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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_babies.wasp
Title produced by softwareExercise 1.13
Date of computationMon, 13 Oct 2008 12:01:31 -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/2008/Oct/13/t1223921020g3opby6jcabcz8u.htm/, Retrieved Wed, 26 Aug 2026 19:34:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15812, Retrieved Wed, 26 Aug 2026 19:34:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact458

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Exercise 1.13] [Exercise 1.13 (Wo...] [2008-10-01 13:28:34] [b98453cac15ba1066b407e146608df68]
F         [Exercise 1.13] [Veranderen nauwke...] [2008-10-13 18:01:31] [df9da03099809a35c4563824465f6767] [Current]
F   P       [Exercise 1.13] [1.13 1 poging 1] [2008-10-15 15:27:03] [77d7444c3ef0d60a6a46c7250286f78f]
-   P       [Exercise 1.13] [1.13 1 poging 2] [2008-10-15 15:33:15] [86761fc994bdf34e4f4ab5b8e1d9e1c3]
-   P       [Exercise 1.13] [Oef. 1.13 1 poging 3] [2008-10-15 15:55:25] [77d7444c3ef0d60a6a46c7250286f78f]
-   P       [Exercise 1.13] [Oef 1.13 3 ] [2008-10-15 16:28:18] [86761fc994bdf34e4f4ab5b8e1d9e1c3]
-   P       [Exercise 1.13] [Oef 1.13 3 poging 3] [2008-10-15 16:39:27] [77d7444c3ef0d60a6a46c7250286f78f]
Feedback Forum
2008-10-15 17:45:15 [Christophe Goddaert] [reply] 
Als we de 1e parameter veranderen zien we een observatie van 10 jaar wat de nauwkeurigheid moet verhogen.
Wet van de grote getallen: Nauwkeurigheid verhogen door aantal trekkingen te verhogen want hoe langer de tijdreeksen hoe nauwkeuriger het resultaat.
2008-10-17 13:15:13 [Kenny Simons] [reply] 
Dit is volledig juist, door inderdaad de parameter 'aantal dagen' op het maximum te zetten, ga je meer simulaties doen en zal je resultaat nauwkeuriger worden.

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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=15812&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=15812&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15812&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 days3650
Expected number of births in Large Hospital45
Expected number of births in Small Hospital15
Percentage of Male births per day(for which the probability is computed)0.6
#Females births in Large Hospital82229
#Males births in Large Hospital82021
#Female births in Small Hospital27589
#Male births in Small Hospital27161
Probability of more than 60 % of male births in Large Hospital0.06
Probability of more than 60 % of male births in Small Hospital0.147945205479452
#Days per Year when more than 60 % of male births occur in Large Hospital21.9
#Days per Year when more than 60 % of male births occur in Small Hospital54

\begin{tabular}{lllllllll}
\hline
Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.) \tabularnewline
Number of simulated days & 3650 \tabularnewline
Expected number of births in Large Hospital & 45 \tabularnewline
Expected number of births in Small Hospital & 15 \tabularnewline
Percentage of Male births per day(for which the probability is computed) & 0.6 \tabularnewline
#Females births in Large Hospital & 82229 \tabularnewline
#Males births in Large Hospital & 82021 \tabularnewline
#Female births in Small Hospital & 27589 \tabularnewline
#Male births in Small Hospital & 27161 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.06 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.147945205479452 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 21.9 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15812&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]3650[/C][/ROW]
[ROW][C]Expected number of births in Large Hospital[/C][C]45[/C][/ROW]
[ROW][C]Expected number of births in Small Hospital[/C][C]15[/C][/ROW]
[ROW][C]Percentage of Male births per day(for which the probability is computed)[/C][C]0.6[/C][/ROW]
[ROW][C]#Females births in Large Hospital[/C][C]82229[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]82021[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]27589[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]27161[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.06[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.147945205479452[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]21.9[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15812&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15812&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 days3650
Expected number of births in Large Hospital45
Expected number of births in Small Hospital15
Percentage of Male births per day(for which the probability is computed)0.6
#Females births in Large Hospital82229
#Males births in Large Hospital82021
#Female births in Small Hospital27589
#Male births in Small Hospital27161
Probability of more than 60 % of male births in Large Hospital0.06
Probability of more than 60 % of male births in Small Hospital0.147945205479452
#Days per Year when more than 60 % of male births occur in Large Hospital21.9
#Days per Year when more than 60 % of male births occur in Small Hospital54


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 3650 ; par2 = 45 ; par3 = 15 ; par4 = 0.6 ;
Parameters (R input):
par1 = 3650 ; 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='Probability in Large Hospital',xlab='#simulated days',ylab='probability')
dev.off()
bitmap(file='test2.png')
plot(smallprob,col=2,main='Probability in Small Hospital',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,'Expected number of births in Large Hospital',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Expected number of births in Small Hospital',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Percentage of Male births per day
(for which the probability is computed)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#Females births in Large Hospital',header=TRUE)
a<-table.element(a,tbig[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#Males births in Large Hospital',header=TRUE)
a<-table.element(a,tbig[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#Female births in Small Hospital',header=TRUE)
a<-table.element(a,tsmall[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#Male births in Small Hospital',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')