AHSS Ch. 3.1-3.3 Probability

Relative Frequency Probability

The proportion of times the outcome would occur if we observed the random process an infinite number of times.

Relative Frequency

The proportion of times the event occurs out of
the number of trials.

Law of Large Numbers

As more observations are collected, the observed proportion of occurrences with a particular outcome after n trials converges to the true probability P of that outcome.

Disjoint or Mutually Exclusive

The relationship of two outcomes that cannot both happen in the same trial, i.e. P(A and B) = 0.

Addition Rule for disjoint events

If outcomes are disjoint, the probability that one or the other occurs is found by adding their individual probabilities.

Venn Diagrams

Useful when outcomes can be categorized as "in" or "out" for two or three variables, attributes, or random processes.

General Addition Rule

P(A or B) = P(A) + P(B) - P(A and B)

?

Symbol for intersection / "and

U

Symbol for union / "or" (inclusive)

Sample Space (S)

The set of all possible outcomes. The total probability of a sample space must equal 1.

Complement

An event A together with its complement comprise the entire sample space.

Independent events

The outcome of one does not change the likelihood of the outcome of the other, i.e. P(A | B) = P(A).

Multiplication Rule for independent events

The probability of 2
independent
events can be calculated as the product of their unconditional probabilities.

Conditional Probability

The probability of an event is computed under another condition (a known outcome or event). The outcome of interest A given condition B is
computed as:
P(A|B) =P(A and B)/P(B)

Joint Probability

A probability that measures the likelihood two or more events will happen concurrently.

Joint/And Probabilities from a tree diagram

When there are two events, this is found as P(A) x P(B | A)

General Multiplication Rule

P(A and B) = P(A)
P(B|A) = P(A|B)
P (B)

Independent Events Check

If one of the following holds true: P(A|B)=P(A) ,
P(A and B)=P(A)*P(B), then A and B are independent

Mutually Exclusive (Disjoint) Check

If one of the following holds true: P(A and B) = 0,
P(A or B) = P(A) + P(B), then A and B are mutually exclusive (disjoint)

Tree Diagrams

A branched diagram used to organize outcomes and probabilities; most useful when two or more processes occur in a sequence and each process is conditioned on its predecessors.

Bayes' Theorem

A theorem used to find inverse probabilities. It can be derived using a tree diagram (see diagram)
� The numerator identifies the probability of getting both A and B.
� The denominator is the overall probability of getting B. Traverse each branch of the t

Binomial Formula Check

Four conditions to check.
(1) The trials are independent.
(2) The number of trials, n, is fixed.
(3) Each trial outcome can be classified as a success or failure.
(4) The probability of a success, p, is the same for each trial.

Binomial Formula

Suppose the probability of a single trial being a success is p. Then the probability
of observing exactly x successes in n independent trials is given by

Binomial coefficient

n choose x = n!/[x!(n-x)!]; computes the number of combinations with exactly x success in n trials:

primary branch of tree diagram

Corresponds to unconditional probabilities of the form P(A)

secondary branch of tree diagram

corresponds to conditional probabilities of the form P(B | A)

P(at least 1)

Solve via complements; P(at least 1) = 1 - P(none)