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4.4 - Hypergeometric Distributions

The document discusses hypergeometric distributions, which model dependent probability events where the probability of success changes with each trial as items are not replaced. It provides examples like choosing a starting lineup or committee members. The probability of x successes in r trials is given by a formula. For a given problem about choosing a committee of 5 from 6 men and 8 women, it shows setting up the probability distribution and calculating the expected number of women. It also provides a simplified formula for finding the expected value of a hypergeometric distribution.

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Zeinab Ramadan
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0% found this document useful (0 votes)
113 views2 pages

4.4 - Hypergeometric Distributions

The document discusses hypergeometric distributions, which model dependent probability events where the probability of success changes with each trial as items are not replaced. It provides examples like choosing a starting lineup or committee members. The probability of x successes in r trials is given by a formula. For a given problem about choosing a committee of 5 from 6 men and 8 women, it shows setting up the probability distribution and calculating the expected number of women. It also provides a simplified formula for finding the expected value of a hypergeometric distribution.

Uploaded by

Zeinab Ramadan
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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MDM4U

 –  Module  2:  Probability    –  Unit  4:  Probability  Distributions  –  Lesson  4                      Date:___________  

Hypergeometric  Distributions  
A.  What  is  a  Hypergeometric  Distribution?!  
Unlike  the  other  distributions  we  have  encountered,  hypergeometric  distributions  have  trials  whose  
probabilities  do  change  from  one  trial  to  the  next  –  making  them  dependent  on  one  another!!  Each  dependent  
trial  continues  to  have  success  or  failure  as  the  only  options,  but  the  probability  of  success  changes  as  each  trial  
is  made.    In  a  hypergeometric  distribution,each  trial  reduces  the  number  of  items  available  for  the  next  selection  
(i.e.  items  are  not  replaced/repeated).      

The  random  variable  for  a  hypergeometric  distribution  is  number  of  successful  trials  in  an  experiment.    

Examples:     a)  When  choosing  a  starting  lineup  for  a  game,the  coach  must  obviously  choose  a  different  
player  for  each  position.  
b)  When  you  deal  cards  from  a  standard  deck,  there  can  be  no  repetitions.  
c)  When  choosing  members  to  form  a  committee,  there  can  also  be  no  repetition.  
 
 
 
  Probability  in  a  Hypergeometric  D𝒏(𝑬) istribution  
The  theoretical     p robability   o f   a n   e vent,   E ,   i s   g iven   b y:       P (E)   =    
𝒏(𝑺)
The  probability  of  x  successes  in  r  dependent  trials  is  given  by  the  formula:  
                                                                                                     where  0  ≤  P(E)  ≤  1  
 
  C × C
P(x)  =   a x n −a r −x  
  C
n r
 
  Where  a  is  the  number  of  successful  outcomes  among  a  total  of  n  possible  outcomes  

The  hypergeometric  probability  distribution  can  be  created  by  finding  the  probabilities  for  all  possible  values  of  x  .    

Ex.  1:  A  committee  of  5  is  to  be  chosen  from  6  men  and  8  women.    
(a)  Determine  the  probability  distribution  for  the  number  of  women  on  this  committee.                
(b)  What  is  the  expected  number  of  women  on  the  committee?      
     

Number  of   Probability,  P(x)     Product  of    


Women,  x   xi  *  P(xi)  
       

       

       

       

       

       

     
E(X):  
 
B.  Expected  Values    
The  expected  value,  E(X),  for  a  hypergeometric  distribution  can  be  calculated  “traditionally”  by  taking  the  sum  
of  all  xi*P(xi),  but  it  can  also  be  simplified  as  a  ratio  of  successes  in  the  overall  population  as  follows:  

  The  expected  value  for  a  hypergeometric  distribution  for  r  dependent   𝒏(𝑬) trials  is  given  by  the  formula:  
The  theoretical  probability  of  an  event,  E,  is  given  by:      P(E)  =    
  𝒏(𝑺)
  =   r a  
                                                                                                   where  0  ≤  P(E)  ≤  1E(x)  
 
n
 
Where  a  is  the  number  of  successful  outcomes  among  a  total  of  n  possible  outcomes  

 
Ex.  2:  A  box  contains  seven  yellow,  three  green,  five  purple,  and  six  red  candies  jumbled  together.  What  is  the  
expected  number  of  red  candies  among  five  candies  poured  from  the  box?  
 
 
 
 
 
 
 
 
 
 
 
Ex.  3:  In  the  spring,  500  dinosaurs  were  caught  in  a  wilderness  area.  The  dinosaurs  were  released  after  being  
outfitted  with  laser  vision.  To  estimate  the  dinosaur  population  in  the  area,  rangers  caught  40  dinosaurs  in  the  
summer.  Of  these,  15  had  laser  vision.  Estimate  the  dinosaur  population  in  the  wilderness  area.  
 
 
 
 
 
 
 
 
 
 
 
 
                 Watch  the  Video  for  Example  #1  on  p.  398-­‐400  using  Excel;        CW:  p.  404-­‐405  #  1-­‐4,  7,  8,  10-­‐12  

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