AP Stats Probability Vocab

Bernoulli Trial

a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is conducted.

Continuous Random Variable

can take on any value within a range of values.

Discrete Random Variable

discrete variables can take on only certain values

Dependent events

he probability of one event occurring influences the likelihood of the other event.

Variance

measures how far each number in the set is from the mean

10% Condition

states that sample sizes should be no more than 10% of the population

Theoretical Probability

the number of ways that the event can occur, divided by the total number of outcomes.

Independent events

the probability that one event occurs in no way affects the probability of the other event occurring

Empirical Probability

the ratio of the number of outcomes in which a specified event occurs to the total number of trials, not in a theoretical sample space but in an actual experiment.

Complement Rule

the sum of the probabilities of an event and its complement must equal 1

Geometric Probability Model

a kind of discrete probability distribution that applies to Bernoulli trials when you try, and try, and try again until you get a success

Probability Model

a mathematical representation of a random phenomenon.

Expected Value

a predicted value of a variable, calculated as the sum of all possible values each multiplied by the probability of its occurrence.

Standard Deviation

a quantity calculated to indicate the extent of deviation for a group as a whole.

Normal Model

A probability distribution that plots all of its values in a symmetrical fashion and most of the results are situated around the probability's mean

Sample Space

A set of elements that represents all possible outcomes of a statistical experiment

Event

A subset of a sample space - one or more sample points .

Binomial Model

An experiment with a fixed number of independent trials, each of which can only have two possible outcomes.

Outcome

An individual result of a component of a simulation

Tree diagram

Diagram used to calculate the probability of outcomes occurring

Law of Large Numbers

The idea that the relative frequency of an event will converge on the probability of the event, as the number of trials increases

Conditional Probability

The probability that Event A occurs, given that Event B has occurred

Multiplication Rule

The probability that Events A and B both occur is equal to the probability that Event A occurs times the probability that Event B occurs, given that A has occurred.

Success/Failure Condition

The sample size must be large enough so that we can expect at least 10 "successes" and 10 "failures".

Trial

The sequence of several components representing events that we are pretending will take place

Mutually exclusive/disjoint events

Two events are disjoint if they cannot occur simultaneously.

Random variable

When the value of a variable is determined by a chance event

Addition Rule

When two events, A and B, are mutually exclusive, the probability that A or B will occur is the sum of the probability of each event