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Objective: To be able to understand and apply the rules for probability.
Random: refers to the type of order that reveals itself after a large number of trials.
Probability of any outcome of a random phenomenon is the proportion of times the outcome would occur in a very long series of repetitions.
Types of Probability:
1. Empirical: probability based on observation.
Ex. Hershey Kisses:
2. Theoretical: probability based on a mathematical model.
Ex. Calculate the probability of flipping 3 coins and getting all head.
Sample Space: set of all possible outcomes of a random phenomenon.
Outcome: one result of a situation involving uncertainty.
Event: any single outcome or collection of outcomes from the sample space.
Methods for Finding the Total Number of Outcomes:
1. Tree Diagrams: useful method to list all outcomes in the sample space. Best with a small number of outcomes.
Ex. Draw a tree diagram and list the sample space for the event where one coin is flipped and one die is rolled.
2. Multiplication Principle: If event 1 occurs M ways and event 2 occurs N ways then events 1 and 2 occur in succession M*N ways.
Ex. Use the multiplication principle to determine the number of outcomes in the sample space for when 5 dice are rolled.
Sampling with replacement: when multiple items are being selected, the previous item is replaced prior to the next selection.
Sampling without replacement: then the item is NOT replaced prior to the next selection.
Rules for ProbabilityLet A = any event; Let P(A) be read as “the probability of event A”
1.
2.
3. If P(A) = 0 then A can never occur.
4. If P(A) = 1 then A always occurs.
5. ; the sum of all the outcomes in S equals 1.
6. Complement Rule: or is read as “the complement of A”
is read as “the probability that A does NOT occur”
or
Key words: not, at least, at most
7. The General Addition Rule: (use when selecting one item)
Ex. Roll one die, find
Ex. Roll one die, find
Events A and B are disjoint if A and B have no elements in common. (mutually exclusive)
8. Equally Likely Outcomes: If sample space S has k equally likely outcomes and event A consists of one of these outcomes, then Ex.
9. The Multiplication Rule: (use when more than one item is being selected)
If events A and B are independent and A and B occur in succession, the
Events A and B are said to be independent if the occurrence of the first event does not change the probability of the second event occurring.
Ex. TEST FOR INDEPENDENCE. Flip 2 coins, let A = heads on 1st and B = heads on 2nd. Are A and B independent?
Find Find
Any events that involve “replacement” are independent and events that involve “without replacement” are dependent.
IF EVENTS ARE DISJOINT, THEN THEY CAN NOT BE INDEPENDENT!!!!!
Ex. Let A = earn an A in Statistics; P(A) = 0.30
Let B = earn a B in Statistics; P(B) = 0.40
Are events A and B disjoint?
Are events A and B independent?
Independence vs. DisjointCase 1) A and B are NOT disjoint and independent.
Suppose a family plans on having 2 children and the P(boy) = 0.5
Let A = first child is a boy. Let B = second child is a boy
Are A and B disjoint?
Are A and B independent? (check mathematically)
Case 2) A and B are NOT disjoint and dependent. (Use a Venn Diagram for Ex)
Are A and B disjoint?
Are A and B independent? (check mathematically)
Case 3) A and B are disjoint and dependent.
Given P(A) = 0.2 , P(B) = 0.3 and P(A and B) = 0
Are A and B independent? (check mathematically)
(Also refer to example for grade in class)
Case 4) A and B are disjoint and independent.
IMPOSSIBLE
Ex. Given the following table of information regarding meal plan and number of days at a university:
A student is chosen at random from this university, find
P(plan A) P(5 days)
P(plan B and 2 days) P(plan B or 2 days)
Are days and meal plan independent? (verify mathematically)
Day/Meal Plan A Plan B Total:
2 0.15 0.20
5 0.20 0.25
7 0.05 0.15
Total: