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QM
Probability


Page 1        QM/T3
Concept of Probability


 You      are rolling a die.
 What are the possible outcomes (value of
 the top face) if the die is rolled only once?
 Outcomes        are either 1 or 2 or 3 or 4 or 5
 or 6.
 Chance       of occurring ‘1’ is one out of six.

  Page 2                                QM/T3
Concept of Probability
   Probability that outcome of roll of a die is ‘1’ is
    1/6.
   P(Die roll result = 1) = 1/6
                                    Simple EVENT
       Outcome    Probability
              1       1/6
              2       1/6
              3       1/6
              4       1/6
              5       1/6
              6       1/6
     Page 3                               QM/T3
Concept of Probability
 What   is the probability that outcome of
 roll of a die is an even number.
 Thisoutcome can occur if the roll result is
 2 or 4 or 6. i.e. 3 ways.
 Number    of all possible result is 6.
 P(Even    number) = 3/6 = 0.5
 Similarly   probability of odd number is 3/6.



   Page 4                             QM/T3
Concept of Probability

       A       1 3 5 2 4 6                   B
 P(A)     = 3/6 = 0.5
 P(B)     = 3/6 = 0.5
 P(A)     + P(B) = 1                    NOTE
                         •A & B are mutually exclusive.
 P(A)     = 1 – P(B)
                         •A & B are mutually exhaustive.
                         •Sum probability of all outcome is 1.
                         •Probability is always ≥ 0.
  Page 5                                         QM/T3
What is Sample Spaces
 Collection    of all possible outcomes.
   All    six faces of a die:



   All    52 cards in a deck:




  Page 6                             QM/T3
Events
 Simple     event
   Outcome   from a sample space with one
    characteristic.
   e.g.:   A red card from a deck of 52 cards




 Page 7                                QM/T3
Visualizing Events
              Red cards     26
              Black cards   26
              Total cards   52



   P(A red card is drawn from a deck) = 26/52
                                       = 0.5




     Page 8                             QM/T3
Events
 Compound    event
  Involves   at      least   two    outcomes
   simultaneously.
  e.g.:An ace that is also red from a deck of
   cards.




  Page 9                            QM/T3
Visualizing Events
                      Ace Others Total
              Red      2    24    26
              Black    2    24    26
              Total    4    48    52


   P(An Ace and Red) = 2/52




    Page 10                              QM/T3
Impossible Events
 Impossible      event
   e.g.:    One card drawn is ‘Q’ of Club & diamond
 Also      known as ‘Null Event’




  Page 11                               QM/T3
Joint Probability
   P(An ‘Ace’ and ‘Red’ from a deck of cards)

                      Ace Others Total
              Red         2   24   26
              Black       2   24   26
              Total       4   48   52


              A = ‘Ace’
                              P(A & B) = ?
              B = ‘Red’
    Page 12                              QM/T3
Joint Probability
 The   probability of a joint event, A and B:
 P(A   and B) = P(A ∩ B)

                                     B
                   A       A&B



                No. of outcomes from A and B
            =
                Total No. of possible outcomes


  Page 13                                QM/T3
Compound Probability
 Probability     of a compound event, A or B:
 P(A    or B) = P(A U B)

                                     B
                    A      A&B



     No. of outcomes from A only or B only or Both
 =
               Total No. of possible outcomes

     Page 14                              QM/T3
Compound Probability
 P(A     or B) = P(A U B)
                   = P(A) + P(B) – P(A ∩ B)



       All Ace                        All Red
         4                  2
                                        26


     4        26       2        7
=         +        -        =        Addition Rule
     52       52       52       13

    Page 15                               QM/T3
Compliment Set
 In   roll of a die
   Set     of all outcomes = {1,2,3,4,5,6}.
   If   A = {1} then Ac has {2,3,4,5,6}.
   If   B = Set of even outcomes = {2, 4, 6} then Bc
       has {1,3, 5}.
 In
   a class if A = Set of students that have
 passed, then Ac is = Set of students that
 have not passed.


