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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 computationMon, 13 Oct 2008 11:33:52 -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/13/t1223920410ec9pofb8d137fvw.htm/, Retrieved Tue, 28 May 2024 16:25:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15796, Retrieved Tue, 28 May 2024 16:25:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140

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] [oef. 1.13] [2008-10-13 17:33:52] [46b5932fe641d17912b9bed340844588] [Current]
Feedback Forum
2008-10-18 15:06:19 [Siem Van Opstal] [reply] 
Fout antwoord op vraag 1. Bij vraag 1 moet je verschillende keer de berekening maken om de zien hoeveel procent van de dagen er meer dan 60% jongens geboren worden. Als je dat een aantal keren berekent, merkt je dat er telkens een paar procent verschil is tussen de uitkomsten. daaruit kan je concluderen dat het antwoord niet nauwkeurig is. http://www.freestatistics.org/blog/date/2008/Oct/18/t12243421070ormh8cijwzqawr.htm
http://www.freestatistics.org/blog/date/2008/Oct/18/t1224342199sap2lqvju9s2j82.htm
http://www.freestatistics.org/blog/date/2008/Oct/18/t12243423307ds2o6espzvl8v8.htm
2008-10-18 15:10:37 [Siem Van Opstal] [reply] 
dit is het antwoord op vraag 2, maar het antwoord is foutief. als je aantal geboortes verhoogt, verander je de opgaves. Om tot nauwkeurigere resultaten te komen, moet je de dagen verhogen. Hoe meer jaar, hoe nauwkeuriger het resultaat. Ik heb 3 berekeningen gedaan over 10 jaar en mijn resultaten waren 14.9; 15.2 en 15.7. Het verschil tussen de 3 blijft kleiner dan 1%, de nauwkeurigheid is dus groter geworden. http://www.freestatistics.org/blog/date/2008/Oct/18/t1224338959zf5zamm4xzs3vig.htm
http://www.freestatistics.org/blog/date/2008/Oct/18/t12243395427kaytpsb769bzkj.htm
http://www.freestatistics.org/blog/date/2008/Oct/18/t1224339681h1eum6fvzg5vqge.htm
2008-10-20 11:02:18 [Toon Nauwelaerts] [reply] 
De aan te passen parameter is inderdaad de tijd en niet het aantal geboortes.
2008-10-20 16:54:50 [Steven Symons] [reply] 
dit is inderdaad niet de juiste oplossing voor vraag 1. In de opgave vragen ze om de accuracy te verhogen, dit doe je door middel van het aantal dagen op te trekken. Hoe groter het aantal dagen, hoe groter dus ook de accuracy. In ons voorbeeld staat het aantal dagen standaard op 365, je kan dit veranderen naar maximaal 3650 (=10jaar). Je zal zien dat je een heel andere uitkomst bekomt, in mijn voorbeeld namelijk 13,9%, als je dit een aantal keer herhaalt zal je zien dat je een min waarde en max waarde bekomt zo kan je dus een nog nauwkeurigere uitspraak doen
link: http://www.freestatistics.org/blog/date/2008/Oct/13/t12239285368nzh088t6fy4nqn.htm/, Retrieved Mon, 13 Oct 2008 23:24:09 +0000

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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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15796&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15796&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15796&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Exercise 1.13 p. 14 (Introduction to Probability, 2nd ed.)
Number of simulated days365
Expected number of births in Large Hospital110
Expected number of births in Small Hospital40
Percentage of Male births per day(for which the probability is computed)0.6
#Females births in Large Hospital20008
#Males births in Large Hospital20142
#Female births in Small Hospital7342
#Male births in Small Hospital7258
Probability of more than 60 % of male births in Large Hospital0.0164383561643836
Probability of more than 60 % of male births in Small Hospital0.063013698630137
#Days per Year when more than 60 % of male births occur in Large Hospital6
#Days per Year when more than 60 % of male births occur in Small Hospital23

\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 & 110 \tabularnewline
Expected number of births in Small Hospital & 40 \tabularnewline
Percentage of Male births per day(for which the probability is computed) & 0.6 \tabularnewline
#Females births in Large Hospital & 20008 \tabularnewline
#Males births in Large Hospital & 20142 \tabularnewline
#Female births in Small Hospital & 7342 \tabularnewline
#Male births in Small Hospital & 7258 \tabularnewline
Probability of more than 60 % of male births in Large Hospital & 0.0164383561643836 \tabularnewline
Probability of more than 60 % of male births in Small Hospital & 0.063013698630137 \tabularnewline
#Days per Year when more than 60 % of male births occur in Large Hospital & 6 \tabularnewline
#Days per Year when more than 60 % of male births occur in Small Hospital & 23 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15796&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]110[/C][/ROW]
[ROW][C]Expected number of births in Small Hospital[/C][C]40[/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]20008[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]20142[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]7342[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]7258[/C][/ROW]
[ROW][C]Probability of more than 60 % of male births in Large Hospital[/C][C]0.0164383561643836[/C][/ROW]
[C]Probability of more than 60 % of male births in Small Hospital[/C][C]0.063013698630137[/C][/ROW]
[ROW][C]#Days per Year when more than 60 % of male births occur in Large Hospital[/C][C]6[/C][/ROW]
[C]#Days per Year when more than 60 % of male births occur in Small Hospital[/C][C]23[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15796&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15796&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 Hospital110
Expected number of births in Small Hospital40
Percentage of Male births per day(for which the probability is computed)0.6
#Females births in Large Hospital20008
#Males births in Large Hospital20142
#Female births in Small Hospital7342
#Male births in Small Hospital7258
Probability of more than 60 % of male births in Large Hospital0.0164383561643836
Probability of more than 60 % of male births in Small Hospital0.063013698630137
#Days per Year when more than 60 % of male births occur in Large Hospital6
#Days per Year when more than 60 % of male births occur in Small Hospital23


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 110 ; par3 = 40 ; par4 = 0.6 ;
Parameters (R input):
par1 = 365 ; par2 = 110 ; par3 = 40 ; 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')