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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 computationMon, 13 Oct 2008 10:36:46 -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/t1223915871r6ve1yj1sjgnzfm.htm/, Retrieved Sun, 19 May 2024 15:55:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15730, Retrieved Sun, 19 May 2024 15:55:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

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] [Minder dan 60%] [2008-10-13 16:36:46] [698f00352662853fcbf936bba9a8b936] [Current]
Feedback Forum
2008-10-17 15:26:31 [Kelly Verbruggen] [reply] 
Bij deze vraag was het de bedoeling om de R-code aan te passen zowel in de tabel als in de code zelf. De tabel met tekst is correct veranderd. In de code zelf moet het ongelijkheidsteken worden omgedraaid om te logica van de berekening te veranderen.
if (as.matrix(table(bighospital[i,]))[2] < par4*par2) numsuccessbig = numsuccessbig + 1
bigprob[i] <- numsuccessbig/i
2008-10-19 12:21:03 [Lindsay Heyndrickx] [reply] 
Hij heeft hier de titels en de tekst wel goed aangepast maar ook niet alle tekst is aangepast. Hij heeft hier in de if code niets veranderd dus de cijfers zijn nog altijd voor meer dan 60% geboortes van jongens.
Hierdoor kloppen de cijfers niet.
De commentaar die hij geeft is juist maar die is volledig tegenstrijdig met de cijfers. Er staat dat er meer kans is op minder dan 60% jongens in het grote ziekenhuis. Dit klopt maar de cijfers die hij geblogged heeft zeggen totaal iets anders: 6% in het grote en 13% in het kleine ziekenhuis.

De juiste oplossing voor de if code is:
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


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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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15730&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15730&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15730&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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 Hospital8263
#Males births in Large Hospital8162
#Female births in Small Hospital2747
#Male births in Small Hospital2728
Probability of fewer than 60 % of male births in Large Hospital0.063013698630137
Probability of fewer than 60 % of male births in Small Hospital0.134246575342466
#Days per Year when more than 60 % of male births occur in Large Hospital23
#Days per Year when more than 60 % of male births occur in Small Hospital49

\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 & 8263 \tabularnewline
#Males births in Large Hospital & 8162 \tabularnewline
#Female births in Small Hospital & 2747 \tabularnewline
#Male births in Small Hospital & 2728 \tabularnewline
Probability of fewer than 60 % of male births in Large Hospital & 0.063013698630137 \tabularnewline
Probability of fewer than 60 % of male births in Small Hospital & 0.134246575342466 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 23 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 49 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15730&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]8263[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8162[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2747[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2728[/C][/ROW]
[ROW][C]Probability of fewer than 60 % of male births in Large Hospital[/C][C]0.063013698630137[/C][/ROW]
[C]Probability of fewer than 60 % of male births in Small Hospital[/C][C]0.134246575342466[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]23[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]49[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15730&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15730&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 Hospital8263
#Males births in Large Hospital8162
#Female births in Small Hospital2747
#Male births in Small Hospital2728
Probability of fewer than 60 % of male births in Large Hospital0.063013698630137
Probability of fewer than 60 % of male births in Small Hospital0.134246575342466
#Days per Year when more than 60 % of male births occur in Large Hospital23
#Days per Year when more than 60 % of male births occur in Small Hospital49


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='Waarschijnlijkheid in groot ziekenhuis',xlab='#simulated days',ylab='probability')
dev.off()
bitmap(file='test2.png')
plot(smallprob,col=2,main='Waarschijnlijkheid in klein ziekenhuis',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 fewer 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')