  Page 16                                      QM/T3
Computing Joint Probability
A = Card drawn from deck is ‘Ace’
Ac = Card drawn from deck is not ‘Ace’
B = Card drawn from deck is ‘Red’
B c = Card drawn from deck is not ‘Red’

           Event
                     Total
Event      B    Bc
A          2    2     4
Ac         24   24    48
Total      26   26    52

 Page 17                            QM/T3
Computing Joint Probability
A = Card drawn from deck is ‘Ace’
Ac = Card drawn from deck is not ‘Ace’
B = Card drawn from deck is ‘Red’
B c = Card drawn from deck is not ‘Red’


                    Event
                            c
                                Total
      Event     B       B
      A       A∩B     A∩Bc       A
      Ac      Ac ∩ B Ac ∩ B c    Ac
      Total     B       Bc
 Page 18                                QM/T3
Computing Joint Probability
                    Event
                                   Total
   Event      B             Bc
   A       P(A ∩ B)   P(A ∩ B c)   P(A)
   Ac      P(Ac ∩ B) P(Ac ∩ B c)   P (Ac)

   Total     P(B)       P(B c)       1




Page 19                            QM/T3
Conditional Probability
   Finding probability of an event A, given that
    event B has occurred.
   This means that we need to find out probability
    of occurrence of ‘Ace’ given that the card drawn
    is ‘Red’.
                           Event
                                     Total
               Event    B      Bc
                                                2
                 A       2       2      4     =
                  c                             26
                A       24     24      48
                Total   26    26     52
      Page 20                             QM/T3
Conditional Probability
 Theprobability of event A given that event
 B has occurred

     P(A ∩ B)
=                 This is known as
        P(B)    ‘Conditional Probability’
                   and denoted as:

                        P(A l B)


  Page 21                          QM/T3
Multiplication Rule

                     P(A ∩ B)
 P(A   ∩ B) =                  x P(B)
                       P(B)


                 = P(A l B) x P(B)


                 = P(B l A) x P(A)




  Page 22                                QM/T3
Statistical Independence
 Events A and B are independent if the
 probability of one event, A, is not affected
 by another event, B


 P(A   l B) = P(A)
 P(B   l A) = P(B)
 P(A   and B) = P(A) x P(B)



  Page 23                        QM/T3
Bayes’s Theorem
                 P(B l A) x P(A)
 P(A   l B) =
                     P(B)




  Page 24                          QM/T3
Bayes’s Theorem
                  P(B l A) x P(A)
 P(A   l B) =
                      P(B)

                  P(B l A) x P(A)
            =
                 P(B ∩ A) + P(B ∩ Ac)

                      P(B l A) x P(A)
            =
                P(B l A) x P(A) + P(B l Ac) x P(Ac)

  Page 25                               QM/T3
Bayes’s Theorem (General)



                        P(A l Bi) x P(Bi)
 P(Bi      l A) =
                 P(A l B1).P(B1) +…+ P(A l Bk).P(Bk) )




  Page 26                                   QM/T3
Example
Fifty percent of borrowers repaid their loans. Out of those
who repaid, 40% had a college degree. Ten percent of
those who defaulted had a college degree. What is the
probability that a randomly selected borrower who has a
college degree will repay the loan?

                 Repaid loan   Not repaid loan      Total

    College
    degree           0.2             0.05           0.25
    No college
    degree           0.3             0.45           0.75
    Total
                     0.5             0.5            1.0
   Page 27                                  QM/T3
Example
Fifty percent of borrowers repaid their loans. Out of those
who repaid, 40% had a college degree. Ten percent of those
who defaulted had a college degree. What is the probability
that a randomly selected borrower who has a college degree
will repay the loan?

 CD - College degree

 NCD – No College degree
                                 P(RL | CD) = ?
 RL – Repaid Loan

 NRL – Not Repaid Loan

    Page 28                                 QM/T3
Example
Fifty percent of borrowers repaid their loans. Out of those
who repaid, 40% had a college degree. Ten percent of
those who defaulted had a college degree. What is the
probability that a randomly selected borrower who has a
college degree will repay the loan?


