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1
Chapter 2, Sections 4-5
A Probability Model
The Discrete Case
©
John J Currano,
01/25/2010
2
Terminology
(Random) Experiment
•
The outcome cannot be predicted with certainty
•
The set of all possible outcomes can be described
Examples
•
Toss a coin and observe the face that shows
•
Toss a die and observe the top face
•
Sample output from an industrial process
Sample Space
– Set of all possible outcomes
•
Its elements are called
Sample Points
or
Outcomes
•
Its subsets are called
Events
•
Simple Event
: a subset with only one outcome
•
Compound Event
: subset with more than one outcome
3
Terminology
(Random) Experiment
Sample Space
– Set of all possible outcomes
• Subsets:
Events
• Elements:
Sample Points
or
Outcomes
Discrete Sample Space
– Finite or Countably Infinite
Example
: Toss a die and observe the top face
S
1
= { 1, 2, 3, 4, 5, 6 }
S
2
= { even, odd }
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Terminology
(Random) Experiment
Sample Space
– Set of all possible outcomes
A
Probability Model
for an experiment consists of:
• A
Sample Space
,
S
• A
Probability Measure
on
S
A real-valued function,
P
, defined on the subsets
of
S
(the events) that satisfies certain axioms

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