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Transcript
Probability




Probability is a numerical
measurement of likelihood of an
event.
The probability of any event is a
number between zero and one.
Events with probability close to one
are more likely to occur.
If an event has probability equal to
one, the event is certain to occur.
Probability Notation
If A represents an event,
P(A)
represents the probability of
A.
Three methods to find
probabilities:

Intuition

Relative frequency

Equally likely outcomes
Intuition method
based upon our level of
confidence in the result
Example: I am 95% sure
that I will attend the party.
Probability
as Relative Frequency
Probability of an event =
the fraction of the time that the event
occurred in the past =
f
n
where f = frequency of an event
n = sample size
Example of Probability
as Relative Frequency
If you note that 57 of the last 100 applicants
for a job have been female, the
probability that the next applicant is
female would be:
57
100
Equally likely outcomes
No one result is expected to
occur more frequently than
any other.
Probability of an event when
outcomes are equally likely =
number of outcomes favorable to event
total number of outcomes
Example of Equally Likely
Outcome Method
When rolling a die, the probability of
getting a number less than three =
2
1

6
3
Law of Large Numbers
In the long run,
as the sample size increases and
increases, the relative frequencies of
outcomes
get closer and closer to
the theoretical (or actual) probability
value.
Example of Law of Large
Numbers



Flip a coin 10 times and record the outcomes.
(Do it now…ok 1 person do it…no need for
everyone to throw money around!)
Flip a coin 20 times and record the outcomes.
(Yes, do this now also!)
Flip a coin 30 times and record the outcomes.
(Don’t skip this step!)
Example of Law of Large
Numbers


What happens to the P(heads) vs P(tails)
as the sample space increases?
How does the actual result compare to the
theoretical result? What did happen vs
what should have happened?
Statistical Experiment
activity that results in a
definite outcome
Sample Space
set of all possible outcomes of
an experiment
Sample Space for the
rolling of an ordinary die:
1, 2, 3, 4, 5, 6
For the experiment of
rolling an ordinary die:



P(even number) = 3 = 1
6
2
P(result less than four)
3 = 1
6
2
P(not getting a two) = 5
6
Complement of Event A
Complement is not the same as Compliment
the event not A
Probability of a
Complement
P(not A) = 1 – P(A)
Probability of a Complement
If the probability that it will snow
today is 30%,
P(It will not snow) = 1 – P(snow) =
1 – 0.30 = 0.70
Probabilities of an Event and its
Complement




Denote the probability of an event by
the letter p.
Denote the probability of the
complement of the event by the
letter q.
p + q must equal 1
q=1-p
Probability
Related to Statistics


Probability makes statements about
what will occur when samples are
drawn from a known population.
Statistics describes how samples are
to be obtained and how inferences
are to be made about unknown
populations.