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Title: Finding Probability Using Tree Diagrams and Outcome Tables


1
Finding Probability Using Tree Diagrams and
Outcome Tables
  • Chapter 4.5 Introduction to Probability
  • Mathematics of Data Management (Nelson)
  • MDM 4U

2
Tree Diagrams
  • if you flip a coin twice, you can model the
    possible outcomes using a tree diagram or an
    outcome table resulting in 4 possible outcomes

Flip 1 Flip 2 Simple Event
H H HH
H T HT
T H TH
T T TT
T
3
Tree Diagrams Continued
  • if you rolled 1 die and then flipped a coin you
    have 12 possible outcomes

(1,H)
1
(1,T)
(2,H)
2
(2,T)
(3,H)
3
(3,T)
(4,H)
(4,T)
4
(5,H)
5
(5,T)
(6,H)
6
(6,T)
4
Sample Space
  • the sample space for the last experiment would be
    all the ordered pairs in the form (d,c), where d
    represents the roll of a die and c represents the
    flip of a coin
  • clearly there are 12 possible outcomes (6 x 2)
  • P(odd roll,head) ?
  • there are 3 possible outcomes for an odd die and
    a head
  • so the probability is 3 in 12 or ¼
  • P(odd roll, head) ¼

5
Multiplicative Principle for Counting
  • The total number of outcomes is the product of
    the number of possible outcomes at each step in
    the sequence
  • if a is selected from A, and b selected from B
  • n (a,b) n(A) x n(B)
  • (this assumes that each outcome has no influence
    on the next outcome)
  • How many possible three letter words are there?
  • you can choose 26 letters for each of the three
    positions, so there are 26 x 26 x 26 17576
  • how many possible postal codes are there in
    Canada?
  • 26 x 10 x 26 x 10 x 26 x 10 17 576 000

6
Independent and Dependent Events
  • two events are independent of each other if an
    occurence of one event does not change the
    probability of the occurrence of the other
  • what is the probability of getting heads when you
    know in advance that you will throw an even die?
  • these are independent events, so knowing the
    outcome of the second does not change the
    probability of the first

7
Multiplicative Principle for Probability of
Independent Events
  • If we know that if A and B are independent
    events, then
  • P(B A) P(B)
  • if this is not true, then the events are
    dependent
  • we can also prove that if two events are
    independent the probability of both occurring is
  • P(A and B) P(A) P(B)

8
Example 1
  • a sock drawer has a red, a green and a blue sock
  • you pull out one sock, replace it and pull
    another out
  • a) draw a tree diagram representing the possible
    outcomes
  • b) what is the probability of drawing 2 red
    socks?
  • these are independent events

9
Example 2
  • a) If you draw a card, replace it and draw
    another, what is the probability of getting two
    aces?
  • 4/52 x 4/52
  • These are independent events
  • b) If you draw an ace and then draw a second card
    (without replacement), what is the probability
    of two aces?
  • 4/52 x 3/51
  • second event depends on first event
  • the sample space is reduced by the first event

10
Example 3 - Predicting Outcomes
  • Mr. Lieff is playing Texas HoldEm
  • He finds that he wins 70 of the pots when he
    does not bluff
  • He also finds that he wins 50 of the pots when
    he does bluff
  • If there is a 60 chance that Mr. Lieff will
    bluff on his next hand, what are his chances of
    winning the pot?
  • We will start by creating a tree diagram

11
Tree Diagram
P0.6 x 0.5 0.3
Win pot
0.5
bluff
0.6
0.5
P0.6 x 0.5 0.3
Lose pot
Win pot
0.7
P0.4 x 0.7 0.28
0.4
no bluff
P0.4 x 0.3 0.12
Lose pot
0.3
12
Continued
  • P(no bluff, win) P(no bluff) x P(win no
    bluff)
  • 0.4 x 0.7 0.28
  • P(bluff, win) P(bluff) x P(win bluff)
  • 0.6 x 0.5 0.30
  • Probability of a win 0.28 0.30 0.58
  • So Mr. Lieff has a 58 chance of winning the next
    pot

13
Exercises
  • Read the examples on pages 239-244
  • Try pp. 245 249 2, 3, 5, 7, 9, 12, 13a, 14
  • Check each answer with the back of the book to
    make sure that you are understanding these
    concepts

14
Warm up
  • How many different outcomes are there if a
    20-sided die is rolled then a spinner with 5
    sections is spun?
  • 20 x 5 100

15
Counting Techniques and Probability Strategies -
Permutations
  • Chapter 4.6 Introduction to Probability
  • Mathematics of Data Management (Nelson)
  • MDM 4U

16
Arrangements of objects
  • Suppose you have three people in a line
  • How many different arrangements are there?
  • It turns out that there are 6
  • How many arrangements are there for blocks of
    different colours?
  • How many for 4 blocks?
  • How many for 5 blocks?
  • How many for 6 blocks?
  • What is the pattern?

