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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 computationThu, 09 Oct 2008 06:05:25 -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/09/t1223554050mg3txh523doazdz.htm/, Retrieved Sun, 19 May 2024 15:23:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15085, Retrieved Sun, 19 May 2024 15:23:12 +0000
QR Codes:

Original text written by user:Geboortes per ziekenhuis meer dan 60% jongens met gewijzigde parameters
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact219

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   P     [Exercise 1.13] [Oefening 1.13] [2008-10-09 12:05:25] [35348cd8592af0baf5f138bd59921307] [Current]
Feedback Forum
2008-10-17 15:48:04 [Annelies Michiels] [reply] 
Dit is spijtig genoeg niet correct.
Je mag de oorspronkelijke opgave niet wijzigen.

Het is parameter 1 die je moet veranderen:

http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/12/t1223837703359u0e0utgir6tw.htm/

In dit voorbeeld heb ik parameter 1 verandert in 3650 dagen.
Als je dit resultaat een aantal keer controleert, zal je zien dat de oplossing altijd zal liggen tussen de 13 en de 14%.
Dit is een veel kleinere schommeling dan de schommelingen die men krijgt als men paramter 1 op 365 blijft staan.
We kunnen dus concluderen dat het niet het aantal geboorten maar wel het aantal dagen dat men onderzoek doet de schommelingen zal doen dalen.

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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=15085&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=15085&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15085&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 Hospital110
Expected number of births in Small Hospital40
Percentage of Male births per day(for which the probability is computed)0.6
#Females births in Large Hospital20065
#Males births in Large Hospital20085
#Female births in Small Hospital7372
#Male births in Small Hospital7228
Probability of more than 60 % of male births in Large Hospital0.0191780821917808
Probability of more than 60 % of male births in Small Hospital0.0493150684931507
#Days per Year when more than 60 % of male births occur in Large Hospital7
#Days per Year when more than 60 % of male births occur in Small Hospital18

\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 & 110 \tabularnewline
Expected number of births in Small Hospital & 40 \tabularnewline
Percentage of Male births per day(for which the probability is computed) & 0.6 \tabularnewline
#Females births in Large Hospital & 20065 \tabularnewline
#Males births in Large Hospital & 20085 \tabularnewline
#Female births in Small Hospital & 7372 \tabularnewline
#Male births in Small Hospital & 7228 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.0191780821917808 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.0493150684931507 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 7 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 18 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15085&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]110[/C][/ROW]
[ROW][C]Expected number of births in Small Hospital[/C][C]40[/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]20065[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]20085[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]7372[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]7228[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.0191780821917808[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.0493150684931507[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]7[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]18[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15085&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15085&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 Hospital110
Expected number of births in Small Hospital40
Percentage of Male births per day(for which the probability is computed)0.6
#Females births in Large Hospital20065
#Males births in Large Hospital20085
#Female births in Small Hospital7372
#Male births in Small Hospital7228
Probability of more than 60 % of male births in Large Hospital0.0191780821917808
Probability of more than 60 % of male births in Small Hospital0.0493150684931507
#Days per Year when more than 60 % of male births occur in Large Hospital7
#Days per Year when more than 60 % of male births occur in Small Hospital18


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 110 ; par3 = 40 ; par4 = 0.6 ;
Parameters (R input):
par1 = 365 ; par2 = 110 ; par3 = 40 ; 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')