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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 computationFri, 10 Oct 2008 05:44:40 -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/10/t12236391438yerx7gf73d38jo.htm/, Retrieved Sun, 19 May 2024 18:19:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15161, Retrieved Sun, 19 May 2024 18:19:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact188

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] [Ex 1.13 ongewijzi...] [2008-10-10 11:44:40] [90714a39acc78a7b2ecd294ecc6b2864] [Current]
Feedback Forum
2008-10-15 15:35:32 [Kevin Truyts] [reply] 
Bij de eerste vraagstelling heeft de student de vraag goed geïnterpreteerd. Zo kwam hij tot de juiste conclusie. Hij vermeld dan ook iets wat onrechtstreeks dat dat er meer metingen/trekkingen nodig zijn om een beter oordeel te kunnen vellen.
Bij de tweede vraag komt de student tot de conclusie dat het resultaat niet echt accuraat is. Drie berekening maken is een goed middel om dit te bewijzen, maar wanneer we het aantal metingen/trekkingen vergroten, kunnen we zien welk een meer accuraat cijfer is.
Aan de hand van de oplossing bij de derde vraag kunnen we afleiden dat de student de verkeerde parameter heeft gewijzigd. Hierdoor gaat hij de vraagstelling (de vaste gegevens) wijzigen wat niet kan in het echt. Je kan niet ineens meer kinderen laten geboren worden elke dag van het jaar. De enigste mogelijke oplossing is dat de periode van 1 jaar groter moet worden gemaakt, waardoor zo de kans op afwijkingen kleiner wordt.
De vierde vraag is volledig correct beantwoord geweest door de student. Hij heeft dan ook de juiste parameter veranderd, van 60% jongens naar 80%.
Bij de laatste vraag had de student de juiste aanpassingen gedaan in de R code, maar door het aanpassen van more naar fewer heeft de student te veel aangepast waardoor de berekeningen foutief zijn.
Toch komt de student tot een juiste conclusie.
2008-10-18 08:12:32 [Jeroen Michel] [reply] 
Ik kan de feedback van de vorige student alleen maar bevestigen. De student laat ook in deze berekening (poging 2) de parameters ongewijzigd, net zoals in berekening 1 (http://www.freestatistics.org/blog/date/2008/Oct/10/t1223638929wqrpnvnu468abvp.htm ). Hierdoor bekomt hij weer een ander resultaat uit. Dit resultaat is ook hier niet accuraat, dit omdat de juiste parameters niet werden gewijzigd.

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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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15161&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15161&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15161&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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 Hospital8118
#Males births in Large Hospital8307
#Female births in Small Hospital2730
#Male births in Small Hospital2745
Probability of more than 60 % of male births in Large Hospital0.0876712328767123
Probability of more than 60 % of male births in Small Hospital0.153424657534247
#Days per Year when more than 60 % of male births occur in Large Hospital32
#Days per Year when more than 60 % of male births occur in Small Hospital56

\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 & 8118 \tabularnewline
#Males births in Large Hospital & 8307 \tabularnewline
#Female births in Small Hospital & 2730 \tabularnewline
#Male births in Small Hospital & 2745 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.0876712328767123 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.153424657534247 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 32 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 56 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15161&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]8118[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8307[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2730[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2745[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.0876712328767123[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.153424657534247[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]32[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]56[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15161&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15161&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 Hospital8118
#Males births in Large Hospital8307
#Female births in Small Hospital2730
#Male births in Small Hospital2745
Probability of more than 60 % of male births in Large Hospital0.0876712328767123
Probability of more than 60 % of male births in Small Hospital0.153424657534247
#Days per Year when more than 60 % of male births occur in Large Hospital32
#Days per Year when more than 60 % of male births occur in Small Hospital56


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')