Probability In statistics
Basic idea
Experiment: a process the results in an outcome that cannot be predicted in advance with certainty.
Toss a Coin
S = {H,T}
Sample space: set of all possible outcomes
Rolling a die
S = {1,2,3,4,5,6}
Event: subset of the sample space
Back to the examples:
Let even A
be the roll of 1, A
={1}
Let event E
be an even role, E
={2,4,6}
Up to this point, you have been a “frequentist”
Plugging in the numbers:
Basic Axioms:
Axioms are the basic building blocks of probability theory.
Here are the three basic axioms:
P(a) is greater than or equal to 0, but less than or equal to 1 for all events a
P(S) is equal to 1
P(A or B) = P(A) + P(B) - P(A and B)
Ven Diagrams
Setting up the environment:
- Not in A
- Not in B
- A and B
- A or B
- DeMorgans Law
DeMorgan’s Law states that the complement of the union of two sets is equal to the intersection of the complements of the two sets.
Lets examine the ideas DeMorgans Law presents.
Quantification vs Complement
Quantification | Complement |
---|---|
All 5 | Not all 0, 1, 2, 3, 4 |
1,2,3,4,5 | Not some |
Are events mutually exclusive?
Depends on the problem.
Lets look at a deck of cards:
Deck of Cards
S = {52 cards} A = {red cards} B = {face cards} A and B = {red face cards}
Are A and B mutually exclusive?
No, because there are red face cards.
The intersection of A and B is not empty.