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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 Nov 2010 21:52:53 +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/22/t1290462656jg6jvtbk1zg0ulc.htm/, Retrieved Sat, 04 May 2024 03:23:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=98755, Retrieved Sat, 04 May 2024 03:23:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118

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]
-  M D    [Blocked Bootstrap Plot - Central Tendency] [Xtboxplot] [2010-11-22 17:14:57] [8b2514d8f13517d765015fc185a22b4b]
-    D      [Blocked Bootstrap Plot - Central Tendency] [Xtboxplot1] [2010-11-22 20:39:07] [8b2514d8f13517d765015fc185a22b4b]
-   PD          [Blocked Bootstrap Plot - Central Tendency] [ws6Ytboxplot] [2010-11-22 21:52:53] [6e19356a8195a048e2417405f21c29e8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
145
621
262
208
362
424
339
736
291
58
498
643
390
332
750
368
659
234
396
300
343
536
543
217
298
1103
406
254
862
204
206
250
21
298
350
800
726
370
536
291
808
543
149
350
242
198
213
296
317
482
155
802
200
282
573
388
250
396
572

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98755&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98755&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98755&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean393.46186440678404.169491525424416.49576271186416.920446547145223.0338983050847
median33935036221.509554199092323

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 393.46186440678 & 404.169491525424 & 416.495762711864 & 16.9204465471452 & 23.0338983050847 \tabularnewline
median & 339 & 350 & 362 & 21.5095541990923 & 23 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98755&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]393.46186440678[/C][C]404.169491525424[/C][C]416.495762711864[/C][C]16.9204465471452[/C][C]23.0338983050847[/C][/ROW]
[ROW][C]median[/C][C]339[/C][C]350[/C][C]362[/C][C]21.5095541990923[/C][C]23[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98755&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98755&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
mean393.46186440678404.169491525424416.49576271186416.920446547145223.0338983050847
median33935036221.509554199092323






95% Confidence Intervals
MeanMedian
Lower Bound403.083097332186348.374825793953
Upper Bound406.340631481373351.625174206047

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 403.083097332186 & 348.374825793953 \tabularnewline
Upper Bound & 406.340631481373 & 351.625174206047 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98755&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]403.083097332186[/C][C]348.374825793953[/C][/ROW]
[ROW][C]Upper Bound[/C][C]406.340631481373[/C][C]351.625174206047[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98755&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98755&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 Bound403.083097332186348.374825793953
Upper Bound406.340631481373351.625174206047


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')