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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, 02 May 2011 18:13:32 +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/2011/May/02/t1304359802x6jfu51q1zpl3ij.htm/, Retrieved Sat, 11 May 2024 08:56:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=120817, Retrieved Sat, 11 May 2024 08:56:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W22
Estimated Impact78

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Blocked Bootstrap Plot - Central Tendency] [Monthly sales of ...] [2011-05-02 18:13:32] [efc14e9f026602d150a82e87225d5526] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
55
60
68
63
65
61
54
52
46
42
37
30
37
44
55
53
58
50
48
45
41
34
30
24
29
34
44
54
57
51
51
53
46
46
46
39
41
53
55
62
55
56
57
59
58
55
49
47
57
68
84
81
78
74
64
74
71
63
55
51
57
63
75
85
80
77
68
72
68
70
53
50
53
58
73
72
68
63
64
68
60
54
41
35
43
44
44
36
44
50
55
61
50
46
39
33
37
40
49
44
45
38
36
34
28
29
27
29
28
29
36
32
36
34
31
36
39
40
39
33
44
46
57
59
64
59
51
50
48
51
45
48
52
58
63
61
59
58
52
48
53
55
42
38
48
55
67
60
65
65
63
61
54
52
51
47
55
59
89
84
75
66
57
52
60
54
48
49
53
59
73
72
62
58
55
56
52
52
43
37
43
55
68
68
64
65
57
59
54
57
43
42
52
51
58
60
61
58
62
61
49
51
47
40
45
50
58
52
50
50
46
46
38
37
34
29
30
40
46
46
47
47
43
46
37
41
39
36
48
55
56
53
52
53
52
56
51
48
42
42
44
50
60
66
58
59
55
57
57
56
53
51
45
58
74
65
65
55
52
59
54
57
45
40
47
47
60
58
63
64
64
63
55
54
44

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'Herman Ole Andreas Wold' @ www.yougetit.org

\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 & 'Herman Ole Andreas Wold' @ www.yougetit.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120817&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]'Herman Ole Andreas Wold' @ www.yougetit.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120817&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120817&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'Herman Ole Andreas Wold' @ www.yougetit.org






Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean50.737272727272752.287272727272753.26454545454551.960544599595452.52727272727273
median5153542.026457651234023
midrange56.12556.556.51.310709419998750.375

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 50.7372727272727 & 52.2872727272727 & 53.2645454545455 & 1.96054459959545 & 2.52727272727273 \tabularnewline
median & 51 & 53 & 54 & 2.02645765123402 & 3 \tabularnewline
midrange & 56.125 & 56.5 & 56.5 & 1.31070941999875 & 0.375 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120817&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]50.7372727272727[/C][C]52.2872727272727[/C][C]53.2645454545455[/C][C]1.96054459959545[/C][C]2.52727272727273[/C][/ROW]
[ROW][C]median[/C][C]51[/C][C]53[/C][C]54[/C][C]2.02645765123402[/C][C]3[/C][/ROW]
[ROW][C]midrange[/C][C]56.125[/C][C]56.5[/C][C]56.5[/C][C]1.31070941999875[/C][C]0.375[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120817&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120817&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
mean50.737272727272752.287272727272753.26454545454551.960544599595452.52727272727273
median5153542.026457651234023
midrange56.12556.556.51.310709419998750.375


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 12 ;
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')