CD - College degree
                             P(RL | CD) = ?
NCD – No College degree
RL – Repaid Loan                 0.4      0.5
NRL – Not Repaid Loan
                              P(CD | RL) P(RL)

                 P(CD | RL) P(RL) + P(CD | NRL) P(NRL)
                    0.4      0.5        0.1      0.5
   Page 29                                   QM/T3
Class Exercise
1.    P(A) = 0.25, P(B) = 0.4, P(A|B) = 0.15
      Find out P(AUB).
2.    Probability of two independent events A
      and B are 0.3 and 0.6 respectively. What
      is P(A∩B)?
3.    P(A∩B) = 0.2 ; P(A∩C) = 0.3 ;
      P(B|A) + P(C|A) = 1; What is P(A)?



     Page 30                          QM/T3
Class Exercise
4.    A jar contains 6 red, 5 green, 8 blue and
      3 yellow marbles.
     a)   What is the probability of choosing a red
          marble?
5.    You are tossing a coin three times.
     a)   What is the probability of getting two tails?
     b)   What is the probability of getting at least 2
          heads?



     Page 31                                QM/T3
Class Exercise
6.    A plant has 3 assembly lines that
      produces memory chips. Line1 produces
      50% of chips (defective 4%), Line2
      produces 30% of chips (defective 5%),
      Line3 produces the rest (defective 1%).
      A chip is chosen at random from
      produced lot.
     a)   What is the probability that it is defective?
     b)   Given that the chip is defective, what is the
          probability that it is from Line2?
     Page 32                                QM/T3
Class Exercise
7.    An urn initially contains 6 red and 4
      green balls. A ball is chosen at random
      and then replaced along with two
      additional ball of same colour. This
      process is repeated.
     a)   What is the probability that the 1st and 2nd
          ball drawn are red and 3rd is green?
     b)   What is the probability of 2nd ball drawn is
          red?


     Page 33                              QM/T3
Class Exercise
8.    Two squares are chosen at random on a
      chessboard. What is the probability that
      they have a side in common?
9.    An anti aircraft gun can fire four shots at
      a time. If the probabilities of the first,
      second, third and the last shot hitting
      the enemy aircraft are 0.7, 0.6, 0.5 and
      0.4, what is the probability that four
      shots aimed at an enemy aircraft will
      bring the aircraft down?
     Page 34                         QM/T3