17
Selecting When Order Matters
  • When order matters, we have fewer choices for
    later places in the arrangements
  • For the problem of 3 people
  • For person 1 we have 3 choices
  • For person 2 we have 2 choices left
  • For person 3 we have one choice left
  • The number of possible arrangements for 3 people
    is 3 x 2 x 1 6
  • There is a mathematical notation for this (and
    your calculator has it)

18
Factorial Notation
  • The notation is called factorial
  • n! is the number of ways of arranging n unique
    objects when order matters
  • n! n x (n 1) x (n 2) x x 2 x 1
  • for example
  • 3! 3 x 2 x 1 6
  • 5! 5 x 4 x 3 x 2 x 1 120
  • If we have 10 books to place on a shelf, how many
    possible ways are there to arrange them?
  • 10! 3 628 800 ways

19
Permutations
  • Suppose we have a group of 10 people. How many
    ways are there to pick a president,
    vice-president and treasurer?
  • In this case we are selecting people for a
    particular order
  • However, we are only selecting 3 of the 10
  • For the first person, we can select from 10
  • For the second person, we can select from 9
  • For the third person, we can select from 8
  • So there are 10 x 9 x 8 720 ways

20
Permutation Notation
  • a permutation is an ordered arrangement of
    objects selected from a set
  • written P(n,r) or nPr
  • it is the number of possible permutations of r
    objects from a set of n objects

21
Picking 3 people from 10
  • We get 720 possible arrangements

22
Permutations When Some Objects Are Alike
  • Suppose you are creating arrangements and some
    objects are alike
  • For example, the word ear has 3! or 6
    arrangements (aer, are, ear, era, rea, rae)
  • But the word eel has repeating letters and only 3
    arrangements (eel, ele, lee)
  • How do we calculate arrangements in these cases?

23
Permutations When Some Objects Are Alike
  • To perform this calculation we divide the number
    of possible arrangements by the arrangements of
    objects that are similar
  • n is the number of objects
  • a, b, c are objects that occur more than once

24
So back to our problem
  • Arrangements of the letters in the word eel
  • What would be the possible arrangements of 8
    socks if 3 were red, 2 were blue, 1 black, one
    white and one green?

25
Another Example
  • How many arrangements are there of the letters in
    the word BOOKKEEPER?

26
Arrangements With Replacement
  • Suppose you were looking at arrangements where
    you replaced the object after you had chosen it
  • If you draw two cards from the deck, you have 52
    x 51 possible arrangements
  • If you draw a card, replace it and then draw
    another card, you have 52 x 52 possible
    arrangements
  • Replacement increases the possible arrangements

27
Permutations and Probability
  • If you have 10 different coloured socks in a
    drawer, what is the probability of choosing a
    red, green and blue sock?
  • Probability is the number of possible outcomes
    you want divided by the total number of possible
    outcomes
  • You need to divide the number of possible
    arrangements of the red, green and blue socks by
    the total number of ways that 3 socks can be
    pulled from the drawer

28
The Answer
  • so we have 1 chance in 120 or 0.0083 probability

29
Circular Permutations
  • How many arrangements are there of 6 old chaps
    around a table?

30
Circular Permutations
  • There are 6! different orderings of 6 people
  • Number the people in the original photo
  • 1-2-3-4-5-6.
  • 2-3-4-5-6-1 is the permutation when everyone
    moves one seat to the left.
  • This is not considered to be a different
    arrangement, since the people are seated in the
    same order, but we have counted it 6 times.
  • This is true of every arrangement - we have
    counted them 6 times, so we must divide the total
    by 6.

31
Circular Permutations
  • So the number of orderings of 6 people around a
    table is
  • 6! 5!
  • 6
  • Therefore the number of arrangements of n people
    in a circle is
  • n! (n-1)!
  • n

32
Circular Permutations
  • There are 6! ways to arrange 6 the old chaps
    around a table
  • However, if everyone shifts one seat to the left,
    the arrangement is the same
  • This can be repeated 4 more times (6 total)
  • Therefore 6 of each arrangement are identical
  • So the number of DIFFERENT arrangements is
  • 6! / 6 5!
  • In general, there are (n-1)! ways to arrange n
    objects in a circle.

