Week 2

Question 1

Probability

Answer 1

A number telling you the chance of an event occuring.

Question 2

Event

Answer 2

One or more outcomes, what you are finding the probability of.

Question 3

Experiment

Answer 3

Measuring or observing an activity to collect data

Question 6

Subjective Probability

Answer 6

Use when you can’t use classical or empirical probability. We then have to rely on or prior knowledge, experience, and judgement.

Examples:

- Possible Presidential Election Outcomes
- Future Market Patterns

Question 7

Complement

Answer 7

Everything that is not part of Event A.

1 - [Event A] = complement

Question 9

Law of Large Numbers

Answer 9

When an empirical experiment is conducted with extremely high numbers, then the result will match the hypothetical classical probability.

Question 10

Sample Space

Answer 10

All possible outcomes. (A Truth Chart)

Question 11

Simple Event

Answer 11

When an event cannot be more simplified. (Like rolling a 5 with one die.)

Question 12

Addition Rule

Answer 12

Calculates the probability of a union.

Question 13

Bayes’ Theorem

Answer 13

If we know that possibility that Event A will happen when Event B does, then we can calculate the probability of Event B occurring when Event A does.

Question 14

Conditional Probability (of A given B)

Answer 14

Probability that Event A will occur is Event B has or will occur.

Question 15

Dependent Events

Answer 15

Events that must occur in conjunction with another event.

Question 16

Independent Events

Answer 16

Occur without the impact of other events.

Question 17

Intersection

Answer 17

Number of times two (or more) separate events occur at the same time.

Question 18

Union

Answer 18

The number of times Event A occurs, Event B occurs, or Events A & B occur together.

Question 19

Simple Probabilty

Answer 19

Looking at a single event

Question 20

Empirical Probability

Answer 20

Use when you must conduct an experiment to observe the frequency of an event.

Examples:

- The average spending level of a store's customers
- Epidemiological research
- The efficacy of a certain education model

Question 21

Classical Probability

Answer 21

Use when we can determine all possible outcomes.

Examples:

- Rolling dice
- Choosing cards from a deck

Question 22

Marginal Probability

Answer 22

= simple probability. (looking at a single event)

Question 24

Posterior Probability

Answer 24

Probability of an event occurring, no matter what.

Question 25

Joint Probability

Answer 25

Probability of an intersection.

Question 26

Combinations

Answer 26

Number of ways a group of objects can be arranged without regard to order. So KQJ=QKJ=JQK=etc.

Question 27

Permutations

Answer 27

Number of ways that a group of objects can be arranged where order matters. So KQJ≢QKJ≢JKQ≢etc.

Question 28

Multiplication Rule

Answer 28

Finds the probability of an intersection. (Finds the joint probability)

Question 29

The Rules of Probability | There are 5

Answer 29

(1) If P(A)=1, then it must occur. (2) If P(A)=0, then it can never occur. (3) Probability must fall between 0-1. (4) All possible probabilities must add up to 1. (5) The compliment to A must include all of the outcomes that are not A.

Question 30

Fundamental Counting Principle

Answer 30

The number of ways an event can occur.

Question 31

Mutually Exclusive Events

Answer 31

Events that can never occur at the same time.

Question 32

Contingency Table

Answer 32

Number of event occurrences in a table with two or more categories.

Question 33

Decision Trees

Answer 33

Displays joint and marginal probability taken from a contingency table.

Question 36

Collectively Exhaustive

Answer 36

When the sample space (Truth Chart) contains all possible outcomes. Corresponds with "classical probability."