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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 computationMon, 13 Oct 2008 12:27:48 -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/t1223922729kygottm49bfoe9z.htm/, Retrieved Wed, 29 May 2024 06:40:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=15870, Retrieved Wed, 29 May 2024 06:40:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

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] [1.13 Male Births ...] [2008-10-13 18:27:48] [07b7cf1321bc38017c2c7efcf91ca696] [Current]
Feedback Forum
2008-10-15 07:23:45 [Ed Van Stee] [reply] 
Dit is een test assessment
2008-10-19 14:46:48 [Stijn Loomans] [reply] 
De Student begint direct met te antwoorden op deel 2 van vraag 1 zonder eerst een paar keer de berekening te doen en zo te zien dat de 16,438% niet accuraat is. Dat deze elke keer verschild.

Hierna is de student verschillende paramaters gaan aanpassen die de vraagstelling aanpassen . Zoals' Percentage of Male births per day', 'Number of simulated days', 'aantal geboortes in zowel klein als groot ziekenhuis'.

hiervaan is maar een parameter dat je echt moogt aanpassen namelijk van het aantal dagen. De andere die heeft uitgeprobeerd veranderen de vraagstelling wat dus fout is.
2008-10-20 14:57:27 [Jeroen Aerts] [reply] 
Vraag 1&2: de berekening is juist uitgevoerd maar er zijn niet genoeg 'tests' geblogged om effectief te kunnen zien of een accuraat gegeven is. Zijn antwoord is wel correct maar wordt dus niet gestaafd aan de hand van berekeningen. Het tweede deel van de vraag is echter foutief, want de student beweerd dat de paramater van de 'probability' gewijzigd moet worden om een exactere oplossing te krijgen, namelijk het aantal dagen waarop er berekend wordt moet gewijzigd worden om een juister beeld te krijgen.

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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'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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15870&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15870&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15870&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'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)0.75
#Females births in Large Hospital8166
#Males births in Large Hospital8259
#Female births in Small Hospital2744
#Male births in Small Hospital2731
Probability of more than 75 % of male births in Large Hospital0
Probability of more than 75 % of male births in Small Hospital0.0164383561643836
#Days per Year when more than 75 % of male births occur in Large Hospital0
#Days per Year when more than 75 % of male births occur in Small Hospital6

\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) & 0.75 \tabularnewline
#Females births in Large Hospital & 8166 \tabularnewline
#Males births in Large Hospital & 8259 \tabularnewline
#Female births in Small Hospital & 2744 \tabularnewline
#Male births in Small Hospital & 2731 \tabularnewline
Probability of more than 75 % of male births in Large Hospital & 0 \tabularnewline
Probability of more than 75 % of male births in Small Hospital & 0.0164383561643836 \tabularnewline
#Days per Year when more than 75 % of male births occur in Large Hospital & 0 \tabularnewline
#Days per Year when more than 75 % of male births occur in Small Hospital & 6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=15870&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]0.75[/C][/ROW]
[ROW][C]#Females births in Large Hospital[/C][C]8166[/C][/ROW]
[ROW][C]#Males births in Large Hospital[/C][C]8259[/C][/ROW]
[ROW][C]#Female births in Small Hospital[/C][C]2744[/C][/ROW]
[ROW][C]#Male births in Small Hospital[/C][C]2731[/C][/ROW]
[ROW][C]Probability of more than 75 % of male births in Large Hospital[/C][C]0[/C][/ROW]
[C]Probability of more than 75 % of male births in Small Hospital[/C][C]0.0164383561643836[/C][/ROW]
[ROW][C]#Days per Year when more than 75 % of male births occur in Large Hospital[/C][C]0[/C][/ROW]
[C]#Days per Year when more than 75 % of male births occur in Small Hospital[/C][C]6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=15870&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=15870&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)0.75
#Females births in Large Hospital8166
#Males births in Large Hospital8259
#Female births in Small Hospital2744
#Male births in Small Hospital2731
Probability of more than 75 % of male births in Large Hospital0
Probability of more than 75 % of male births in Small Hospital0.0164383561643836
#Days per Year when more than 75 % of male births occur in Large Hospital0
#Days per Year when more than 75 % of male births occur in Small Hospital6


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.75 ;
Parameters (R input):
par1 = 365 ; par2 = 45 ; par3 = 15 ; par4 = 0.75 ;
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')