33
MSIP / Homework
  • p. 255-257 1-7, 11, 13, 14, 16

34
Warm up
  • How many ways can 8 children be placed on a
    8-horse Merry-Go-Round?
  • 7! 5 040
  • What if Simone insisted on riding the red horse?
  • Here we are only arranging 7 children on 7
    horses, so 6! 720

35
Counting Techniques and Probability Strategies -
Combinations
  • Chapter 4.7 Introduction to Probability
  • Mathematics of Data Management (Nelson)
  • MDM 4U

36
When Order is Not Important
  • A combination is an unordered selection of
    elements from a set
  • There are many times when order is not important
  • Suppose Mr. Russell has 10 basketball players and
    must choose a starting lineup of 5 players
    (without specifying positions)
  • Order of players is not important
  • We use the notation C(n,r) or nCr where n is the
    number of elements in the set and r is the number
    we are choosing

37
Combinations
  • A combination of 5 players from 10 is calculated
    the following way, giving 252 ways for Mr.
    Russell to choose his starting lineup

38
An Example of a Restriction on a Combination
  • Suppose that one of Mr. Russells players is the
    superintendents daughter, and so must be one of
    the 5 starting players
  • Here there are really only 4 choices from 9
    players
  • So the calculation is C(9,4) 126
  • Now there are 126 possible combinations for the
    starting lineup

39
Combinations from Complex Sets
  • If you can choose of 1 of 3 entrees, 3 of 6
    vegetables and 2 of 4 desserts for a meal, how
    many possible combinations are there?
  • Combinations of entrees C(3,1) 3
  • Combinations of vegetables C(6,3) 20
  • Combinations of desserts C(4,2) 6
  • Possible combinations
  • C(3,1) x C(6,3) x C(4,2) 3 x 20 x 6 360
  • You have 360 possible dinner combinations, so you
    had better get eating!

40
Calculating the Number of Combinations
  • Suppose you are playing coed volleyball, with a
    team of 4 men and 5 women
  • The rules state that you must have at least 3
    women on the floor at all times (6 players)
  • How many combinations of team lineups are there?
  • You need to take into account team combinations
    with 3, 4, or 5 women

41
Solution 1 Direct Reasoning
  • In direct reasoning, you determine the number of
    possible combinations of suitable outcomes and
    add them
  • Find the combinations that have 3, 4 and 5 women
    and add them

42
Solution 2 Indirect Reasoning
  • In indirect reasoning, you determine the total
    possible combinations of outcomes and subtract
    unsuitable combinations
  • Find the total combinations and subtract those
    with 2 women

43
Warm up
  • For your favourite sport
  • How many players on the roster?
  • How many players in the starting lineup?
  • How many different groups of players can be put
    in the starting lineup? (no assigned positions)
  • How many ways can the coach set the starting
    lineup? (assigned positions)

44
Hockey
  • 12F, 6D, 2G 20 players
  • 3F, 2D, 1G start
  • There are
  • C(20,6) 38 760 groups of 6 players
  • P(12, 3) x P(6, 2) x P(2, 1) 1320 x 30 x 2 79
    200 starting lineups

45
Finding Probabilities Using Combinations
  • What is the probability of drawing a Royal Flush
    (10-J-Q-K-A from the same suit) from a deck of
    cards?
  • There are C(52,5) ways to draw 5 cards
  • There are 4 ways to draw a royal flush
  • P(Royal Flush) 4 / C(52,5) 1 / 649 740
  • You will likely need to play a lot of poker to
    get one of these hands!

46
Finding Probability Using Combinations
  • What is the probability of drawing 4 of a kind?
  • There are 13 different cards that can be used to
    make up the 4 of a kind, and the last card can be
    any other card remaining

47
Probability and Odds
  • These two terms have different uses in math
  • Probability involves comparing the number of
    favorable outcomes with the total number of
    possible outcomes
  • If you have 5 green socks and 8 blue socks in a
    drawer the probability of drawing a green sock is
    5/13
  • Odds compare the number of favorable outcomes
    with the number of unfavorable
  • With 5 green and 8 blue socks, the odds of
    drawing a green sock is 5 to 8 (or 58)

48
Combinatorics Summary
  • In Permutations, order matters
  • e.g., President
  • In Combinations, order doesnt matter
  • e.g., Committee

49
MSIP / Homework
  • p. 262 265 1, 2, 3, 5, 7, 9, 18, 23

50
References
  • Wikipedia (2004). Online Encyclopedia. Retrieved
    September 1, 2004 from http//en.wikipedia.org/wik
    i/Main_Page

51
The Birthday Paradox
  • I will bet any takers 1 that two people in the
    room have the same birthday (I didnt check
    beforehand).
  • In the long run, will I win money? lose money?
    break even?

52
The Birthday Paradox
  • Assume all birthdays are equally likely
  • Find the probability that no two birthdays are
    the same
  • because the second person cannot have the same
    birthday as the first (364/365), the third cannot
    have the same birthday as the first two
    (363/365), etc.

53
The Birthday Paradox
  • The event of at least two of the n persons having
    the same birthday is complementary to all n
    birthdays being different. Therefore, its
    probability p(n) is
  • The approximate probability that no two people
    share a birthday in a group of n people.
  • This probability surpasses 1/2 for n 23 (with
    value about 50.7).

54
The Birthday Paradox
n p(n)
10 11.7
20 41.1
23 50.7
50 70.6
53 97.0
57 99.0
100 99.99997
366 100
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