Chapter 10
•
A
random phenomenon
has outcomes that we cannot predict but that
nonetheless have a regular
distribution
in very many repetitions.
•
The
probability
of an
event
is the proportion of times the
event
occurs in many
repeated trials of a random phenomenon.
•
A
probability model
for a random phenomenon consists of a
sample space
S
and
an assignment of
probabilities
P
.
•
The
sample space
S
is the set of all possible outcomes of the random
phenomenon. Sets of outcomes are called
events
.
P
assigns a number
P
(
A
) to an
event
A
as its
probability
.
•
Any assignment of
probability
must obey the rules that state the basic properties
of
probability
:
1. 0 ≤
P
(
A
) ≤ 1 for any
event
A
.
2.
P
(
S
) = 1.
3.
Addition rule:
Events
A
and
B
are
disjoint
if they have no outcomes in common. If
A
and
B
are
disjoint
, then
P
(
A
or
B
) =
P
(
A
) +
P
(
B
).
4. For any
event
A
,
P
(
A
does not occur) = 1 −
P
(
A
).
•
When a
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 Fall '11
 
 Probability, Probability distribution, Probability theory

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