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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 computationTue, 15 Nov 2011 16:02:28 -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/15/t1321390959b7zqxsacjxpmho3.htm/, Retrieved Fri, 01 Nov 2024 00:10:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=143548, Retrieved Fri, 01 Nov 2024 00:10:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact249

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]
- RM D    [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Car Sales] [2010-11-06 16:12:15] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- R P         [Blocked Bootstrap Plot - Central Tendency] [] [2011-11-15 21:02:28] [542c32830549043c4555f1bd78aefedb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26862
28261
31761
32624
32950
34711
34124
31860
32404
33027
28944
29702
29144
29715
35710
37324
37687
39071
38986
37702
36444
36423
35266
35461
33073
35721
44670
43461
42998
45039
41555
43850
42253
42036
39552
38572
36862
37883
47264
43698
48335
50368
45633
48708
44588
44021
41601
39761
40848
45488
51253
49495
53348
50286
50191
50596
46689
49249
43597
41862

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=143548&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=143548&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=143548&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
mean38310.866666666740009.4541373.88752190.293839728563063.02083333333
median3768739656.5420362916.96084081324349

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 38310.8666666667 & 40009.45 & 41373.8875 & 2190.29383972856 & 3063.02083333333 \tabularnewline
median & 37687 & 39656.5 & 42036 & 2916.9608408132 & 4349 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=143548&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]38310.8666666667[/C][C]40009.45[/C][C]41373.8875[/C][C]2190.29383972856[/C][C]3063.02083333333[/C][/ROW]
[ROW][C]median[/C][C]37687[/C][C]39656.5[/C][C]42036[/C][C]2916.9608408132[/C][C]4349[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=143548&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=143548&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
mean38310.866666666740009.4541373.88752190.293839728563063.02083333333
median3768739656.5420362916.96084081324349






95% Confidence Intervals
MeanMedian
Lower Bound39746.441863705939176.700755561
Upper Bound40179.641469627439791.299244439

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 39746.4418637059 & 39176.700755561 \tabularnewline
Upper Bound & 40179.6414696274 & 39791.299244439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=143548&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]39746.4418637059[/C][C]39176.700755561[/C][/ROW]
[ROW][C]Upper Bound[/C][C]40179.6414696274[/C][C]39791.299244439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=143548&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=143548&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 Bound39746.441863705939176.700755561
Upper Bound40179.641469627439791.299244439


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
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')