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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 computationSun, 06 Jun 2010 20:18:25 +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/Jun/06/t1275855526c3d3l5rgxemq9eo.htm/, Retrieved Sun, 26 Oct 2025 03:33:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77793, Retrieved Sun, 26 Oct 2025 03:33:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact345

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Datareeks - Maand...] [2010-02-10 10:03:07] [718fc9b3d403b712b51e1f070e50e17e]
-   PD  [Univariate Data Series] [Maandelijkse bier...] [2010-06-06 12:41:45] [74be16979710d4c4e7c6647856088456]
- RMPD      [Blocked Bootstrap Plot - Central Tendency] [Bierproductie Aus...] [2010-06-06 20:18:25] [abee0efc8e8d52b36c60065f2f882b43] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93.2
96
95.2
77.1
70.9
64.8
70.1
77.3
79.5
100.6
100.7
107.1
95.9
82.8
83.3
80
80.4
67.5
75.7
71.1
89.3
101.1
105.2
114.1
96.3
84.4
91.2
81.9
80.5
70.4
74.8
75.9
86.3
98.7
100.9
113.8
89.8
84.4
87.2
85.6
72
69.2
77.5
78.1
94.3
97.7
100.2
116.4
97.1
93
96
80.5
76.1
69.9
73.6
92.6
94.2
93.5
108.5
109.4
105.1
92.5
97.1
81.4
79.1
72.1
78.7
87.1
91.4
109.9
116.3
113
100
84.8
94.3
87.1
90.3
72.4
84.9
92.7
92.2
114.9
112.5
118.3
106
91.2
96.6
96.3
88.2
70.2
86.5
88.2
102.8
119.1
119.2
125.1
106.1
102.1
105.2
101
84.3
87.5
92.7
94.4
113
113.9
122.9
132.7
106.9
96.6
127.3
98.2
100.2
89.4
95.3
104.2
106.4
116.2
135.9
134
104.6
107.1
123.5
98.8
98.6
90.6
89.1
105.2
114
122.1
138
142.2
116.4
112.6
123.8
103.6
113.9
98.6
95
116
113.9
127.5
131.4
145.9
131.5
131
130.5
118.9
114.3
85.7
104.6
105.1
117.3
142.5
140
159.8
131.2
125.4
126.5
119.4
113.5
98.7
114.5
113.8
133.1
143.4
137.3
165.2
126.9
124
135.7
130
109.4
117.8
120.3
121
132.3
142.9
147.4
175.9
132.6
123.7
153.3
134
119.6
116.2
118.6
130.7
129.3
144.4
163.2
179.4
128.1
138.4
152.7
120
140.5
116.2
121.4
127.8
143.6
157.6
166.2
182.3
153.1
147.6
157.7
137.2
151.5
98.7
145.8
151.7
129.4
174.1
197
193.9
164.1
142.8
157.9
159.2
162.2
123.1
130
150.1
169.4
179.7
182.1
194.3
161.4
169.4
168.8
158.1
158.5
135.3
149.3
143.4
142.2
188.4
166.2
199.2
182.7
145.2
182.1
158.7
141.6
132.6
139.6
147
166.6
157
180.4
210.2
159.8
157.8
168.2
158.4
152
142.2
137.2
152.6
166.8
165.6
198.6
201.5
170.7
164.4
179.7
157
168
139.3
138.6
153.4
138.9
172.1
198.4
217.8
173.7
153.8
175.6
147.1
160.3
135.2
148.8
151
148.2
182.2
189.2
183.1
170
158.4
176.1
156.2
153.2
117.9
149.8
156.6
166.7
156.8
158.6
210.8
203.6
175.2
168.7
155.9
147.3
137
141.1
167.4
160.2
191.9
174.4
208.2
159.4
161.1
172.1
158.4
114.6
159.6
159.7
159.4
160.7
165.5
205
205.2
141.6
148.1
184.9
132.5
137.3
135.5
121.7
166.1
146.8
162.8
186.8
185.5
151.5
158.1
143
151.2
147.6
130.7
137.5
146.1
133.6
167.9
181.9
202
166.5
151.3
146.2
148.3
144.7
123.6
151.6
133.9
137.4
181.6
182
190
161.2
155.5
141.9
164.6
136.2
126.8
152.5
126.6
150.1
186.3
147.5
200.4
177.2
127.4
177.1
154.4
135.2
126.4
147.3
140.6
152.3
151.2
172.2
215.3
154.1
159.3
160.4
151.9
148.4
139.6
148.2
153.5
145.1
183.7
210.5
203.3
153.3
144.3
169.6
143.7
160.1
135.6
141.8
159.9
145.7
183.5
198.2
186.8
172
150.6
163.3
153.7
152.9
135.5
148.5
148.4
133.6
194.1
208.6
197.3
164.4
148.1
152
144.1
155
124.5
153
146
138
190
192
192
147
133
163
150
129
131
145
137
138
168
176
188
139
143
150
154
137
129
128
140
143
151
177
184
151
134
164
126
131
125
127
143
143
160
190
182
138
136
152
127
151
130
119
153

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77793&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]3 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=77793&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77793&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 time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean133.844695378151136.395378151261139.6148634453784.217549977035085.7701680672269
median136.625139.15142.98755.189776154191266.36250000000001
midrange140.05141.3142.251.558213589928142.19999999999999

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 133.844695378151 & 136.395378151261 & 139.614863445378 & 4.21754997703508 & 5.7701680672269 \tabularnewline
median & 136.625 & 139.15 & 142.9875 & 5.18977615419126 & 6.36250000000001 \tabularnewline
midrange & 140.05 & 141.3 & 142.25 & 1.55821358992814 & 2.19999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77793&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]133.844695378151[/C][C]136.395378151261[/C][C]139.614863445378[/C][C]4.21754997703508[/C][C]5.7701680672269[/C][/ROW]
[ROW][C]median[/C][C]136.625[/C][C]139.15[/C][C]142.9875[/C][C]5.18977615419126[/C][C]6.36250000000001[/C][/ROW]
[ROW][C]midrange[/C][C]140.05[/C][C]141.3[/C][C]142.25[/C][C]1.55821358992814[/C][C]2.19999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77793&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77793&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
mean133.844695378151136.395378151261139.6148634453784.217549977035085.7701680672269
median136.625139.15142.98755.189776154191266.36250000000001
midrange140.05141.3142.251.558213589928142.19999999999999


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 33 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 50 ; 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)
s.midrange <- (max(s) + min(s)) / 2
c(s.mean, s.median, s.midrange)
}
(r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed'))
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$t[,3]))
colnames(z) <- list('mean','median','midrange')
bitmap(file='plot7.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$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$t[,2])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'midrange',header=TRUE)
q1 <- quantile(r$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')