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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 02:24:00 -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/t1223886531zy03z72ca8pwrl5.htm/, Retrieved Sat, 18 May 2024 05:29:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15573, Retrieved Sat, 18 May 2024 05:29:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact193

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] [Opgave 1.13 ] [2008-10-13 08:24:00] [2ba2a74112fb2c960057a572bf2825d3] [Current]
-           [Exercise 1.13] [opgave 1.13 deel ...] [2008-10-19 11:24:40] [491a70d26f8c977398d8a0c1c87d3dd4]
-           [Exercise 1.13] [Opgave 1.13 deel ...] [2008-10-19 11:30:38] [491a70d26f8c977398d8a0c1c87d3dd4]
Feedback Forum
2008-10-17 12:19:20 [Julie Leurentop] [reply] 
Uit deze berekening heb je geconcludeerd dat de oplossing bij benadering correct is, maar ze is eigenlijk niet accuraat. De getallen worden at random uitgekozen en als je om deze vraag op te lossen meerdere reproducties had opgeslagen had je een goede vergelijking van de simulaties kunnen maken. Ik merk wel op dat je in je besluit correct verwijst naar de variatie van de resultaten naarmate je meerdere simulaties uitvoerde. Het is dan ook een tip naar volgende opdracht toe om deze blogs op te nemen en te bespreken in je werk.

Je hebt correct de waarschijnlijkheid berekend en besproken over een periode van 10 jaar ipv 1 jaar waaruit een nauwkeuriger resultaat voortvloeit.

Bij het schrijven van je conclusie van de reproductie met 3650 dagen heb je het resultaat wel fout overgenomen. Het percentage dat je verkreeg was niet 15,78% maar 15,20%.

2008-10-19 11:26:20 [Lindsay Heyndrickx] [reply] 
Hier staat dat de uitkomst bij benadering juist is maar eigelijk is het niet zo nauwkeurig. Onderaan de tabel legt ze wel uit wat er moet gebeuren om een nauwkeuriger resultaat te krijgen. Ze heeft de juiste parameters gewijzigd om een nauwkeuriger resultaat te krijgen.
Ze heeft het aantal dagen verhoogd naar 3650 wat zeer goed is want hoe langer de termijn hoe nauwkeuriger.
Bij de uitleg over het % kans op jongens in het kleine ziekenhuis heeft ze een kleine fout gemaakt: 15.78% ipv 15.20%
2008-10-19 16:54:32 [Kevin Neelen] [reply] 
De oplossingen zijn zeker niet allemaal even accuraat. Als meerdere computations waren opgeslagen, kon dit geverifieerd worden. Nu beschikken we slechts over 1 computation. De juiste parameters zijn wel gewijzigd geweest. Ook klopt haar anwtoord als ze zegt dat er meerdere jaren nosig zijn om tot meer nauwkeurige resultaten te komen, want een analyse over 1 jaar is een te korte periode. Daarnaast was er ook een kleine vergetelheid betreffende de vernoemde precentages in het bijgevoegde Word-document: 15,78% moet 15,21% zijn.

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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=15573&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=15573&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15573&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 Hospital81797
#Males births in Large Hospital82453
#Female births in Small Hospital27442
#Male births in Small Hospital27308
Probability of more than 60 % of male births in Large Hospital0.0734246575342466
Probability of more than 60 % of male births in Small Hospital0.152054794520548
#Days per Year when more than 60 % of male births occur in Large Hospital26.8
#Days per Year when more than 60 % of male births occur in Small Hospital55.5

\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 & 81797 \tabularnewline
#Males births in Large Hospital & 82453 \tabularnewline
#Female births in Small Hospital & 27442 \tabularnewline
#Male births in Small Hospital & 27308 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.0734246575342466 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.152054794520548 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 26.8 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 55.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15573&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]81797[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]82453[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]27442[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]27308[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.0734246575342466[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.152054794520548[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]26.8[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]55.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15573&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15573&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 Hospital81797
#Males births in Large Hospital82453
#Female births in Small Hospital27442
#Male births in Small Hospital27308
Probability of more than 60 % of male births in Large Hospital0.0734246575342466
Probability of more than 60 % of male births in Small Hospital0.152054794520548
#Days per Year when more than 60 % of male births occur in Large Hospital26.8
#Days per Year when more than 60 % of male births occur in Small Hospital55.5


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')