1outcome space
a set of possible outcomes usually written in brackets
2Example of outcome space
For a coin flip {H,T}
For flipping a coin twice {HH,HT,TH,TT}
3Outcome
A subset of the outcome space
4Example of outcome
Outcome of heads in a coin flip {H}
5Probability Function
Is denoted as Pr().
It is a function that maps outcomes to probabilities.
6Pr(A) = X
A is the outcome. It is the input to the probability function.
X is the probability. It is the output of the probability functno
7Example of probability. Pr(Heads)=
0.5
8Probabilities range from
0(will not happen with certainty) to 1(will happen with certainty)
9The probability of rolling a seven with a six-sided die is
ZERO!
10Everything Rule
The probability of the entire outcome set is 1
11Example of everything rule
Rolling 1-6 with a six-sided die is 1
12Not Rule
The probability of anything but outcome A, which we call Pr(Not A), =1-Pr(A)
13Probability of Not Rule Example
Probability of a American roulette wheel is red.
Pr(Red) = 9/19, so the probability of any other outcome.
Pr(Not Red), is equal to 1-9/19, or 10/19
14Equal probability
If all outcomes have equal probability, then the probability of any outcome is 1/n, where n is the number of possible outcomes
15Independent
one occuring event DOES NOT change the probability of the other event occuring
16Mutually Exclusive
it is impossible for both events to happen
17Conjunction or Joint probability
Two outcomes are independent. Probability of outcome A and outcome B both happening.
Pr(A & B) is Pr(A) * Pr(B)
18Example of Conjunction or Joint Probability
I flip a coin twice. What is the probability that the coin lands heads first and tails second (HT)?
Pr (H in first flip) = 1/2 and Pr (T in second flip) = 1/2, so Pr(HT)= 1/2 * 1/2 = 1/4
19Disjunction
The probability of either outcome A or outcome B occuring.
Denoted Pr(A \/ B) or Pr (A or B), is Pr(A) + Pr(B) - Pr(A&B).
If the outcomes are independent, Pr (A \/ B) = Pr (A) + Pr(B) - Pr(A) * Pr (B)
If outcomes are mutually exclusive, so Pr(A&B) must equal 0, so Pr(A \/ B) = Pr(A) + Pr(B)