Transcript PROBABILITY

PROBABILITY
Chapter 9
Section 9-1
Review Percents and
Probability
Experiment
An activity that is used to
produce data that can be
observed and recorded
Example – rolling a die
Example - tossing a coin
Example – drawing a card
Outcome
The result of each trial of an
experiment.
Event
Any one of the possible
outcomes or combination of
possible outcomes of an
experiment
Experimental Probability
Represents an estimate of the
likelihood of an event, E, or
desired outcome
P(E)= # of observations of E
total # of observations
Theoretical Probability
P(E) = # of favorable outcomes
# of possible outcomes
Sample Space
The set of all possible
outcomes of the experiment
Tossing a coin –
S = {H, T}
Rolling a dice –
S = {1, 2, 3, 4, 5, 6}
Tree Diagram
A diagram that lists one part
of an event and then adds
branches to show all the
outcomes involving that part
of the event
Example
In an experiment, a coin is
tossed and a number cube is
rolled.
 Make a tree diagram
beginning with the possible
outcomes of the coin toss
Relative Frequency
Compares the number of times
the outcome occurs to the total
number of observations
Example
The more often you toss a
coin, the closer you will
come to tossing an equal
number of heads and tails.
Section 9-2
Problem Solving Skills:
Simulations
Section 9-3
Compound Events
Compound Event
Made up of two or more
simpler events
Probability of a compound
event is the probability of
one event and/or another
occurring
Probability
The probability of a
compound event is
represented by P(A ∩ B)
The probability of one event
or another occurring is
written P(A  B)
MUTUALLY EXCLUSIVE EVENTS
Events that cannot occur at
the same time
Example – A die is rolled.
The events, getting an even
number and getting an odd
number are mutually
exclusive.
MUTUALLY EXCLUSIVE EVENTS
If two events A and B are
mutually exclusive then
AB=Ø
and
Mutually Exclusive Events
For mutually exclusive
events only:
P(A  B) = P(A) + P(B)
EXAMPLE – MUTUALLY EXCLUSIVE
EVENTS
• Suppose a die is tossed.
• Let A be the event that an
even number turns up
• Let B be the event that an
odd number turns up, then
Mutually Exclusive Events
A = {2, 4, 6}, and B = {1, 3, 5}
AB=Ø
THEOREM
If A and B are not mutually
exclusive events, then
P(A  B)
=
P(A) + P(B) – P(A  B)
Example A card is drawn at random from a
deck of 52 playing cards. Find the
probability that the card is a heart
or an ace.
A = card is a heart
B = card is an ace
P(A  B) = P(A) + P(B) – P(A  B)
Section 9-4
Independent and
Dependent Events
INDEPENDENT EVENTS
Two events are independent
if the result of the second
event is not affected by the
result of the first event.
INDEPENDENT EVENTS
The events A and B are
independent if, and only if
P(A  B) = P(A) • P(B)
Example
A bag contains 3 red marbles, 4
green marbles and 5 blue
marbles. One marble is taken at
random and then replaced. Then
another marble is taken at
random.
Find the probability that the 1st
marble is red and the 2nd is blue.
DEPENDENT EVENTS
Two events are dependent if
the result of one event is
affected by the result of
another event
DEPENDENT EVENTS
The result of event A affects
event B
P(A  B) =
P(A) • P(B, given that A occurred)
P(A) • P(B|A)
Example
A bag contains 3 red marbles, 4
green marbles and 5 blue
marbles. One marble is taken
at random and is not replaced.
Then another marble is taken at
random.
 Find the probability that the 1st
marble is red and the 2nd is
blue.
Section 9-5
Permutations and
Combinations
Fundamental Counting Principle
If there are two or more
stages of an activity, the total
number of possible
outcomes is the product of
the number of possible
outcomes for each stage
Example
At a pizza place there are
three sizes (Large, Medium,
and Small). There are also
five choices of toppings
(cheese, pepperoni,
sausage, onions, peppers).
How many different pizzas
with one topping could a
customer order?
What is the probability that a
customer will order a
Medium pizza with sausage?
Example
A store sells shirts in 8 sizes.
For each size, there is a
choice of 5 colors. For each
color, there is a choice of 6
patterns. How many
different shirts does the store
have?
What is the probability that a
customer will buy a large
shirt that is blue with stripes?
PERMUTATION
An arrangement of items in
a particular order.
n! (n factorial)
n(n-1)(n-2)…(2)(1)
FACTORIAL
5! = 5 x 4 x 3 x 2 x 1
0! = 1
EXAMPLE PERMUTATIONS
How many different “ways”
can the letters a, b, and c
be arranged if all the
letters are used?
3!
(a,b,c), (a,c,b), (b,c,a),
(b,a,c), (c,a,b), (c,b,a)
PERMUTATIONS
NO REPETITIONS
Uses only a part of the set
without repetitions
nPr = n!__
(n-r)!
n = number of items
r = number of items taken at
a time
EXAMPLE PERMUTATIONS
How many different “ways”
can the letters a, b, c, and
d be arranged if only three
different letters are used?
4!__
(4 - 3)!
ANSWER
How many different “ways”
can the letters a, b, c, and
d be arranged if only three
different letters are used?
4! = 24
COMBINATION
An arrangement of items in
which order is not
important.
nCr = n!__
(n-r)!r!
COMBINATION
nCr =
n!__
(n-r)!r!
n = number of different items
r = number of items taken at
a time
EXAMPLE COMBINATIONS
How many different ways can
a 2-person committee be
chosen from 8 people if there
are no restrictions?
8!____
(8 - 2)!2!
EXAMPLE COMBINATIONS
A random drawing is held to
determine which 2 of the 6
members of the math club will
be sent to a regional math
contest.
How many different pairs of two
could be sent to the contest?
EXAMPLE COMBINATIONS
How many combinations of
three letters could you make
out of the letters a, b, c, d, e,
and f?
EXAMPLE COMBINATIONS
A popular touring band has
20 songs. How many
combinations of songs can
the band play in their
opening 3-song set?
Section 9-6
Scatter Plots and Boxplots
SCATTER PLOT
A type of visual display
showing a relationship
between two sets of data,
represented by
unconnected points on a
grid.
Factory Wages
14
12
Hourly Pay
10
8
6
4
2
0
0
2
4
6
8
Years of Experience
10
12
14
16
BOX-AND-WHISKER PLOT
A type of visual display
showing how data are
dispersed around a
median. It does not show
specific items in the data.
but
BOX-AND-WHISKER PLOT
It shows the median and the
extremes of a set of data.
The lower half of the data,
called the lower quartile, and
the median of the upper half
called the upper quartile.
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