Statistics 270 - Lecture 4 - PowerPoint PPT Presentation

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Title: Statistics 270 - Lecture 4


1
Statistics 270 - Lecture 4
2
  • Last class measures of spread and box-plots
  • Have completed Chapter 1
  • Today - Chapter 2

3
Probability
  • There is a 75 chance of rain tomorrow
  • What does this mean?

4
Definitions
  • Probability of an outcome is a numerical measure
    of the chance of the outcome occurring
  • A experiment is any action whose outcome is
    uncertain
  • Sample space, S, is the collection of possible
    outcomes of an experiment
  • Event is a set of outcomes
  • Event occurs when one of its outcomes occurs

5
Example
  • A coin is tossed 1 time
  • S
  • Describe event of getting 1 heads
  • Event with one outcome is called

6
Example
  • A coin is tossed 2 times
  • S
  • Describe event of getting 1 heads and 1 tails
  • Event with more than one outcome is called

7
Review of Sets
  • The union of two events, A and B, is the event
    consisting of outcomes that are in either A or B
    or both
  • The Intersection of two events, A and B, is the
    event consisting of all outcomes that are in both
    A and B
  • The complement of an event A, denoted A, is the
    set of all outcomes in the sample space that are
    not in A

8
Visually
  • Union
  • Intersection
  • Complement

9
  • Two sets, A and B, are said to be mutually
    exclusive if they have no events in common
  • Visually

10
Example
  • Bag of balls has 5 red and 5 green balls
  • 3 are drawn at random
  • S

11
Example (continued)
  • A is the event that at least 2 green are chosen
  • A
  • B is the event that 3 green are chosen
  • B

12
Example (continued)
  • A

13
Probability
  • Probability of an event is the long-term
    proportion of times the event would occur if the
    experiment is repeated many times

14
Probability
  • Probability of event, A is denoted P(A)
  • Axioms
  • For any event, A,
  • P(S) 1
  • If A1, A2, , Ak are mutually exclusive events,
  • These imply that

15
Discrete Uniform Distribution
  • Sample space has k possible outcomes
    Se1,e2,,ek
  • Each outcome is equally likely
  • P(ei)
  • If A is a collection of distinct outcomes from S,
    P(A)

16
Example
  • A coin is tossed 1 time
  • S
  • Probability of observing a heads or tails is

17
Example
  • A coin is tossed 2 times
  • S
  • What is the probability of getting either two
    heads or two tails?
  • What is the probability of getting either one
    heads or two heads?

18
Example
  • Inherited characteristics are transmitted from
    one generation to the next by genes
  • Genes occur in pairs and offspring receive one
    from each parent
  • Experiment was conducted to verify this idea
  • Pure red flower crossed with a pure white flower
    gives
  • Two of these hybrids are crossed. Outcomes
  • Probability of each outcome

19
Note
  • Sometimes, not all outcomes are equally likely
    (e.g., fixed die)
  • Recall, probability of an event is long-term
    proportion of times the event occurs when the
    experiment is performed repeatedly
  • NOTE Probability refers to experiments or
    processes, not individuals

20
Probability Rules
  • Have looked at computing probability for events
  • How to compute probability for multiple events?
  • Example 65 of SFU Business School Professors
    read the Wall Street Journal, 55 read the
    Vancouver Sun and 45 read both. A randomly
    selected Professor is asked what newspaper they
    read. What is the probability the Professor
    reads one of the 2 papers?

21
  • Addition Rules
  • If two events are mutually exclusive
  • Complement Rule
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