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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 04:41:35 -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/t1223894596zs0mxcjac5fegtu.htm/, Retrieved Sat, 18 May 2024 04:46:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15635, Retrieved Sat, 18 May 2024 04:46:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsfewer than 60% + titel plot is gewijzigd in R code
Estimated Impact210

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]
- R P   [Exercise 1.13] [1.13 Gr-kl 105-35...] [2008-10-08 18:29:40] [44ec60eb6065a3f81a5f756bd5af1faf]
F R P     [Exercise 1.13] [1.13 <60%] [2008-10-08 19:27:49] [44ec60eb6065a3f81a5f756bd5af1faf]
F   P         [Exercise 1.13] [ex 1.13 simulatie 5] [2008-10-13 10:41:35] [4e6e942b02458d77e60e1b0e1044e71b] [Current]
Feedback Forum
2008-10-16 16:14:33 [Dana Molenberghs] [reply] 
Klopt, al zou ik wel in je excel-file getypt hebben wat je net veranderd hebt.
2008-10-17 18:16:52 [Jan Van Riet] [reply] 
De aanpassing in de R-code is correct, maar hiervan vond ik niets terug in het excel-bestand. Hierdoor is het een beetje zoeken naar de redenering achter de oplossing.
2008-10-18 18:43:55 [Astrid Sniekers] [reply] 
Uitleg oplossing vraag 3:
De student heeft de nodige veranderingen in de R-code goed uitgevoerd (‘>’ werd ‘<’ en ‘more’ werd ‘fewer’). Het woord ‘fewer’ was wel beter ‘less’ geweest. Het antwoord van de student is zeer beknopt. Hij of zij had er nog bij kunnen vermelden dat het logisch is dat het grote ziekenhuis op het einde van het jaar het meeste aantal dagen zal tellen dat minder dan 60% van de geboortes jongens zijn. In het grote ziekenhuis worden er namelijk meer kinderen geboren waardoor de kans groter wordt dat de helft van de geboortes jongens zullen zijn en de helft van de geboortes meisjes zullen 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 time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15635&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15635&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15635&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'Gwilym Jenkins' @ 72.249.127.135






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 Hospital8130
#Males births in Large Hospital8295
#Female births in Small Hospital2692
#Male births in Small Hospital2783
Probability of fewer than 60 % of male births in Large Hospital0.865753424657534
Probability of fewer than 60 % of male births in Small Hospital0.663013698630137
#Days per Year when fewer than 60 % of male births occur in Large Hospital316
#Days per Year when fewer than 60 % of male births occur in Small Hospital242

\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 & 8130 \tabularnewline
#Males births in Large Hospital & 8295 \tabularnewline
#Female births in Small Hospital & 2692 \tabularnewline
#Male births in Small Hospital & 2783 \tabularnewline
Probability of fewer than 60 % of male births in Large Hospital & 0.865753424657534 \tabularnewline
Probability of fewer than 60 % of male births in Small Hospital & 0.663013698630137 \tabularnewline
#Days per Year when fewer than 60 % of male births occur in Large Hospital & 316 \tabularnewline
#Days per Year when fewer than 60 % of male births occur in Small Hospital & 242 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15635&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]8130[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8295[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2692[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2783[/C][/ROW]
[ROW][C]Probability of fewer than 60 % of male births in Large Hospital[/C][C]0.865753424657534[/C][/ROW]
[C]Probability of fewer than 60 % of male births in Small Hospital[/C][C]0.663013698630137[/C][/ROW]
[ROW][C]#Days per Year when fewer than 60 % of male births occur in Large Hospital[/C][C]316[/C][/ROW]
[C]#Days per Year when fewer than 60 % of male births occur in Small Hospital[/C][C]242[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15635&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15635&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 Hospital8130
#Males births in Large Hospital8295
#Female births in Small Hospital2692
#Male births in Small Hospital2783
Probability of fewer than 60 % of male births in Large Hospital0.865753424657534
Probability of fewer than 60 % of male births in Small Hospital0.663013698630137
#Days per Year when fewer than 60 % of male births occur in Large Hospital316
#Days per Year when fewer than 60 % of male births occur in Small Hospital242


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 fewer 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')