c08141d7d783218a8164fd2ea166f2]
- R P           [Blocked Bootstrap Plot - Central Tendency] [] [2011-11-15 21:33:36] [ec2187f7727da5d5d939740b21b8b68a]
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Dataseries X:
12117
11597
12291
12461
13469
13448
13896
13846
13159
13682
13083
13507
12545
12076
13181
13395
14108
14017
14464
14139
13393
13979
13538
13752
12729
12308
13663
13660
14367
14737
15155
15616
14738
14872
14551
15020
13884
13224
14771
14645
15960
16223
16073
16233
15210
15173
14696
15202
14492
14176
15634
16043
17448
16975
17055
17286
15987
16682
16243
16580




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92465&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]2 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=92465&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92465&T=0

As an alternative you can also use a 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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean14131.358333333314440.914757.2375435.090344764028625.879166666666
median13894.514271.514716.5538.151805912992822

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 14131.3583333333 & 14440.9 & 14757.2375 & 435.090344764028 & 625.879166666666 \tabularnewline
median & 13894.5 & 14271.5 & 14716.5 & 538.151805912992 & 822 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92465&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]14131.3583333333[/C][C]14440.9[/C][C]14757.2375[/C][C]435.090344764028[/C][C]625.879166666666[/C][/ROW]
[ROW][C]median[/C][C]13894.5[/C][C]14271.5[/C][C]14716.5[/C][C]538.151805912992[/C][C]822[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92465&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92465&T=1

As an alternative you can also use a QR Code:  

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

Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean14131.358333333314440.914757.2375435.090344764028625.879166666666
median13894.514271.514716.5538.151805912992822







95% Confidence Intervals
MeanMedian
Lower Bound14362.999730584714117.8116974487
Upper Bound14451.683602748714234.1883025513

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 14362.9997305847 & 14117.8116974487 \tabularnewline
Upper Bound & 14451.6836027487 & 14234.1883025513 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92465&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]14362.9997305847[/C][C]14117.8116974487[/C][/ROW]
[ROW][C]Upper Bound[/C][C]14451.6836027487[/C][C]14234.1883025513[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92465&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92465&T=2

As an alternative you can also use a QR Code:  

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

95% Confidence Intervals
MeanMedian
Lower Bound14362.999730584714117.8116974487
Upper Bound14451.683602748714234.1883025513



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')