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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 computationMon, 13 Oct 2008 10:03:01 -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/t1223913902fjvruinjfrxpwmw.htm/, Retrieved Fri, 17 May 2024 02:09:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15693, Retrieved Fri, 17 May 2024 02:09:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145

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 R P     [Exercise 1.13] [# days less than 60%] [2008-10-13 16:03:01] [54ae75b68e6a45c6d55fa4235827d5b3] [Current]
Feedback Forum
2008-10-16 11:44:28 [Tim Loyens] [reply] 
De berekening werd zeer goed begrepen door deze studente. Ze wist zowel de lay-out van de tabel aan te passen en ook de wijziging van de werkelijke gegevens correct aan te passen.

Een punt van verbetering zou hier wel kunnen. Ook hier het aantal dagen wijzigen naar 3650 zou de resultaten positief beïnvloeden met een correcter en nauwkeuriger resultaat tot gevolg.
2008-10-17 09:27:52 [Jan Helsen] [reply] 
Je hebt inderdaad de opgave goed geïnterpreteerd. De broncode zelf werd aangepast i.p.v. in het tekstvak een correctie uit te voeren wat toch niets had uitgehaald.

Je omschrijving van de berekening is ook heel duidelijk.
2008-10-17 10:09:36 [Ine Coremans] [reply] 
De studente heeft de R code juist aangepast, waardoor de oplossing van de berekening duidelijk is.
De grafiek hierbij in het worddocument geeft de oplossing duidelijk weer.
Dit is correct berekend en geblogd door de student.
2008-10-18 19:18:21 [Astrid Sniekers] [reply] 
Uitleg oplossing vraag 3:
Ik had de nodige veranderingen in de R-code goed uitgevoerd (‘>’ werd ‘<’ en ‘more’ werd ‘less’). Mijn conclusie was ook correct. Toch had ik er nog bij kunnen vermelden dat het logisch is dat het grote ziekenhuis op het einde van het jaar het meeste aantal dagen zal tellen dat minder dan 60% van de geboortes jongens zijn. In het grote ziekenhuis worden er namelijk meer kinderen geboren waardoor de kans groter wordt dat de helft van de geboortes jongens zullen zijn en de helft van de geboortes meisjes zullen zijn. De grafiek geeft wel een meerwaarde aan mijn oplossing.
2008-10-19 12:13:24 [Bob Leysen] [reply] 
Antwoord is correct en ze zegt hierboven ook waarom de kans in het grote ziekenhuis kleiner is.

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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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15693&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15693&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15693&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.)
Number of simulated days365
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 Hospital8243
#Males births in Large Hospital8182
#Female births in Small Hospital2775
#Male births in Small Hospital2700
Probability of less than 60 % of male births in Large Hospital0.898630136986301
Probability of less than 60 % of male births in Small Hospital0.723287671232877
#Days per Year when less than 60 % of male births occur in Large Hospital328
#Days per Year when less than 60 % of male births occur in Small Hospital264

\begin{tabular}{lllllllll}
\hline
Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.) \tabularnewline
Number of simulated days & 365 \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 & 8243 \tabularnewline
#Males births in Large Hospital & 8182 \tabularnewline
#Female births in Small Hospital & 2775 \tabularnewline
#Male births in Small Hospital & 2700 \tabularnewline
Probability of less than 60 % of male births in Large Hospital & 0.898630136986301 \tabularnewline
Probability of less than 60 % of male births in Small Hospital & 0.723287671232877 \tabularnewline
#Days per Year when less than 60 % of male births occur in Large Hospital & 328 \tabularnewline
#Days per Year when less than 60 % of male births occur in Small Hospital & 264 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15693&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]365[/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]8243[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8182[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2775[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2700[/C][/ROW]
[ROW][C]Probability of less than 60 % of male births in Large Hospital[/C][C]0.898630136986301[/C][/ROW]
[C]Probability of less than 60 % of male births in Small Hospital[/C][C]0.723287671232877[/C][/ROW]
[ROW][C]#Days per Year when less than 60 % of male births occur in Large Hospital[/C][C]328[/C][/ROW]
[C]#Days per Year when less than 60 % of male births occur in Small Hospital[/C][C]264[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15693&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15693&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 days365
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 Hospital8243
#Males births in Large Hospital8182
#Female births in Small Hospital2775
#Male births in Small Hospital2700
Probability of less than 60 % of male births in Large Hospital0.898630136986301
Probability of less than 60 % of male births in Small Hospital0.723287671232877
#Days per Year when less than 60 % of male births occur in Large Hospital328
#Days per Year when less than 60 % of male births occur in Small Hospital264


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.6 ;
Parameters (R input):
par1 = 365 ; 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 less 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 less 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')