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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_babies.wasp
Title produced by softwareExercise 1.13
Date of computationThu, 01 Oct 2009 02:41:36 -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/Oct/01/t1254386557urmu9dbvpuoroxn.htm/, Retrieved Mon, 29 Apr 2024 04:31:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=43159, Retrieved Mon, 29 Apr 2024 04:31:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsJSshwws1v2-Acc1
Estimated Impact142

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Exercise 1.13] [Simulatie 1] [2009-10-01 08:24:08] [214e6e00abbde49700521a7ef1d30da2]
F   P     [Exercise 1.13] [Accuratie 1] [2009-10-01 08:41:36] [6a216f7ee875fd9e638fe17124c5ffda] [Current]
-   P       [Exercise 1.13] [SHW WS1] [2009-10-08 15:24:37] [023d83ebdf42a2acf423907b4076e8a1]
-   P       [Exercise 1.13] [WS1 vr2] [2009-10-08 15:35:24] [023d83ebdf42a2acf423907b4076e8a1]
Feedback Forum
2009-10-08 15:46:56 [db5ae776ab7337817f00d3a5e526415e] [reply] 
De oplossing wordt volgens de wet van de grote getallen neuwkeuriger naarmate het aantal simulaties stijgt. Ik heb de simulatie opnieuw gedaan, maar dan niet met 1290, maar met 1350 aantal dagen. http://www.freestatistics.org/blog/index.php?v=date/2009/Oct/08/t125501620954xjb0he9e1d7ko.htm/

2009-10-09 11:11:52 [Sofie Coppens] [reply] 
Hoe hoger het aantal dagen, hoe groter de nauwkeurigheid. De grafiek gaat zich steeds meer stabiliseren en er zijn dus minder schommelingen te zien.
Dus om nog nauwkeuriger te werk te gaan kan je kiezen voor 3650 dagen of door de r-code aan te passen (dan kan je nog meer dagen invullen).
Het resultaat is nauwkeuriger als je langer simuleert maar je gaat nooit een exact antwoord krijgen.

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Dataset

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=43159&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]5 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=43159&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=43159&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 time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.)
Number of simulated days2190
Geplande geboortes in groot ziekenhuis45
Geplande geboortes in klein ziekenhuis15
Geboorte van jongens per dag (%)0.6
Aantal geboortes van meisjes in groot ziekenhuis49378
Aantal geboortes van jongens in groot ziekenhuis49172
Aantal geboortes van meisjes in klein ziekenhuis16378
Aantal geboortes van jongens in klein ziekenhuis16472
Probability of more than 60 % of male births in Large Hospital0.0611872146118721
Probability of more than 60 % of male births in Small Hospital0.142922374429224
#Days per Year when more than 60 % of male births occur in Large Hospital22.3333333333333
#Days per Year when more than 60 % of male births occur in Small Hospital52.1666666666667

\begin{tabular}{lllllllll}
\hline
Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.) \tabularnewline
Number of simulated days & 2190 \tabularnewline
Geplande geboortes in groot ziekenhuis & 45 \tabularnewline
Geplande geboortes in klein ziekenhuis & 15 \tabularnewline
Geboorte van jongens per dag (%) & 0.6 \tabularnewline
Aantal geboortes van meisjes in groot ziekenhuis & 49378 \tabularnewline
Aantal geboortes van jongens in groot ziekenhuis & 49172 \tabularnewline
Aantal geboortes van meisjes in klein ziekenhuis & 16378 \tabularnewline
Aantal geboortes van jongens in klein ziekenhuis & 16472 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.0611872146118721 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.142922374429224 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 22.3333333333333 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 52.1666666666667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=43159&T=1

[TABLE]
[ROW][C]Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.)[/C][/ROW]
[ROW][C]Number of simulated days[/C][C]2190[/C][/ROW]
[ROW][C]Geplande geboortes in groot ziekenhuis[/C][C]45[/C][/ROW]
[ROW][C]Geplande geboortes in klein ziekenhuis[/C][C]15[/C][/ROW]
[ROW][C]Geboorte van jongens per dag (%)[/C][C]0.6[/C][/ROW]
[ROW][C]Aantal geboortes van meisjes in groot ziekenhuis[/C][C]49378[/C][/ROW]
[ROW][C]Aantal geboortes van jongens in groot ziekenhuis[/C][C]49172[/C][/ROW]
[ROW][C]Aantal geboortes van meisjes in klein ziekenhuis[/C][C]16378[/C][/ROW]
[ROW][C]Aantal geboortes van jongens in klein ziekenhuis[/C][C]16472[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.0611872146118721[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.142922374429224[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]22.3333333333333[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]52.1666666666667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=43159&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=43159&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:

Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.)
Number of simulated days2190
Geplande geboortes in groot ziekenhuis45
Geplande geboortes in klein ziekenhuis15
Geboorte van jongens per dag (%)0.6
Aantal geboortes van meisjes in groot ziekenhuis49378
Aantal geboortes van jongens in groot ziekenhuis49172
Aantal geboortes van meisjes in klein ziekenhuis16378
Aantal geboortes van jongens in klein ziekenhuis16472
Probability of more than 60 % of male births in Large Hospital0.0611872146118721
Probability of more than 60 % of male births in Small Hospital0.142922374429224
#Days per Year when more than 60 % of male births occur in Large Hospital22.3333333333333
#Days per Year when more than 60 % of male births occur in Small Hospital52.1666666666667


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2190 ; par2 = 45 ; par3 = 15 ; par4 = 0.6 ;
Parameters (R input):
par1 = 2190 ; par2 = 45 ; par3 = 15 ; par4 = 0.6 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
numsuccessbig <- 0
numsuccesssmall <- 0
bighospital <- array(NA,dim=c(par1,par2))
smallhospital <- array(NA,dim=c(par1,par3))
bigprob <- array(NA,dim=par1)
smallprob <- array(NA,dim=par1)
for (i in 1:par1) {
bighospital[i,] <- sample(c('F','M'),par2,replace=TRUE)
if (as.matrix(table(bighospital[i,]))[2] > par4*par2) numsuccessbig = numsuccessbig + 1
bigprob[i] <- numsuccessbig/i
smallhospital[i,] <- sample(c('F','M'),par3,replace=TRUE)
if (as.matrix(table(smallhospital[i,]))[2] > par4*par3) numsuccesssmall = numsuccesssmall + 1
smallprob[i] <- numsuccesssmall/i
}
tbig <- as.matrix(table(bighospital))
tsmall <- as.matrix(table(smallhospital))
tbig
tsmall
numsuccessbig/par1
bigprob[par1]
numsuccesssmall/par1
smallprob[par1]
numsuccessbig/par1*365
bigprob[par1]*365
numsuccesssmall/par1*365
smallprob[par1]*365
bitmap(file='test1.png')
plot(bigprob,col=2,main='Waarschijnlijkheid in groot ziekenhuis',xlab='#simulated days',ylab='probability')
dev.off()
bitmap(file='test2.png')
plot(smallprob,col=2,main='Waarschijnlijkheid in klein ziekenhuis',xlab='#simulated days',ylab='probability')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of simulated days',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Geplande geboortes in groot ziekenhuis',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Geplande geboortes in klein ziekenhuis',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Geboorte van jongens per dag (%)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Aantal geboortes van meisjes in groot ziekenhuis',header=TRUE)
a<-table.element(a,tbig[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Aantal geboortes van jongens in groot ziekenhuis',header=TRUE)
a<-table.element(a,tbig[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Aantal geboortes van meisjes in klein ziekenhuis',header=TRUE)
a<-table.element(a,tsmall[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Aantal geboortes van jongens in klein ziekenhuis',header=TRUE)
a<-table.element(a,tsmall[2])
a<-table.row.end(a)
a<-table.row.start(a)
dum1 <- paste('Probability of more than', par4*100, sep=' ')
dum <- paste(dum1, '% of male births in Large Hospital', sep=' ')
a<-table.element(a, dum, header=TRUE)
a<-table.element(a, bigprob[par1])
a<-table.row.end(a)
dum <- paste(dum1, '% of male births in Small Hospital', sep=' ')
a<-table.element(a, dum, header=TRUE)
a<-table.element(a, smallprob[par1])
a<-table.row.end(a)
a<-table.row.start(a)
dum1 <- paste('#Days per Year when more than', par4*100, sep=' ')
dum <- paste(dum1, '% of male births occur in Large Hospital', sep=' ')
a<-table.element(a, dum, header=TRUE)
a<-table.element(a, bigprob[par1]*365)
a<-table.row.end(a)
dum <- paste(dum1, '% of male births occur in Small Hospital', sep=' ')
a<-table.element(a, dum, header=TRUE)
a<-table.element(a, smallprob[par1]*365)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')