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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 14:36:38 -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/t1223843926pp6xokt9tk9v6j4.htm/, Retrieved Sun, 19 May 2024 15:38:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15541, Retrieved Sun, 19 May 2024 15:38:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175

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] [Oplossing voor vr...] [2008-10-12 20:10:36] [74be16979710d4c4e7c6647856088456]
F   P     [Exercise 1.13] [Oplossing voor vr...] [2008-10-12 20:29:35] [74be16979710d4c4e7c6647856088456]
F R P         [Exercise 1.13] [Oplossing voor vr...] [2008-10-12 20:36:38] [4b953869c7238aca4b6e0cfb0c5cddd6] [Current]
Feedback Forum
2008-10-17 16:28:13 [681c55e73135f51ec9ab72d25c0ff036] [reply] 
Dit is inderdaad opnieuw een juist antwoord.
Het is bovendien zeer goed dat de student ook parameter 1 verandert waardoor hij een kleine schommeling krijgt.

Er bestaan nog steeds schommelingen in het aantal dagen dat er minder dan 60% jongens worden geboren. Daarom is het belangrijk dat de student meerdere simulaties uitvoert. Zo kan de student een schatting geven van het aantal dagen.
2008-10-18 09:42:47 [8e2cc0b2ef568da46d009b2f601285b2] [reply] 
De student heeft de vraag correct opgelost. De if structuren en outputs zijn aangepast. Het aantal dagen is op 3650 gezet waardoor de berekende waarschijnlijkheden nauwkeuriger zijn. Vermits de nauwkeurigheid zich heeft kunnen convergeren.

De student is echter wel vergeten de grafiek titels te vertalen, dit is eenvoudig te doen in de functie 'plot' in de R-code.

De student heeft het de berekening foutief opgeslagen. Hierdoor is de auteur onbekend en kan men niet nagaan of de student de orginele auteur is.
2008-10-18 11:40:32 [Pieter Broos] [reply] 
In de R-code zijn de 'less' en het '<' goed aangepast waardoor de berekening correct is.
2008-10-20 17:50:24 [a7e076854c32462fd499d2de3f6d4e86] [reply] 
De oplossing is correct.
De student heeft de r-code aangepast, hij heeft hierbij 'more then' vervangen door 'less then' en tevens de 'gelijkheidstekens' goed aangepast waardoor hij een correcte oplossing heeft gevonden.
Het is belangrijk dat men meerdere malen de berekening uitvoert om een goed resultaat te bekomen.

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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=15541&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=15541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15541&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 Hospital81783
#Males births in Large Hospital82467
#Female births in Small Hospital27516
#Male births in Small Hospital27234
Probability of less than 60 % of male births in Large Hospital0.877808219178082
Probability of less than 60 % of male births in Small Hospital0.703835616438356
#Days per Year when less than 60 % of male births occur in Large Hospital320.4
#Days per Year when less than 60 % of male births occur in Small Hospital256.9

\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 & 81783 \tabularnewline
#Males births in Large Hospital & 82467 \tabularnewline
#Female births in Small Hospital & 27516 \tabularnewline
#Male births in Small Hospital & 27234 \tabularnewline
Probability of less than 60 % of male births in Large Hospital & 0.877808219178082 \tabularnewline
Probability of less than 60 % of male births in Small Hospital & 0.703835616438356 \tabularnewline
#Days per Year when less than 60 % of male births occur in Large Hospital & 320.4 \tabularnewline
#Days per Year when less than 60 % of male births occur in Small Hospital & 256.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15541&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]81783[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]82467[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]27516[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]27234[/C][/ROW]
[ROW][C]Probability of less than 60 % of male births in Large Hospital[/C][C]0.877808219178082[/C][/ROW]
[C]Probability of less than 60 % of male births in Small Hospital[/C][C]0.703835616438356[/C][/ROW]
[ROW][C]#Days per Year when less than 60 % of male births occur in Large Hospital[/C][C]320.4[/C][/ROW]
[C]#Days per Year when less than 60 % of male births occur in Small Hospital[/C][C]256.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15541&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 Hospital81783
#Males births in Large Hospital82467
#Female births in Small Hospital27516
#Male births in Small Hospital27234
Probability of less than 60 % of male births in Large Hospital0.877808219178082
Probability of less than 60 % of male births in Small Hospital0.703835616438356
#Days per Year when less than 60 % of male births occur in Large Hospital320.4
#Days per Year when less than 60 % of male births occur in Small Hospital256.9


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 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')