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== Experiments and Outcomes ==
== Experiments, Outcomes and Events ==


The easiest way to think of probability is in terms of experiments and their potential outcomes.  Many examples can be drawn from everyday experience:  the weather today will include "rain", "overcast skies", "sun with no clouds".  These are examples of outcomes from an experiment of observing weather patterns for the day.  There is no implication that these outcomes are mutually exclusive.  We can have "rain" in the morning followed by "sun with no clouds" in the afternoon.  Perhaps a more illustrative example is to consider outcomes from drawing a card from a deck of 52.  Outcomes of interest can be any of the following: "the card is a spade", "the card is a five", "the card is not a face card",...
The easiest way to think of probability is in terms of experiments and their potential outcomes.  Many examples can be drawn from everyday experience:  On the drive home from work, you can encounter a flat tire, or have an uneventful drive; the outcome of an election can include either a win by candidate A, B, or C, or a runoff.


'''Definition:''' The entire collection of possible outcomes from an experiment is termed the ''sample space'', indicated as '''<math>\Omega</math>'''
'''Definition:''' The entire collection of possible outcomes from an experiment is termed the ''sample space'', indicated as '''<math>\Omega</math>'''


The simplest (albeit uninteresting) example would be an experiment with only one outcome, say <math>A</math>.  If we remember our set theory from elementary school, we can expressed the sample space as follows:
The simplest (albeit uninteresting) example would be an experiment with only one possible outcome, say <math>A</math>.  If we remember our set theory from elementary school, we can expressed the sample space as follows:
<math>\Omega = \{ A \} </math>
<math>\Omega = \{ A \} </math>
A more interesting example is the result of rolling a six sided dice.  The sample space for this experiment is:
<math>\Omega = \{ 1,2,3,4,5,6 \}</math>
We may be interested in 'events' in an experiment.
'''Definition:''' An ''event'' is some subset of outcomes from the ''sample space''
In the dice example, events of interest might include
- the outcome is an even number
- the outcome is less than three

Revision as of 15:39, 28 June 2005

Experiments, Outcomes and Events

The easiest way to think of probability is in terms of experiments and their potential outcomes. Many examples can be drawn from everyday experience: On the drive home from work, you can encounter a flat tire, or have an uneventful drive; the outcome of an election can include either a win by candidate A, B, or C, or a runoff.

Definition: The entire collection of possible outcomes from an experiment is termed the sample space, indicated as <math>\Omega</math>

The simplest (albeit uninteresting) example would be an experiment with only one possible outcome, say <math>A</math>. If we remember our set theory from elementary school, we can expressed the sample space as follows: <math>\Omega = \{ A \} </math>

A more interesting example is the result of rolling a six sided dice. The sample space for this experiment is: <math>\Omega = \{ 1,2,3,4,5,6 \}</math> We may be interested in 'events' in an experiment. Definition: An event is some subset of outcomes from the sample space

In the dice example, events of interest might include - the outcome is an even number - the outcome is less than three