Statistics For Business And Economics

Front 1

Probability

Back 1

A numerical measure of the likelihood that an event will occur.

Front 2

Experiment

Back 2

A process that generates well-defined outcomes, meaning only one possible outcome will occur.

Front 3

Sample Space

Back 3

The set of all experimental outcomes.

Front 4

Sample Point

Back 4

An element of the sample space. A sample point represents an experimental outcome.

Front 5

Multiple-step Experiment

Back 5

An experiment that can be described as a sequence of steps. If a multiple-step experiment has k steps with n1 possible outcomes on the first step, n2 possible outcomes on the second step, and so on, the total number of experimental outcomes is given by (n1)(n2)...(nk).

Front 6

Tree Diagram

Back 6

A graphical representation that helps in visualizing a multiple-step experiment.

Front 7

Combination

Back 7

The number of ways n objects can be selected from among N objects without regard to the order in which the n objects are selected. Each selection of n objects is called a combination and the total number of combinations of N objects taken n at a time is N!/n!(N-n)!.

Front 8

Permutation

Back 8

The number of ways n objects mayb ne selected from among N objects when the order in which n objects are selected is important. Each ordering of n objects is called a permutation and the total number of permutations of N objects taken n at a time is N!/(N-n)!.

Front 9

Basic Requirements for Assigning Probabilities

Back 9

Two requirements that restrict the manner in which probability assignments can be made: 1. For each experimental outcome Ei, we must have 0<P(Ei)<1. 2. Considering all experimental outcomes, we must have P(E1)+P(E2)+...+P(En)= 1.

Front 10

Classical Method

Back 10

A method of assigning probabilities that is appropriate when all the experimental outcomes are equally likely.

Front 11

Relative Frequency Method

Back 11

A method of assigning probabilities that is appropriate when data are available to estimate the proportion of the time the experimental outcome will occur is the experiment is repeated a large number of times.

Front 12

Subjective Method

Back 12

A method of assigning probabilities on the basis of judgment and expertise.

Front 13

Event

Back 13

A collection of sample points.

Front 14

Complement of A

Back 14

An event consisting of all sample points that are not in A.

Front 15

Union of Two Events

Back 15

The event containing all sample points belonging to A or B or both.

Front 16

Intersection of Two Events

Back 16

The event containing the sample points belonging to both A and B.

Front 17

Addition Law

Back 17

A probability law used to compute the probability of the union of two events.

Front 18

Mutually Exclusive Events

Back 18

Events that have no sample points in common.

Front 19

Conditional Probability

Back 19

The probability of an event given that another event already occurred.

Front 20

Joint Probability

Back 20

The probability of two events both occurring: that is the probability of the intersection of two events.

Front 21

Marginal Probability

Back 21

The probability of each event taken separately when finding joint probability.

Front 22

Independent Events

Back 22

Two events A and B where the events have no influence on each other, so the probability of B occurring after A has occurred is P(B).

Front 23

Multiplication Law

Back 23

A probability law used to compute the probability of the intersection of two events.