FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot1.wasp
Title produced by softwareBootstrap Plot - Central Tendency
Date of computationThu, 04 Jun 2009 09:33:12 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jun/04/t1244129621dnhptoxjyc8mcgc.htm/, Retrieved Tue, 14 May 2024 14:09:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41710, Retrieved Tue, 14 May 2024 14:09:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bootstrap Plot - Central Tendency] [bootstrapplot] [2009-06-04 15:33:12] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D    [Bootstrap Plot - Central Tendency] [opgave 7 dennis gys] [2009-06-05 13:31:33] [74be16979710d4c4e7c6647856088456]
- RMPD    [Classical Decomposition] [opgave9W.Verlinden] [2009-06-05 13:55:11] [74be16979710d4c4e7c6647856088456]
-           [Classical Decomposition] [opgave 9 Dennis Gys] [2009-06-06 11:11:29] [74be16979710d4c4e7c6647856088456]
-    D        [Classical Decomposition] [opgave 9(2) denni...] [2009-06-06 11:16:53] [74be16979710d4c4e7c6647856088456]
-   PD    [Bootstrap Plot - Central Tendency] [opgave 7(2) denni...] [2009-06-05 13:56:25] [74be16979710d4c4e7c6647856088456]
- RMP     [Classical Decomposition] [opgave9bW.Verlinden] [2009-06-05 14:07:30] [74be16979710d4c4e7c6647856088456]
- RMPD    [Exponential Smoothing] [opgave10W.Verlinden] [2009-06-05 15:07:33] [74be16979710d4c4e7c6647856088456]
-           [Exponential Smoothing] [opgave 10 dennis gys] [2009-06-06 11:28:51] [74be16979710d4c4e7c6647856088456]
-    D        [Exponential Smoothing] [opgave 10(2) denn...] [2009-06-06 11:35:11] [74be16979710d4c4e7c6647856088456]
- RMP     [Exponential Smoothing] [opgave10bW.Verlinden] [2009-06-05 15:15:35] [74be16979710d4c4e7c6647856088456]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
665272
661735
621014
574889
677734
717075
653612
690697
665864
830701
789303
617808
805775
909449
599973
955874
799494
876097
823300
900079
860754
923882
1121084
741757
966066
901978
648659
852732
706036
835792
722489
714262
739459
816834
743082
683375
1006000
866000
644000
703000
699000
713000
688000
672000
600000
847000
697000
687000
973000
796000
658000
709000
798000
820000
776000
699000
828433
942131
792916
864942
982689
948143
874863
735794
854605
1284216
961585
818379
1079498
1095091
1008925
967118
1127715

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'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=41710&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=41710&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41710&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'George Udny Yule' @ 72.249.76.132






Estimation Results of Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean793419.619863014808657.93150685818146.02054794515774.290931846024726.4006849315
median77600079800080577528058.223147234429775
midrange854440.875929552.5929552.541709.312665380575111.625

\begin{tabular}{lllllllll}
\hline
Estimation Results of Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 793419.619863014 & 808657.93150685 & 818146.020547945 & 15774.2909318460 & 24726.4006849315 \tabularnewline
median & 776000 & 798000 & 805775 & 28058.2231472344 & 29775 \tabularnewline
midrange & 854440.875 & 929552.5 & 929552.5 & 41709.3126653805 & 75111.625 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41710&T=1

[TABLE]
[ROW][C]Estimation Results of 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]793419.619863014[/C][C]808657.93150685[/C][C]818146.020547945[/C][C]15774.2909318460[/C][C]24726.4006849315[/C][/ROW]
[ROW][C]median[/C][C]776000[/C][C]798000[/C][C]805775[/C][C]28058.2231472344[/C][C]29775[/C][/ROW]
[ROW][C]midrange[/C][C]854440.875[/C][C]929552.5[/C][C]929552.5[/C][C]41709.3126653805[/C][C]75111.625[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41710&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41710&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 Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean793419.619863014808657.93150685818146.02054794515774.290931846024726.4006849315
median77600079800080577528058.223147234429775
midrange854440.875929552.5929552.541709.312665380575111.625


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ;
Parameters (R input):
par1 = 50 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
if (par1 < 10) par1 = 10
if (par1 > 5000) par1 = 5000
library(lattice)
library(boot)
boot.stat <- function(s,i)
{
s.mean <- mean(s[i])
s.median <- median(s[i])
s.midrange <- (max(s[i]) + min(s[i])) / 2
c(s.mean, s.median, s.midrange)
}
(r <- boot(x,boot.stat, R=par1, stype='i'))
bitmap(file='plot1.png')
plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
grid()
dev.off()
bitmap(file='plot2.png')
plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
grid()
dev.off()
bitmap(file='plot3.png')
plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
grid()
dev.off()
bitmap(file='plot4.png')
densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
dev.off()
bitmap(file='plot5.png')
densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
dev.off()
bitmap(file='plot6.png')
densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
dev.off()
z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3]))
colnames(z) <- list('mean','median','midrange')
bitmap(file='plot7.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Bootstrap',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$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$t[,2])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'midrange',header=TRUE)
q1 <- quantile(r$t[,3],0.25)[[1]]
q3 <- quantile(r$t[,3],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[3])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,3])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')