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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 computationFri, 10 Oct 2008 08:46:37 -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/10/t1223650282o9juem6ypkasvzz.htm/, Retrieved Sun, 19 May 2024 20:58:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15244, Retrieved Sun, 19 May 2024 20:58:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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] [Exercise 1.13] [2008-10-10 14:46:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-10-17 10:48:35 [Jeremy Leysen] [reply] 
Goede berekening, inclusief aanpassing van de juiste parameter om tot een nauwkeuriger resultaat te komen.
2008-10-18 11:06:29 [Pieter Broos] [reply] 
Berekening is correct uitgevoerd.
Het antwoord op vraag één had wel iets nauwkeurige gekund. Bijvoorbeeld door de herberekening ook te bloggen, nu kan ik niet zien hoe de student kan weten dat de percentages tussen de 10 en de 20 % liggen.
Het antwoord op vraag twee is correct, de juiste parameter is veranderd. Ook hier had de student een nog nauwkeurigere oplossing kunnen geven door bijvoorbeeld 3 keer te simuleren met 3650 dagen en van deze 3 simulaties een gemiddelde te nemen.
2008-10-18 18:54:18 [Astrid Sniekers] [reply] 
Uitleg oplossing vraag 1:
De student zegt dat de oplossing niet nauwkeurig is. Dit is juist, maar spijtig genoeg heeft hij deze verschillende herberekeningen niet geblogd en kan ik ze ook niet zien. De student heeft ook de juiste parameter (aantal dagen) gewijzigd om een nauwkeuriger resultaat te bekomen. Ook hier heeft hij maar één berekening geblogd. Hij had er meerdere moeten doen, om zijn antwoord nog meer te kunnen staven.
2008-10-19 12:53:15 [Thomas Baken] [reply] 
Het antwoord op vraag één is goed, liever had ik weer meer antwoorden geblogd gezien. Meerdere malen reproducen is vereist om het antwoord kracht bij te zetten en een degelijke oplossing te kunnen staven.

Vraag twee is ook juist beantwoord maar ik geloof niet dat 3650 slechts 'een voorbeeld' kan genoemd worden. Volgens mij is deze parameter toch essentieel.

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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 time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15244&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]4 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=15244&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15244&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 time4 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 Hospital81730
#Males births in Large Hospital82520
#Female births in Small Hospital27096
#Male births in Small Hospital27654
Probability of more than 60 % of male births in Large Hospital0.0701369863013699
Probability of more than 60 % of male births in Small Hospital0.156986301369863
#Days per Year when more than 60 % of male births occur in Large Hospital25.6
#Days per Year when more than 60 % of male births occur in Small Hospital57.3

\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 & 81730 \tabularnewline
#Males births in Large Hospital & 82520 \tabularnewline
#Female births in Small Hospital & 27096 \tabularnewline
#Male births in Small Hospital & 27654 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.0701369863013699 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.156986301369863 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 25.6 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 57.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15244&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]81730[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]82520[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]27096[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]27654[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.0701369863013699[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.156986301369863[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]25.6[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]57.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15244&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15244&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 Hospital81730
#Males births in Large Hospital82520
#Female births in Small Hospital27096
#Male births in Small Hospital27654
Probability of more than 60 % of male births in Large Hospital0.0701369863013699
Probability of more than 60 % of male births in Small Hospital0.156986301369863
#Days per Year when more than 60 % of male births occur in Large Hospital25.6
#Days per Year when more than 60 % of male births occur in Small Hospital57.3


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')