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T3 probability

  • 2. Concept of Probability  You are rolling a die.  What are the possible outcomes (value of the top face) if the die is rolled only once?  Outcomes are either 1 or 2 or 3 or 4 or 5 or 6.  Chance of occurring ‘1’ is one out of six. Page 2 QM/T3
  • 3. Concept of Probability  Probability that outcome of roll of a die is ‘1’ is 1/6.  P(Die roll result = 1) = 1/6 Simple EVENT Outcome Probability 1 1/6 2 1/6 3 1/6 4 1/6 5 1/6 6 1/6 Page 3 QM/T3
  • 4. Concept of Probability  What is the probability that outcome of roll of a die is an even number.  Thisoutcome can occur if the roll result is 2 or 4 or 6. i.e. 3 ways.  Number of all possible result is 6.  P(Even number) = 3/6 = 0.5  Similarly probability of odd number is 3/6. Page 4 QM/T3
  • 5. Concept of Probability A 1 3 5 2 4 6 B  P(A) = 3/6 = 0.5  P(B) = 3/6 = 0.5  P(A) + P(B) = 1 NOTE •A & B are mutually exclusive.  P(A) = 1 – P(B) •A & B are mutually exhaustive. •Sum probability of all outcome is 1. •Probability is always ≥ 0. Page 5 QM/T3
  • 6. What is Sample Spaces  Collection of all possible outcomes.  All six faces of a die:  All 52 cards in a deck: Page 6 QM/T3
  • 7. Events  Simple event  Outcome from a sample space with one characteristic.  e.g.: A red card from a deck of 52 cards Page 7 QM/T3
  • 8. Visualizing Events Red cards 26 Black cards 26 Total cards 52  P(A red card is drawn from a deck) = 26/52 = 0.5 Page 8 QM/T3
  • 9. Events  Compound event  Involves at least two outcomes simultaneously.  e.g.:An ace that is also red from a deck of cards. Page 9 QM/T3
  • 10. Visualizing Events Ace Others Total Red 2 24 26 Black 2 24 26 Total 4 48 52  P(An Ace and Red) = 2/52 Page 10 QM/T3
  • 11. Impossible Events  Impossible event  e.g.: One card drawn is ‘Q’ of Club & diamond  Also known as ‘Null Event’ Page 11 QM/T3
  • 12. Joint Probability  P(An ‘Ace’ and ‘Red’ from a deck of cards) Ace Others Total Red 2 24 26 Black 2 24 26 Total 4 48 52 A = ‘Ace’ P(A & B) = ? B = ‘Red’ Page 12 QM/T3
  • 13. Joint Probability  The probability of a joint event, A and B:  P(A and B) = P(A ∩ B) B A A&B No. of outcomes from A and B = Total No. of possible outcomes Page 13 QM/T3
  • 14. Compound Probability  Probability of a compound event, A or B:  P(A or B) = P(A U B) B A A&B No. of outcomes from A only or B only or Both = Total No. of possible outcomes Page 14 QM/T3
  • 15. Compound Probability  P(A or B) = P(A U B) = P(A) + P(B) – P(A ∩ B) All Ace All Red 4 2 26 4 26 2 7 = + - = Addition Rule 52 52 52 13 Page 15 QM/T3
  • 16. Compliment Set  In roll of a die  Set of all outcomes = {1,2,3,4,5,6}.  If A = {1} then Ac has {2,3,4,5,6}.  If B = Set of even outcomes = {2, 4, 6} then Bc has {1,3, 5}.  In a class if A = Set of students that have passed, then Ac is = Set of students that have not passed. Page 16 QM/T3
  • 17. Computing Joint Probability A = Card drawn from deck is ‘Ace’ Ac = Card drawn from deck is not ‘Ace’ B = Card drawn from deck is ‘Red’ B c = Card drawn from deck is not ‘Red’ Event Total Event B Bc A 2 2 4 Ac 24 24 48 Total 26 26 52 Page 17 QM/T3
  • 18. Computing Joint Probability A = Card drawn from deck is ‘Ace’ Ac = Card drawn from deck is not ‘Ace’ B = Card drawn from deck is ‘Red’ B c = Card drawn from deck is not ‘Red’ Event c Total Event B B A A∩B A∩Bc A Ac Ac ∩ B Ac ∩ B c Ac Total B Bc Page 18 QM/T3
  • 19. Computing Joint Probability Event Total Event B Bc A P(A ∩ B) P(A ∩ B c) P(A) Ac P(Ac ∩ B) P(Ac ∩ B c) P (Ac) Total P(B) P(B c) 1 Page 19 QM/T3
  • 20. Conditional Probability  Finding probability of an event A, given that event B has occurred.  This means that we need to find out probability of occurrence of ‘Ace’ given that the card drawn is ‘Red’. Event Total Event B Bc 2 A 2 2 4 = c 26 A 24 24 48 Total 26 26 52 Page 20 QM/T3
