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Today Today: Some more counting examples; Start Chapter 2 Important Sections from Chapter 1: 1.1-1.5; Please read 1.7-1.8 Reading: Assignment #2 is up on the web site – PowerPoint PPT presentation

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Title: Today


1
Today
  • Today Some more counting examples Start
    Chapter 2
  • Important Sections from Chapter 1 1.1-1.5
    Please read 1.7-1.8
  • Reading
  • Assignment 2 is up on the web site
  • www.stat.lsa.umich.edu/dbingham/stat405
  • Please read Chapter 2
  • Suggested problems 2.4, 2.5, 2.7, 2.13, 2.25,
    2.28, 2.32, 2R1, 2R2

2
Example
  • A batch of 50 manufactured items contains 5
    defective items. If 10 items are randomly
    selected what is the probability that at least
    one of the defectives is found?

3
Example
  • If there are 60 people in a Statistics 405 class,
    what is the probability that at least 2 have the
    same birthday?

4
Partitions
  • A partition of an event F is a collection of
    events (E1, E2, , Ek) that are mutually disjoint
    (i.e., EiEj , for all i and j ) and where
  • Since none of the Eis have outcomes in common,
    then the number of outcomes in F is the same as
    the sum of the outcomes in each of the Eis
  • That is, if F has N outcomes and Ei has Ni
    outcomes, then NN1N2Nk

5
Partitions
  • If E1, E2,, Ek form a partition of F, then the
    number of distinguishable ways to partition N
    objects into k groups is

6
Example
  • What is the number of ways that 52 cards may be
    divided equally among 4 players

7
Chapter 2
  • Chapter 2 has two main topics
  • Random variables and their distributions
  • Conditional probability and independence
  • Will begin with the second topic

8
Conditional Probability
  • Example
  • A family has two children
  • The sample space for the possible gender of their
    children is gg, gb, bg, bb.
  • The parents are seen leaving a Girl Scout
    meeting, suggesting that at least one of their
    children is a girl
  • If each gender is equally likely, what is the
    probability that the other child is a boy

9
Conditional Probability
  • Consider a probability model with sample space
  • Let E be an event in the sample space
  • If F is another event in the sample space where
    P(F)gt0, the conditional probability of E given F
    is
  • Idea This represents the appropriate change in
    the probability assignment when we know that F
    has occurred

10
Example
  • From a group of 5 Democrats, 5 Republicans and 5
    Independents, a committee of size 3 is to
    selected
  • What is the probability that each group will be
    represented on the committee if the first person
    selected is an Independent?

11
Some Useful Formulas
  • Multiplication Rule
  • Law of Total Probability
  • Bayes Theorem

12
Where do these come from?
13
Example
  • Consider a routine diagnostic test for a rare
    disease
  • Suppose that 0.1 of the population has the
    disease, and that when the disease is present the
    probability that the test indicates the disease
    is present is 0.99
  • Further suppose that when the disease is not
    present, the probability that the test indicates
    the disease is present is 0.10
  • For the people who test positive, what is the
    probability they actually have the disease

14
Several Events
  • Suppose (E1, E2, , Ek) form a partition of the
    sample space
  • Bayes Theorem suppose (E1, E2, , Ek) form a
    partition of the sample space

15
Example (2.28 from text)
  • Evidence in a paternity suit indicates that 4
    particular men are equally likely to be the
    father of the child
  • Both the child and the mother have type O blood
  • The table below give the blood type and the
    probability of producing a type O offspring with
    a type O mother
  • What is the probability that man 1 is the father?
    Man 3? Man 3?

16
Independence
  • For a given probability model and events E and F,
    the two events are said to be independent iff
    P(EF)P(E)P(F)
  • Another way of viewing this is that for events E
    and F, the two events are said to be independent
    iff P(EF)P(E)

17
Example
  • A single card is drawn from a standard deck
  • AAce
  • BSpade
  • Are these events independent?

18
Example
  • Consider a pair of genes which may be one of two
    alleles a or A
  • This could represent a smooth (a) or wrinkled
    seed (A)
  • According to Medelain Theory, each parent
    contributes either a or A to the offspring
    independently
  • E1parent 1 gives a
  • E2parent 2 gives a
  • P(aa)
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