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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 computationSat, 09 Oct 2010 15:57:11 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/09/t12866398182k4qo4df2vayjk7.htm/, Retrieved Mon, 29 Apr 2024 05:09:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=82171, Retrieved Mon, 29 Apr 2024 05:09:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Exercise 1.13] [Taak : Babies cal...] [2010-10-09 15:29:20] [74deae64b71f9d77c839af86f7c687b5]
F   P     [Exercise 1.13] [Taak 3: percentag...] [2010-10-09 15:57:11] [e665313c9926a9f4bdf6ad1ee5aefad6] [Current]
Feedback Forum
2010-10-15 12:17:42 [] [reply] 
'Dit komt omdat er in een groot ziekenhuis meer geboortes zijn en dus ook een grotere kans tussen een jongen of een meisje.'

Ik weet niet of je dit nu goed bedoelt of niet, maar hoe ik het interpreteer lijkt me dit fout. Meer geboortes op één dag wil zeggen dat om een succes te behalen het belangrijk is dat er meer jongens geboren gaan worden, bij een kleiner aantal geboortes op één dag zal dit makkelijker zijn omwille van het feit dat de standaardafwijking dan minder van het steekproefgemiddelde afwijkt.
2010-10-15 12:23:35 [] [reply] 
'Dit komt omdat er in een groot ziekenhuis meer geboortes zijn en dus ook een grotere kans tussen een jongen of een meisje.'

Ik weet niet of je dit nu goed bedoelt of niet, maar hoe ik het interpreteer lijkt me dit fout. Meer geboortes op één dag wil zeggen dat om een succes te behalen het belangrijk is dat er meer jongens geboren gaan worden, bij een kleiner aantal geboortes op één dag zal dit makkelijker zijn omwille van het feit dat de standaardafwijking dan minder van het steekproefgemiddelde afwijkt.

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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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=82171&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=82171&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=82171&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'RServer@AstonUniversity' @ vre.aston.ac.uk






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 Hospital8286
#Males births in Large Hospital8139
#Female births in Small Hospital2780
#Male births in Small Hospital2695
Probability of more than 80 % of male births in Large Hospital0
Probability of more than 80 % of male births in Small Hospital0.010958904109589
#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 Hospital4

\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 & 8286 \tabularnewline
#Males births in Large Hospital & 8139 \tabularnewline
#Female births in Small Hospital & 2780 \tabularnewline
#Male births in Small Hospital & 2695 \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 & 0.010958904109589 \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 & 4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=82171&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]8286[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8139[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2780[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2695[/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]0.010958904109589[/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]4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=82171&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=82171&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 Hospital8286
#Males births in Large Hospital8139
#Female births in Small Hospital2780
#Male births in Small Hospital2695
Probability of more than 80 % of male births in Large Hospital0
Probability of more than 80 % of male births in Small Hospital0.010958904109589
#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 Hospital4


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')