  • 21. Conditional Probability  Theprobability of event A given that event B has occurred P(A ∩ B) = This is known as P(B) ‘Conditional Probability’ and denoted as: P(A l B) Page 21 QM/T3
  • 22. Multiplication Rule P(A ∩ B)  P(A ∩ B) = x P(B) P(B) = P(A l B) x P(B) = P(B l A) x P(A) Page 22 QM/T3
  • 23. Statistical Independence  Events A and B are independent if the probability of one event, A, is not affected by another event, B  P(A l B) = P(A)  P(B l A) = P(B)  P(A and B) = P(A) x P(B) Page 23 QM/T3
  • 24. Bayes’s Theorem P(B l A) x P(A)  P(A l B) = P(B) Page 24 QM/T3
  • 25. Bayes’s Theorem P(B l A) x P(A)  P(A l B) = P(B) P(B l A) x P(A) = P(B ∩ A) + P(B ∩ Ac) P(B l A) x P(A) = P(B l A) x P(A) + P(B l Ac) x P(Ac) Page 25 QM/T3
  • 26. Bayes’s Theorem (General) P(A l Bi) x P(Bi)  P(Bi l A) = P(A l B1).P(B1) +…+ P(A l Bk).P(Bk) ) Page 26 QM/T3
  • 27. Example Fifty percent of borrowers repaid their loans. Out of those who repaid, 40% had a college degree. Ten percent of those who defaulted had a college degree. What is the probability that a randomly selected borrower who has a college degree will repay the loan? Repaid loan Not repaid loan Total College degree 0.2 0.05 0.25 No college degree 0.3 0.45 0.75 Total 0.5 0.5 1.0 Page 27 QM/T3
  • 28. Example Fifty percent of borrowers repaid their loans. Out of those who repaid, 40% had a college degree. Ten percent of those who defaulted had a college degree. What is the probability that a randomly selected borrower who has a college degree will repay the loan? CD - College degree NCD – No College degree P(RL | CD) = ? RL – Repaid Loan NRL – Not Repaid Loan Page 28 QM/T3
  • 29. Example Fifty percent of borrowers repaid their loans. Out of those who repaid, 40% had a college degree. Ten percent of those who defaulted had a college degree. What is the probability that a randomly selected borrower who has a college degree will repay the loan? CD - College degree P(RL | CD) = ? NCD – No College degree RL – Repaid Loan 0.4 0.5 NRL – Not Repaid Loan P(CD | RL) P(RL) P(CD | RL) P(RL) + P(CD | NRL) P(NRL) 0.4 0.5 0.1 0.5 Page 29 QM/T3
  • 30. Class Exercise 1. P(A) = 0.25, P(B) = 0.4, P(A|B) = 0.15 Find out P(AUB). 2. Probability of two independent events A and B are 0.3 and 0.6 respectively. What is P(A∩B)? 3. P(A∩B) = 0.2 ; P(A∩C) = 0.3 ; P(B|A) + P(C|A) = 1; What is P(A)? Page 30 QM/T3
  • 31. Class Exercise 4. A jar contains 6 red, 5 green, 8 blue and 3 yellow marbles. a) What is the probability of choosing a red marble? 5. You are tossing a coin three times. a) What is the probability of getting two tails? b) What is the probability of getting at least 2 heads? Page 31 QM/T3
  • 32. Class Exercise 6. A plant has 3 assembly lines that produces memory chips. Line1 produces 50% of chips (defective 4%), Line2 produces 30% of chips (defective 5%), Line3 produces the rest (defective 1%). A chip is chosen at random from produced lot. a) What is the probability that it is defective? b) Given that the chip is defective, what is the probability that it is from Line2? Page 32 QM/T3
  • 33. Class Exercise 7. An urn initially contains 6 red and 4 green balls. A ball is chosen at random and then replaced along with two additional ball of same colour. This process is repeated. a) What is the probability that the 1st and 2nd ball drawn are red and 3rd is green? b) What is the probability of 2nd ball drawn is red? Page 33 QM/T3
  • 34. Class Exercise 8. Two squares are chosen at random on a chessboard. What is the probability that they have a side in common? 9. An anti aircraft gun can fire four shots at a time. If the probabilities of the first, second, third and the last shot hitting the enemy aircraft are 0.7, 0.6, 0.5 and 0.4, what is the probability that four shots aimed at an enemy aircraft will bring the aircraft down? Page 34 QM/T3