Cryptography Reference
In-Depth Information
the ratio of the number of ways of success at getting 7 out of 12 tails divided
by the total number of possible outcomes.
In a more general scenario, we could define probability to be a map from a
subset
of the power set satisfying certain closure properties. However, to keep
the description simple, we will stick with the power set, which we call the
sample
space
, and the subsets of the power set are called
events
, as well as
outcomes
.
Now suppose that we have two experiments
S
and
T
with random events
S
and
T
. Then we can put them together and speak about the
joint random
events
). For instance, suppose that we have a standard deck of 52
cards and
S
consists of the event
the value of the card
, while
U
=(
S
,
T
T
consists of the
event
the suit of the card
. Then
) represents all the possibilities of the
52 outcomes of choosing a card. If
p
s,t
represents the probability that a card is
drawn with value
s
and suit
t
, then given a fair deck with
p
s
=1
/
13,
p
t
=1
/
4,
and
p
s,t
=1
/
52.
In general, we let
p
s,t
denote the probability that
s
U
=(
S
,
T
∈
S
and
t
∈
T
both
occur. It follows that
p
s
=
t
∈
T
p
s,t
,
so the probability of a fixed
s
∈
S
occurring is the sum of all the probabilities
of
t
∈
T
occurring along with
s
∈
S
occurring.
Independence
The two random events
s
∈
S
and
t
∈
T
, are called
independent
if
p
s,t
=
p
s
·
p
t
.
(E.1)
For instance, in the deck of cards illustration above, the suit and value of
the cards are independent events.
Conditional Probability
If we know that event
s
∈
S
has occurred, then the probability that
t
∈
T
will
occur
given
that
p
(
s
)
>
0, is defined as follows:
p
t
|
s
=
p
s,t
p
s
,
(E.2)
called the
conditional probability of
t
given
s
.
Notice that if we combine (E.1)-(E.2), we get that
s
and
t
are independent events if and only if
p
t
|
s
=
p
t
.
In other words, the probability that
t
occurs is unaffected by the probability
that
s
occurs.
In what follows, we assume that
s
and
s
are event subsets of
S
.
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