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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationMon, 21 Nov 2011 06:21:19 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/21/t1321874516611v1no4socc5c8.htm/, Retrieved Fri, 26 Apr 2024 01:32:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=145701, Retrieved Fri, 26 Apr 2024 01:32:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142

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] [Paper] [2011-11-21 11:21:19] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D        [Blocked Bootstrap Plot - Central Tendency] [Paper] [2011-12-12 10:21:34] [aa6b3f8e5b050429abaad141c7204e84]
-    D          [Blocked Bootstrap Plot - Central Tendency] [paper] [2011-12-12 10:38:37] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
68.897 
 38.683 
 44.720 
 39.525 
 45.315 
 50.380 
 40.600 
 36.279 
 42.438 
 38.064 
 31.879 
 11.379 
 70.249 
 39.253 
 47.060 
 41.697 
 38.708 
 49.267 
 39.018 
 32.228 
 40.870 
 39.383 
 34.571 
 12.066 
 70.938 
 34.077 
 45.409 
 40.809 
 37.013 
 44.953 
 37.848 
 32.745 
 39.401 
 34.931 
 33.008 
 8.620 
 68.906 
 39.556 
 50.669 
 36.432 
 40.891 
 48.428 
 36.222 
 33.425 
 39.401 
 37.967 
 34.801 
 12.657 
 69.116 
 41.519 
 51.321 
 38.529 
 41.547 
 52.073 
 38.401 
 40.898 
 40.439 
 41.888 
 37.898 
 8.771 
 68.184 
 50.530 
 47.221 
 41.756 
 45.633 
 48.138 
 39.486 
 39.341 
 41.117 
 41.629 
 29.722 
 7.054 
 56.676 
 34.870 
 35.117 
 30.169 
 30.936 
 35.699 
 33.228 
 27.733 
 33.666 
 35.429 
 27.438 
 8.170 
 63.410 
 38.040 
 45.389 
 37.353 
 37.024 
 50.957 
 37.994 
 36.454 
 46.080 
 43.373 
 37.395

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'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145701&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145701&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145701&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'Gwilym Jenkins' @ jenkins.wessa.net






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean39.102394736842139.752073684210540.43674473684211.065275099576781.33434999999999
median38.68339.34139.4860.9736848550171560.802999999999997

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 39.1023947368421 & 39.7520736842105 & 40.4367447368421 & 1.06527509957678 & 1.33434999999999 \tabularnewline
median & 38.683 & 39.341 & 39.486 & 0.973684855017156 & 0.802999999999997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145701&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]39.1023947368421[/C][C]39.7520736842105[/C][C]40.4367447368421[/C][C]1.06527509957678[/C][C]1.33434999999999[/C][/ROW]
[ROW][C]median[/C][C]38.683[/C][C]39.341[/C][C]39.486[/C][C]0.973684855017156[/C][C]0.802999999999997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145701&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145701&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
mean39.102394736842139.752073684210540.43674473684211.065275099576781.33434999999999
median38.68339.34139.4860.9736848550171560.802999999999997






95% Confidence Intervals
MeanMedian
Lower Bound39.720257998191239.2842602222845
Upper Bound39.908857791282539.3977397777155

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 39.7202579981912 & 39.2842602222845 \tabularnewline
Upper Bound & 39.9088577912825 & 39.3977397777155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=145701&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]39.7202579981912[/C][C]39.2842602222845[/C][/ROW]
[ROW][C]Upper Bound[/C][C]39.9088577912825[/C][C]39.3977397777155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=145701&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=145701&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 Bound39.720257998191239.2842602222845
Upper Bound39.908857791282539.3977397777155


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')