## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationThu, 18 Dec 2008 09:26:44 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/18/t1229617652fv59ertn6n23blz.htm/, Retrieved Wed, 27 Sep 2023 07:55:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34878, Retrieved Wed, 27 Sep 2023 07:55:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact224
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]
- R  D    [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2008-12-17 18:55:16] [7458e879e85b911182071700fff19fbd]
F    D        [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Simulat...] [2008-12-18 16:26:44] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D          [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Bel-20 ...] [2008-12-21 13:33:26] [513002e53792b228fd07c821aaa4d786]
Feedback Forum
 2009-01-01 21:50:06 [Kenny Simons] [reply] Hier zie je ook duidelijk dat de median meer beïnvloed wordt door outliers als de mean. (De bolletjes die niet binnen de streepjes liggen, stellen de outliers voor, aan de hand van de streepjes kan je zien dat de gegevens evenredig verdeeld zijn of niet)

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Dataseries X:
29.59
30.7
30.52
32.67
33.19
37.13
35.54
37.75
41.84
42.94
49.14
44.61
40.22
44.23
45.85
53.38
53.26
51.8
55.3
57.81
63.96
63.77
59.15
56.12
57.42
63.52
61.71
63.01
68.18
72.03
69.75
74.41
74.33
64.24
60.03
59.44
62.5
55.04
58.34
61.92
67.65
67.68
70.3
75.26
71.44
76.36
81.71
92.6
90.6
92.23
94.09
102.79
109.65
124.05
132.69
135.81
116.07
101.42
75.73
55.48

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34878&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34878&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34878&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

 Estimation Results of Blocked Bootstrap statistic Q1 Estimate Q3 S.D. IQR mean 60.447375 65.8325 71.292125 7.99831906884375 10.84475 median 58.745 62.21 67.65 7.8841893656232 8.905

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 60.447375 & 65.8325 & 71.292125 & 7.99831906884375 & 10.84475 \tabularnewline
median & 58.745 & 62.21 & 67.65 & 7.8841893656232 & 8.905 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34878&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]60.447375[/C][C]65.8325[/C][C]71.292125[/C][C]7.99831906884375[/C][C]10.84475[/C][/ROW]
[ROW][C]median[/C][C]58.745[/C][C]62.21[/C][C]67.65[/C][C]7.8841893656232[/C][C]8.905[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34878&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34878&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 statistic Q1 Estimate Q3 S.D. IQR mean 60.447375 65.8325 71.292125 7.99831906884375 10.84475 median 58.745 62.21 67.65 7.8841893656232 8.905

 95% Confidence Intervals Mean Median Lower Bound 64.5824990818834 61.5807749432675 Upper Bound 66.1206675847833 62.8392250567325

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
& Mean & Median \tabularnewline
Lower Bound & 64.5824990818834 & 61.5807749432675 \tabularnewline
Upper Bound & 66.1206675847833 & 62.8392250567325 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34878&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]64.5824990818834[/C][C]61.5807749432675[/C][/ROW]
[ROW][C]Upper Bound[/C][C]66.1206675847833[/C][C]62.8392250567325[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34878&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34878&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 Mean Median Lower Bound 64.5824990818834 61.5807749432675 Upper Bound 66.1206675847833 62.8392250567325

par1 <- as.numeric(par1)par2 <- as.numeric(par2)if (par1 < 10) par1 = 10if (par1 > 5000) par1 = 5000if (par2 < 3) par2 = 3if (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()bload(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')