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Probability

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Title: Probability


1
Probability
2
Overview
It is remarkable that this science
(probability), which originated in the
consideration of games of chance, should have
become the most important object of human
knowledge. Pierre-Simon de Laplace
3
Who Needs Probability?

4
Rare Event Rule of Inferential Statistics
  • If, under a given assumption, the probability of
    a particular observed event is extremely small,
    we conclude that the assumption is probably not
    correct.

5
Fundamentals
6
Rule 1 Relative Frequency Approximation of
Probability
  • Conduct (or observe) a procedure, and count the
    number of times that event A actually occurs.
    Based on these actual results, P(A) is estimated
    as follows

7
Rule 2 Classical Approach to Probability
  • Assume that a given procedure has n different
    simple events and that each of those simple
    events has an equal chance of occurring. If event
    A can occur in s of these n ways, then

8
Rule 3 Subjective Probabilities
  • P(A), the probability of event A, is estimated by
    using knowledge of the relevant circumstances.

9
Some Definitions
  • An event is any collection of results or outcomes
    of a procedure.
  • A simple event is an outcome or an event that
    cannot be further broken down into simpler
    components.
  • The sample space for a procedure consists of all
    possible simple events. That is, the sample space
    consists of all outcomes that cannot be broken
    down any further.

10
Notation for Probabilities
  • P denotes a probability
  • A, B, and C denote specific events
  • P(A) denotes the probability of event A
    occurring

11
Example
  • Each member of the class will toss a coin.
  • What is the sample space?
  • Estimate the probability of tossing a heads.
  • Use the classical definition to calculate the
    probability of tossing a heads.

12
Law of Large Numbers
  • As a procedure is repeated again and again, the
    relative frequency probability (from Rule 1) of
    an event tends to approach the actual probability.

13
Example
  • Consider rolling a single fair die.
  • What is the sample space?
  • What is the probability of rolling a 6?
  • What is the probability of rolling an even number?

14
Example
  • Consider drawing a single card from an ordinary
    deck of cards.
  • What is the sample space?
  • What is the probability of drawing a king?
  • What is the probability of drawing a heart?
  • What is the probability of drawing the king of
    hearts?

15
Example
  • Consider a couple that wants to have two
    children.
  • What is the sample space for the gender of the
    two children?
  • What is the probability of that both children are
    girls?
  • What is the probability of having one girl and
    one boy?

16
Properties of Probabilities
  • The probability of an impossible event is 0.
  • The probability of an event that is certain to
    occur is 1.
  • For any event A, the probability of A is between
    0 and 1 inclusive. That is,

17
Complementary Events
  • The complement of event A, denoted by ,
    consists of all outcomes in which event A does
    not occur.

18
Example
  • Consider rolling a single fair die.
  • What is the probability that the role is not a
    6?
  • What is the probability that the role is not an
    even number?

19
Rounding Off Probabilities
  • When expressing the value of a probability,
    either give the exact fraction or decimal or
    round off final decimal results to three
    significant digits.

20
Odds
  • The actual odds against event A occurring are the
    ratio usually expressed in the form of ab
    (or a to b), where a and b are integers having
    no common factors.
  • The actual odds in favor of event A are the
    reciprocal of the actual odds against that event.
    If the odds against A are ab, then the odds in
    favor of A are ba.
  • The payoff odds against event A represent the
    ratio of net profit (if you win) to the amount
    bet. payoff odds against event A (net
    profit)(amount bet)

21
Example
  • Consider rolling a single fair die.
  • What are the odds against rolling a 6?
  • What are the odds in favor of rolling a 6?

22
Addition Rule
23
Compound Event
  • A compound event is any event combining two or
    more simple events.
  • Given two simple (or compound) events A and B,
    the following are compound events
  • A and B
  • A or B

24
Notation for Addition Rule
  • P(A or B) the probability that, in a single
    trial, event A occurs, or event B occurs, or they
    both occur

25
Example
  • Consider drawing a single card from an ordinary
    deck of cards.
  • What is the probability of drawing a king or a
    queen?
  • What is the probability of drawing a king or a
    heart?

26
Mutually Exclusive
  • Events A and B are disjoint (or mutually
    exclusive) if they cannot occur at the same time.

27
Formal Addition Rule
  • P(A or B) P(A) P(B) P(A and B)
  • If A and B are mutually exclusive, then
    P(A or B) P(A) P(B)

28
Example
  • Use the data given in the table, which summarizes
    blood groups and Rh types for 100 typical people.
    These values may vary in different regions
    according to the ethnicity of the population.

29
Example (cont.)
  • If one person is randomly selected, find the
    probability of getting someone who is Rh.
  • If one person is randomly selected, find the
    probability of getting someone who is group A or
    group B.
  • If one person is randomly selected, find the
    probability of getting someone who is group B or
    Rh.

30
Rule of Complementary Events

31
Multiplication Rule
32
Notation for Mulitiplication Rule
  • P(A and B) the probability that event A occurs
    in a first trial and event B occurs in a second
    trial

33
Example
  • Consider drawing two cards from an ordinary deck
    of cards, with replacement.
  • What is the probability of drawing two kings?

34
Independence
  • Two events A and B are independent if the
    occurrence of one does not affect the probability
    of the occurrence of the other. (Several events
    are similarly independent if the occurrence of
    any does not affect the probabilities of the
    occurrence of the others). If A and B are not
    independent, they are said to be dependent.

35
Example
  • Consider drawing two cards from an ordinary deck
    of cards, without replacement.
  • What is the probability of drawing two kings?

36
Notation for Mulitiplication Rule
  • P(BA) represents the probability of event B
    occurring after it is assumed that event A has
    already occurred. (We can read BA as B given A
    or as event B occurring after event A has
    already occurred.)

