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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 09:43:26 -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/t1223912682nevdna5lftmp3am.htm/, Retrieved Fri, 24 May 2024 09:50:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15676, Retrieved Fri, 24 May 2024 09:50:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139

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] [80% berekening] [2008-10-13 15:43:26] [54ae75b68e6a45c6d55fa4235827d5b3] [Current]
Feedback Forum
2008-10-17 09:16:50 [Jan Helsen] [reply] 
In uw oplossing geef je 1 oplossing. Je moet ermee rekening houden dat deze niet sluitend is. Wanneer je de berekening opnieuw doet zal je zien dat je een ander resultaat krijgt. Dit had je misschien kunnen vermelden want ook hier geld, hoe hoger het aantal dagen je onderzoekt, hoe nauwkeuriger je resultaten.

Verder is er op de berekening zelfs niet aan te merken tenzij misschien het feit dat je omschrijving nog iets duidelijker kan om de berekening onmiddellijk te kunnen duiden.
2008-10-17 10:00:54 [Ine Coremans] [reply] 
De student heeft de juiste parameter aangepast en een oplossing gekregen. Dit is op een correcte manier gebeurd en geblogd.
Ook hier zou het echter beter geweest zijn de berekeningen een paar keer opnieuw te maken, want de oplossingen zullen elke keer anders zijn. Van hieruit kan je dan een conclusie nemen.
2008-10-18 19:17:39 [Astrid Sniekers] [reply] 
Uitleg oplossing vraag 2:
De oplossing is juist, maar ik had de berekening beter nog een aantal keer meer uitgevoerd.
2008-10-19 12:10:25 [Bob Leysen] [reply] 
De berekening is correct, maar het werd maar één keer geprobeerd.

Post a new message

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=15676&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=15676&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15676&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)0.8
#Females births in Large Hospital8172
#Males births in Large Hospital8253
#Female births in Small Hospital2754
#Male births in Small Hospital2721
Probability of more than 80 % of male births in Large Hospital0
Probability of more than 80 % of male births in Small Hospital0.00273972602739726
#Days per Year when more than 80 % of male births occur in Large Hospital0
#Days per Year when more than 80 % of male births occur in Small Hospital1

\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) & 0.8 \tabularnewline
#Females births in Large Hospital & 8172 \tabularnewline
#Males births in Large Hospital & 8253 \tabularnewline
#Female births in Small Hospital & 2754 \tabularnewline
#Male births in Small Hospital & 2721 \tabularnewline
Probability of more than 80 % of male births in Large Hospital & 0 \tabularnewline
Probability of more than 80 % of male births in Small Hospital & 0.00273972602739726 \tabularnewline
#Days per Year when more than 80 % of male births occur in Large Hospital & 0 \tabularnewline
#Days per Year when more than 80 % of male births occur in Small Hospital & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15676&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]0.8[/C][/ROW]
[ROW][C]#Females births in Large Hospital[/C][C]8172[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8253[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2754[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2721[/C][/ROW]
[ROW][C]Probability of more than 80 % of male births in Large Hospital[/C][C]0[/C][/ROW]
[C]Probability of more than 80 % of male births in Small Hospital[/C][C]0.00273972602739726[/C][/ROW]
[ROW][C]#Days per Year when more than 80 % of male births occur in Large Hospital[/C][C]0[/C][/ROW]
[C]#Days per Year when more than 80 % of male births occur in Small Hospital[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15676&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15676&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)0.8
#Females births in Large Hospital8172
#Males births in Large Hospital8253
#Female births in Small Hospital2754
#Male births in Small Hospital2721
Probability of more than 80 % of male births in Large Hospital0
Probability of more than 80 % of male births in Small Hospital0.00273972602739726
#Days per Year when more than 80 % of male births occur in Large Hospital0
#Days per Year when more than 80 % of male births occur in Small Hospital1


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.8 ;
Parameters (R input):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.8 ;
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')