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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, 08 Oct 2009 08:45:17 -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/2009/Oct/08/t12550131617fazuogsi0jkhbs.htm/, Retrieved Sun, 28 Apr 2024 23:06:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=44885, Retrieved Sun, 28 Apr 2024 23:06:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151

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] [SHWWS1V1] [2009-10-08 14:33:40] [f966872135bb25240f339c0c372beeec]
F   P     [Exercise 1.13] [SHWWS1V1.2] [2009-10-08 14:45:17] [ad87854c04c4a917385375bf83f61258] [Current]
-   P       [Exercise 1.13] [SHWWS1V2] [2009-10-08 14:47:53] [f966872135bb25240f339c0c372beeec]
F   P         [Exercise 1.13] [SHWWS1V3] [2009-10-08 14:52:04] [f966872135bb25240f339c0c372beeec]
-   P           [Exercise 1.13] [SHWWS1V3.2] [2009-10-08 14:53:39] [f966872135bb25240f339c0c372beeec]
F R P             [Exercise 1.13] [SHWWS1V4] [2009-10-08 15:01:24] [f966872135bb25240f339c0c372beeec]
- R P             [Exercise 1.13] [workshop 1 vraag 4] [2009-10-10 16:12:46] [badc6a9acdc45286bea7f74742e15a21]
Feedback Forum
2009-10-10 15:08:39 [Kasper Vervloet] [reply] 
In deze link zijn niet het aantal gesimuleerde dagen aangepast, maar het aantal verwachte geboortes in het grote en het kleine ziekenhuis. Deze parameter veranderen is niet relevant aangezien de vraagstelling gebaseerd is op het aantal verwachte geboortes 15 en 40, respectievelijk voor het kleine en het grote ziekenhuis. De aanpassing naar 20 en 50 doet ons alleen nog maar meer afwijken van 16,438%. In deze link is het aantal gesimuleerde dagen wel verhoogd:
http://www.freestatistics.org/blog/index.php?v=date/2009/Oct/10/t12551870163fds5zlpc42oy20.htm/

Als we het aantal gesimuleerde dagen verhogen is de kans ook hoger dat we minder afwijken van het resultaat van 16,438%. Dit komt door de wet van de grote getallen. Dit wil zeggen dat de juiste oplossing meer en meer benaderd wordt indien we het aantal gesimuleerde dagen verhogen.
2009-10-12 21:56:19 [03b3197f63f97ef6379c615bddbe8a42] [reply] 
Je uitleg voor vraag 2 is zeer volledig. Je hebt alle parameters uitgetest en bent tot de juiste conclusie gekomen.

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 time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=44885&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=44885&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=44885&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'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 Hospital50
Expected number of births in Small Hospital20
Percentage of Male births per day(for which the probability is computed)0.6
#Females births in Large Hospital9127
#Males births in Large Hospital9123
#Female births in Small Hospital3590
#Male births in Small Hospital3710
Probability of more than 60 % of male births in Large Hospital0.063013698630137
Probability of more than 60 % of male births in Small Hospital0.109589041095890
#Days per Year when more than 60 % of male births occur in Large Hospital23
#Days per Year when more than 60 % of male births occur in Small Hospital40

\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 & 50 \tabularnewline
Expected number of births in Small Hospital & 20 \tabularnewline
Percentage of Male births per day(for which the probability is computed) & 0.6 \tabularnewline
#Females births in Large Hospital & 9127 \tabularnewline
#Males births in Large Hospital & 9123 \tabularnewline
#Female births in Small Hospital & 3590 \tabularnewline
#Male births in Small Hospital & 3710 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.063013698630137 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.109589041095890 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 23 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 40 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=44885&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]50[/C][/ROW]
[ROW][C]Expected number of births in Small Hospital[/C][C]20[/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]9127[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]9123[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]3590[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]3710[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.063013698630137[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.109589041095890[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]23[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]40[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=44885&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=44885&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 Hospital50
Expected number of births in Small Hospital20
Percentage of Male births per day(for which the probability is computed)0.6
#Females births in Large Hospital9127
#Males births in Large Hospital9123
#Female births in Small Hospital3590
#Male births in Small Hospital3710
Probability of more than 60 % of male births in Large Hospital0.063013698630137
Probability of more than 60 % of male births in Small Hospital0.109589041095890
#Days per Year when more than 60 % of male births occur in Large Hospital23
#Days per Year when more than 60 % of male births occur in Small Hospital40


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 50 ; par3 = 20 ; par4 = 0.6 ;
Parameters (R input):
par1 = 365 ; par2 = 50 ; par3 = 20 ; 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')