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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 computationSun, 12 Oct 2008 07:28:47 -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/12/t1223818186m9z2jcel5e8bmmd.htm/, Retrieved Sun, 19 May 2024 14:45:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15463, Retrieved Sun, 19 May 2024 14:45:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

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] [Kans meer dan 80%...] [2008-10-12 13:28:47] [66d8ac62eef364ab40d20500903318ca] [Current]
Feedback Forum
2008-10-15 15:43:25 [Simon Meeusen] [reply] 
Antwoord 1 is niet juist. Om een accuratere waarschijnlijkheid te bekomen moet je de 'Number of simulated days' aanpassen. Hoe meer dagen, hoe accurater de waarschijnlijkheid.

Antwoord 2 is juist. Enkel het percentage klopt niet volgens mij, want is 0,005... niet 0,5%.
2008-10-16 15:57:32 [Dana Molenberghs] [reply] 
Vraag 1: Zoals Simon hierboven zegt is het inderdaad zo dat je het aantal dagen moet veranderen. Dit komt omdat het om een simulatie gaat, elk jaar is anders. Wanneer je de berekening doet over een grote tijdspanne is je antwoord nauwkeuriger.

Vraag 2: 0,005479 is inderdaad niet in percenten uitgedrukt, dit moest je zelf nog doen. Het gaat hier dus om 0,5479%
2008-10-17 09:20:10 [Davy De Nef] [reply] 
Bij vraag 1 heb je de complete vraagstelling veranderd door het aantal geboortes te veranderen. Zoals hierboven al aangehaald had je het aantal dagen moeten verhogen voor een meer accurate oplossing.
2008-10-19 11:54:38 [Bob Leysen] [reply] 
Vraag 1 is niet juist, je moet werken met 3650 dagen.
Vanboven staat unverified author, dus het werk is niet wetenschappelijk reproduceerbaar.
2008-10-19 11:59:23 [9c60dd28b365b22b9acf7712ebe69d0b] [reply] 
Vraag 1: Er is geen oplossing gegeven op de vraag 'Is this solution very accurate?'. De factor die de accuraatheid doet stijgen is het aantal opgenomen dagen, verander 365 in 3650 waardoor er een vastere oplossing bekomen wordt.

Vraag 2: Het was verstandiger om meermaals op 'reproduce' te klikken, hierdoor kreeg je weer verschillende oplossingen zoals bij vraag één. Daardoor is het onmogelijk om een vast percentage hierop te plakken.
2008-10-19 17:12:03 [Yara Van Overstraeten] [reply] 
Het antwoord op deze vraag is zoals door meerderen hierboven al bevestigd niet correct. Om de accuraatheid van de resultaten te verhogen dient men het aantal simulaties (dagen) te verhogen en niet het aantal verwachte geboortes.
Het is inderdaad wel correct dat de kans op meer dan 80% mannelijke geboortes zeer klein is.
Er is echter geen onderscheid gemaakt tussen het grote en het kleine ziekenhuis.
De kans op meer dan 80% mannelijke geboortes is kleiner in het grote ziekenhuis dan in het kleine ziekenhuis omdat er in het grote ziekenhuis meer geboortes plaatsvinden.

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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 time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15463&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15463&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15463&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'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)0.8
#Females births in Large Hospital8159
#Males births in Large Hospital8266
#Female births in Small Hospital2702
#Male births in Small Hospital2773
Probability of more than 80 % of male births in Large Hospital0
Probability of more than 80 % of male births in Small Hospital0.00547945205479452
#Days per Year when more than 80 % of male births occur in Large Hospital0
#Days per Year when more than 80 % of male births occur in Small Hospital2

\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) & 0.8 \tabularnewline
#Females births in Large Hospital & 8159 \tabularnewline
#Males births in Large Hospital & 8266 \tabularnewline
#Female births in Small Hospital & 2702 \tabularnewline
#Male births in Small Hospital & 2773 \tabularnewline
Probability of more than 80 % of male births in Large Hospital & 0 \tabularnewline
Probability of more than 80 % of male births in Small Hospital & 0.00547945205479452 \tabularnewline
#Days per Year when more than 80 % of male births occur in Large Hospital & 0 \tabularnewline
#Days per Year when more than 80 % of male births occur in Small Hospital & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15463&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]0.8[/C][/ROW]
[ROW][C]#Females births in Large Hospital[/C][C]8159[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8266[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2702[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2773[/C][/ROW]
[ROW][C]Probability of more than 80 % of male births in Large Hospital[/C][C]0[/C][/ROW]
[C]Probability of more than 80 % of male births in Small Hospital[/C][C]0.00547945205479452[/C][/ROW]
[ROW][C]#Days per Year when more than 80 % of male births occur in Large Hospital[/C][C]0[/C][/ROW]
[C]#Days per Year when more than 80 % of male births occur in Small Hospital[/C][C]2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15463&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15463&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)0.8
#Females births in Large Hospital8159
#Males births in Large Hospital8266
#Female births in Small Hospital2702
#Male births in Small Hospital2773
Probability of more than 80 % of male births in Large Hospital0
Probability of more than 80 % of male births in Small Hospital0.00547945205479452
#Days per Year when more than 80 % of male births occur in Large Hospital0
#Days per Year when more than 80 % of male births occur in Small Hospital2


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.8 ;
Parameters (R input):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.8 ;
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')