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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 05:02:13 -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/t12238094750xda2a271kjrwfy.htm/, Retrieved Fri, 17 May 2024 03:42:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15425, Retrieved Fri, 17 May 2024 03:42:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [Small hospital ac...] [2008-10-12 11:02:13] [d41d8cd98f00b204e9800998ecf8427e] [Current]
F   P       [Exercise 1.13] [80% kans] [2008-10-12 11:08:49] [74be16979710d4c4e7c6647856088456]
Feedback Forum
2008-10-19 13:53:36 [Nathalie Koulouris] [reply] 
De student heeft de vraag niet begrepen. De parameter die veranderd moet worden is het aantal dagen, niet het aantal geboortes. Door het aantal geboortes te veranderen verander je de opgave.
2008-10-19 17:17:45 [Kevin Neelen] [reply] 
Deze student heeft de vraag een beetje misbegrepen en heeft de foute conclusies getrokken. Hij heeft voor deze vraag slechts 1 computation gemaakt (althans toch maar 1 geblogd), vandaar dat zijn antwoord op deze vraag waarschijnlijk verkeerd is. Er zijn misschien wel meerdere computations gemaakt geweest, maar deze zijn niet geblogd en kunnen dus niet bekeken worden. Hoe meer computations er gemaakt, hoe beter er een conclusie getrokken kan worden. Een conclusie trekken op basis van slechts 1 computation is wel heel summier.
2008-10-20 14:29:27 [Nathalie Koulouris] [reply] 
De student heeft in deze vraag het aantal geboortes aangepast. Dit was niet de bedoeling. De parameter die hier veranderd moest worden was het aantal dagen. De student heeft de berekening slechts één keer uitgevoerd, dit is niet voldoende om een conclusie te trekken.

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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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15425&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15425&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15425&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






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 Hospital19984
#Males births in Large Hospital20166
#Female births in Small Hospital7320
#Male births in Small Hospital7280
Probability of more than 60 % of male births in Large Hospital0.0219178082191781
Probability of more than 60 % of male births in Small Hospital0.073972602739726
#Days per Year when more than 60 % of male births occur in Large Hospital8
#Days per Year when more than 60 % of male births occur in Small Hospital27

\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 & 19984 \tabularnewline
#Males births in Large Hospital & 20166 \tabularnewline
#Female births in Small Hospital & 7320 \tabularnewline
#Male births in Small Hospital & 7280 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.0219178082191781 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.073972602739726 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 8 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 27 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15425&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]19984[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]20166[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]7320[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]7280[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.0219178082191781[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.073972602739726[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]8[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]27[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15425&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15425&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 Hospital19984
#Males births in Large Hospital20166
#Female births in Small Hospital7320
#Male births in Small Hospital7280
Probability of more than 60 % of male births in Large Hospital0.0219178082191781
Probability of more than 60 % of male births in Small Hospital0.073972602739726
#Days per Year when more than 60 % of male births occur in Large Hospital8
#Days per Year when more than 60 % of male births occur in Small Hospital27


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')