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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 03:49:53 -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/t1223806741oljyztg10rwkwdb.htm/, Retrieved Sun, 19 May 2024 15:37:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15410, Retrieved Sun, 19 May 2024 15:37:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182

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] [Exercise 1.13 p. ...] [2008-10-12 09:49:53] [d41d8cd98f00b204e9800998ecf8427e] [Current]
F R         [Exercise 1.13] [Probability of le...] [2008-10-12 10:53:01] [74be16979710d4c4e7c6647856088456]
-             [Exercise 1.13] [EX 1.13 Vr 4 extr...] [2008-10-18 12:11:00] [0996801648c22721e57e03a7deb595f2]
- R           [Exercise 1.13] [EX 1.13 Vr 3 Corr...] [2008-10-19 13:58:24] [0996801648c22721e57e03a7deb595f2]
Feedback Forum
2008-10-19 12:22:03 [9142cf052ad32d043faa9486189092cf] [reply] 
De student begrijpt het principe van de wet van de grote getallen. Hoe meer waarnemingen er gebeuren hoe nauwkeuriger het resultaat. De student heeft drie maal een steekproef uitgevoerd waardoor het resultaat meer nauwkeurig wordt.

Ondanks dat heeft hij een verkeerde parameter gewijzigd. De student gaat er vanuit dat als hij het aantal baby’s gaat verhogen, het resultaat meer accuraat wordt. Door dit te doen verandert hij de opgave.

Om een nauwkeurigere oplossing te krijgen op de gestelde vraag is het van belang de parameter van het aantal dagen te verhogen (Van 365 naar 3650). Als je de steekproef dan een aantal keer uitvoert zonder de parameters te veranderen, merk je een klein verschil in het resultaat. Dit is te wijten aan het feit dat de computer at random getallen neemt uit de database. Om de oplossing zo accuraat mogelijk te maken is het van belang om verschillende steekproeven uit te voeren. De meest accurate oplossing zal dan liggen tussen het kleinste en het grootste resultaat dat je bekomen bent bij de verschillende proeven.
2008-10-19 20:30:57 [Stijn Van de Velde] [reply] 
Het is zo dat een groter aantal gesimuleerde geboortes er voor zorgt dat het resultaat stabieler wordt. Dit is echter niet het juist antwoord, aangezien je hier de opgave veranderd.
De accuraatie is hier dus niet hoog. Om deze te verhogen is het de bedoeling dat je 365 dagen veranderd in 3650, op deze manier blijft de opgaven ongewijzigd, maar word je resultaat wel stabieler.

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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=15410&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=15410&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15410&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 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 Hospital8266
#Males births in Large Hospital8159
#Female births in Small Hospital2754
#Male births in Small Hospital2721
Probability of more than 60 % of male births in Large Hospital0.063013698630137
Probability of more than 60 % of male births in Small Hospital0.139726027397260
#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 Hospital51

\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 & 8266 \tabularnewline
#Males births in Large Hospital & 8159 \tabularnewline
#Female births in Small Hospital & 2754 \tabularnewline
#Male births in Small Hospital & 2721 \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 & 0.139726027397260 \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 & 51 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15410&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]8266[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8159[/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 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]0.139726027397260[/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]51[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15410&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15410&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 Hospital8266
#Males births in Large Hospital8159
#Female births in Small Hospital2754
#Male births in Small Hospital2721
Probability of more than 60 % of male births in Large Hospital0.063013698630137
Probability of more than 60 % of male births in Small Hospital0.139726027397260
#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 Hospital51


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.6 ;
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 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')