37
Formal Multiplication Rule
  • P(A and B) P(A) . P(BA)
  • If A and B are independent, then P(A
    and B) P(A) . P(B)

38
Example
  • Consider drawing two cards from an ordinary deck
    of cards, with replacement.
  • What is the probability of drawing two red
    cards?
  • What is the probability of drawing two clubs?

39
Example
  • Consider drawing two cards from an ordinary deck
    of cards, without replacement.
  • What is the probability of drawing two red
    cards?
  • What is the probability of drawing two clubs?

40
Treating Dependent Events as Independent
  • If a sample size is no more than 5 of the size
    of the population, treat the selections as being
    independent (even if the selections are made
    without replacement, so they are technically
    dependent).

41
Example
  • Approximately 30 of the calls to an airline
    reservation phone line result in a reservation
    being made.
  • What assumption should we make to calculate the
    probability in part b?
  • Suppose that an operator handles 10 calls. What
    is the probability that none of the 10 calls
    result in a reservation?
  • What is the probability that at least one call
    results in a reservation being made?

42
Multiplication Rule Complements and Conditional
Probability
43
Complements The Probability of At Least One
  • At least one is equivalent to one or more.
  • The complement of getting at least one item of a
    particular type is that you get no items of that
    type.
  • To find the probability of at least one of
    something, calculate the probability of none,
    then subtract that result from 1. That is,
    P(at least one) 1 P(none)

44
Example
  • Consider a couple that wants to have three
    children.
  • What is the probability of that all children are
    girls?
  • What is the probability of having at least one
    boy?

45
Example
  • Consider drawing a single card from an ordinary
    deck of cards.
  • What is the probability of drawing a diamond?
  • What is the probability of drawing a diamond
    given that the card is red?

46
Conditional Probability
  • A conditional probability of an event is a
    probability obtained with the additional
    information that some other event has already
    occurred. P(BA) denotes the conditional
    probability of event B occurring, given that
    event A has already occurred, and it can be found
    by dividing the probability of events A and B
    both occurring by the probability of event A

47
Example
  • Use the data given in the table, which summarizes
    blood groups and Rh types for 100 typical people.
    These values may vary in different regions
    according to the ethnicity of the population.

48
Example (cont.)
  • If one person is randomly selected, find the
    probability of getting someone who is Rh.
  • If one person is randomly selected, find the
    probability of getting someone who is group A
    given that the person is Rh
  • If one person is randomly selected, find the
    probability of getting someone who is Rh given
    that the person is group A.

49
Counting
50
Example
  • Suppose you are looking at a particular model of
    a new car. It comes in three models, the DX, LX,
    and SX. Each model is available in four different
    colors. How many different ways can you select a
    model and color?

51
Fundamental Counting Rule
  • For a sequence of two events in which the first
    event can occur m ways and the second event can
    occur n ways, the events together can occur a
    total of m . n ways.

52
Example
  • DNA (Deoxyribonucleic acid) is made up of
    nucleotides, and each nucleotide can contain on
    of these nitrogenous bases
  • A (adenine),
  • G (guanine),
  • C (cytosine),
  • T (thymine).
  • If one of those four bases (A, G, C, T) must
    be selected three times to form a codon (a linear
    triplet), how many codons are possible?

53
Factorial Rule
  • A collection of n different items can be arranged
    in order n! different ways.
  • Notation
  • The factorial symbol ! Denotes the product of
    decreasing positive whole numbers.
  • n! n(n 1) . . . 2 . 1
  • 0! 1

54
Permutations Rule(When Items Are All Different)
  • Requirements
  • There are n different items available. (This rule
    does not apply if some of the items are identical
    to others.)
  • We select r of the items (without replacement).
  • We consider rearrangements of the same items to
    be different sequences.
  • If the proceeding requirements are satisfied, the
    number of permutations of r items selected from n
    different available items (without replacement)
    is

55
Example
  • In horse-racing, you want your horse to finish in
    first, second, or third place. Suppose the horse
    race has nine horses, how many different ways can
    the horses finish 1-2-3?

56
Permutations Rule (When Some Items Are Identical
to Others)
  • Requirements
  • There are n different items available, and some
    items are identical to others.
  • We select r of the items (without replacement).
  • We consider rearrangements of the same items to
    be different sequences.
  • If the proceeding requirements are satisfied, and
    if there are n1 alike, n2 alike, . . . , nk
    alike, the number of permutations of all items
    selected without replacement is

57
Example
  • Suppose you toss two coins (a penny and a
    nickel), what is the probability of tossing
    exactly one heads?
  • Suppose you toss six coins (a penny, a nickel, a
    dime, a quarter, a half dollar, and a silver
    dollar), what is the probability of tossing
    exactly four heads?

58
Combinations Rule (When Items Are All Different)
  • Requirements
  • There are n different items available.
  • We select r of the n items (without replacement).
  • We consider rearrangements of the same items to
    be the same.
  • If the proceeding requirements are satisfied, the
    number of combinations of r items selected from n
    different items is

59
Example
60
Example (cont.)
  • How many different ways can you pick six numbers
    to play Lotto Texas?
  • What is the probability of winning the jackpot
    (i.e. what is the probability of matching all 6
    of the winning numbers)?
  • What is the probability of matching 5 of the 6
    winning numbers?

61
Example (cont.)
62
Probabilities Through Simulation
63
Simulation
  • A simulation of a procedure is a process that
    behaves the same way as the procedure, so that
    similar results are produced.

64
Generating Random Numbers
  • Table of Random Digits
  • Software
  • MINITAB
  • EXCEL
  • Calculator

65
Example
  • Simulate rolling a single fair die 25 times
    using
  • MINITAB
  • Calculator
  • Use the results to estimate the probability of
    rolling a 4.
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