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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 06:32:45 -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/t12235568904libnkpz6b3ci50.htm/, Retrieved Sat, 18 May 2024 03:28:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15097, Retrieved Sat, 18 May 2024 03:28:01 +0000
QR Codes:

Original text written by user:Wijzigingen: - ">" vervangen door "<" - "Probability of more than" vervangen door "probability of less than" - "Days per year with more than" vervangen door "Days per year with less than" Parameters: 365 45 15 0.6
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact209

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 R P     [Exercise 1.13] [Computation chang...] [2008-10-09 12:32:45] [286e96bd53289970f8e5f25a93fb50b3] [Current]
Feedback Forum
2008-10-17 17:55:03 [Gregory Van Overmeiren] [reply] 
Dit was perfect, enkel spijtig van de plagiaat...

[Exercise 1.13] [Exercise 1.13 (Wo...] [2008-10-01 13:28:34] [Wessa Patrick]
- R P [Exercise 1.13] [Computation chang...] [2008-10-09 12:32:45] [Van Spaandonck Michael] [Current]
2008-10-18 19:10:58 [Astrid Sniekers] [reply] 
Uitleg oplossing vraag 3:
De student heeft de nodige veranderingen in de R-code goed uitgevoerd (‘>’ werd ‘<’ en ‘more’ werd ‘less’). De conclusie die hij maakt is ook correct. Hij 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.
2008-10-20 19:40:24 [Steven Symons] [reply] 
deze oefening is correct, enkel de nederlandse vertaling ontbreekt. Voor de rest heeft hij wel de R-code aangepast bij ( > veranderen in <) en ( more veranderen in less).

wel spijtig dat je het moet kopieren van andere studenten, misschien volgende keer zelf proberen.

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=15097&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=15097&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15097&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 Hospital8160
#Males births in Large Hospital8265
#Female births in Small Hospital2708
#Male births in Small Hospital2767
Probability of less than 60 % of male births in Large Hospital0.86027397260274
Probability of less than 60 % of male births in Small Hospital0.665753424657534
#Days per Year when less than 60 % of male births occur in Large Hospital314
#Days per Year when less than 60 % of male births occur in Small Hospital243

\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 & 8160 \tabularnewline
#Males births in Large Hospital & 8265 \tabularnewline
#Female births in Small Hospital & 2708 \tabularnewline
#Male births in Small Hospital & 2767 \tabularnewline
Probability of less than 60 % of male births in Large Hospital & 0.86027397260274 \tabularnewline
Probability of less than 60 % of male births in Small Hospital & 0.665753424657534 \tabularnewline
#Days per Year when less than 60 % of male births occur in Large Hospital & 314 \tabularnewline
#Days per Year when less than 60 % of male births occur in Small Hospital & 243 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15097&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]8160[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8265[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2708[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2767[/C][/ROW]
[ROW][C]Probability of less than 60 % of male births in Large Hospital[/C][C]0.86027397260274[/C][/ROW]
[C]Probability of less than 60 % of male births in Small Hospital[/C][C]0.665753424657534[/C][/ROW]
[ROW][C]#Days per Year when less than 60 % of male births occur in Large Hospital[/C][C]314[/C][/ROW]
[C]#Days per Year when less than 60 % of male births occur in Small Hospital[/C][C]243[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15097&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15097&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 Hospital8160
#Males births in Large Hospital8265
#Female births in Small Hospital2708
#Male births in Small Hospital2767
Probability of less than 60 % of male births in Large Hospital0.86027397260274
Probability of less than 60 % of male births in Small Hospital0.665753424657534
#Days per Year when less than 60 % of male births occur in Large Hospital314
#Days per Year when less than 60 % of male births occur in Small Hospital243


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.9 ;
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='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 less 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 less 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')