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  1. AP Digital Sat
FlashcardFlashcardStudy GuideStudy GuideQuestion BankQuestion BankGlossaryGlossary

Glossary

A

Addition Rule (for 'OR')

Criticality: 3

Used to find the probability of either event A or event B occurring: P(A or B) = P(A) + P(B) - P(A and B).

Example:

To find the probability of drawing a king or a heart from a deck, you'd use the addition rule (for 'OR'), accounting for the king of hearts overlap.

C

Calculating Probability

Criticality: 3

The method of determining the likelihood of an event by dividing the number of favorable outcomes by the total number of possible outcomes, assuming outcomes are equally likely.

Example:

To find the calculating probability of drawing a red card from a standard deck, you'd divide 26 (favorable) by 52 (total), resulting in 0.5.

Complement of an Event (A')

Criticality: 2

All outcomes in the sample space that are not part of a given event A. Its probability is P(A') = 1 - P(A).

Example:

If event A is rolling a 6 on a die, the complement of an event (A') is rolling any number other than 6.

Compound Event

Criticality: 2

An event that consists of two or more simple events combined.

Example:

Flipping a coin and getting heads, and then rolling a die and getting an even number, is a compound event.

Conditional Probability

Criticality: 3

The probability of an event A occurring given that another event B has already occurred, denoted as P(A|B) = P(A and B) / P(B).

Example:

The conditional probability of a student passing a test, given that they studied for more than 5 hours, would be calculated using this concept.

E

Event

Criticality: 3

A specific outcome or a collection of outcomes from a sample space that you are interested in.

Example:

If you roll a die, getting an even number (2, 4, or 6) is an event.

L

Law of Large Numbers

Criticality: 2

A principle stating that as the number of trials in a random experiment increases, the relative frequency of an event tends to get closer to its true theoretical probability.

Example:

The more times you flip a fair coin, the closer the relative frequency of heads will get to 0.5, illustrating the Law of Large Numbers.

M

Measurement Error

Criticality: 1

The difference between a measured value and the true value, which can occur due to inaccuracies in instruments or procedures.

Example:

If a scale consistently reads 1 pound heavier than the actual weight, this is a form of measurement error.

Multiplication Rule (for 'AND', Dependent Events)

Criticality: 3

Used to find the probability of two dependent events A and B both occurring: P(A and B) = P(A) × P(B|A), where P(B|A) is the conditional probability of B given A.

Example:

To find the probability of drawing a red card, and then drawing another red card without replacement, you'd use the multiplication rule (for 'AND', dependent events).

Multiplication Rule (for 'AND', Independent Events)

Criticality: 3

Used to find the probability of two independent events A and B both occurring: P(A and B) = P(A) × P(B).

Example:

The multiplication rule (for 'AND', independent events) helps calculate the probability of flipping a coin and getting heads, and then rolling a die and getting a 3.

P

Probability

Criticality: 3

The numerical measure of the likelihood that an event will occur, expressed as a value between 0 (impossible) and 1 (certain).

Example:

The probability of flipping a fair coin and getting heads is 0.5.

R

Relative Frequency

Criticality: 3

An estimate of probability based on observed data, calculated as the number of times an event occurs divided by the total number of trials.

Example:

If a basketball player makes 7 out of 10 free throws in practice, their relative frequency of making a free throw is 0.7.

S

Sample Size

Criticality: 2

The number of observations or individuals included in a statistical sample, which affects the reliability of probability estimates.

Example:

A survey of 10,000 people has a larger and generally more reliable sample size than a survey of 100 people.

Sample Space

Criticality: 3

The set of all possible outcomes of a random experiment.

Example:

When rolling a standard six-sided die, the sample space is {1, 2, 3, 4, 5, 6}.

Sampling Bias

Criticality: 2

A systematic error in the selection of a sample that causes it to not be representative of the population, leading to inaccurate conclusions.

Example:

Surveying only students in advanced math classes to gauge overall student interest in math could introduce sampling bias.

Simple Event

Criticality: 1

An event that consists of only one outcome from the sample space.

Example:

Rolling a 7 on a 10-sided die is a simple event.