SCM ch. 4

Question 1

classical probability

Answer 1

a probability that is determined by dividing the number of possible outcomes of an event by the total number of possible outcomes in the sample space

Question 2

collectively exhaustive

Answer 2

describes a set of events where at least one of the events must occur during an experiment

Question 3

complement

Answer 3

all of the outcomes in the sample space that are not part of the event of interest

Question 4

empirical probability

Answer 4

a probability determined by counting the frequency of an event during an experiment

Question 5

event

Answer 5

one or more outcomes of an experiment that are a subset of the sample space

Question 6

experiment

Answer 6

the process of measuring or observing an activity for the purpose of collecting data

Question 7

law of large numbers

Answer 7

a law that states that when an experiment is conducted a large number of times, the empirical probabilities of the process will converge to the classical probabilities

Question 8

probability

Answer 8

a numerical value ranging from zero to one that represents the likelihood of a specific event occurring

Question 9

sample space

Answer 9

a set of all possible outcomes of an experiment

Question 10

simple event

Answer 10

an event with a single outcome in its most basic form that cannot be simplified

Question 11

simple probability

Answer 11

the likelihood of a single event occurring

Question 12

subjective probability

Answer 12

a probability that is calculated based on the experience and intuition of a person (or people). its made when classical and empirical probabilities cannot be calculated

Question 13

addition rule

Answer 13

a math rule used to calc the prob of the union of events

Question 14

bayes` theorem

Answer 14

used to calc P(A/B) from info about P(B/A)

Question 15

conditional prob (of A given B)

Answer 15

the prob of event A occurring given the condition of event B has already occurred

Question 16

contingency table

Answer 16

shows the number of occurrences of events of an experiment classified by two variables

Question 17

decision trees

Answer 17

display marginal and joint prob from a contingency table

Question 18

dependent events

Answer 18

events wherein the occurrence of one event affects the occurrence of another event

Question 19

independent events

Answer 19

events that have no impact on the prob of each other occurring

Question 20

intersection (of events A and B)

Answer 20

the number of instances in which event A and B occur at the same time

Question 21

joint prob

Answer 21

the prob of the intersection of two events

Question 22

marginal probs

Answer 22

simple probs found in margins, or row and column totals, of a contingency table

Question 23

multiplication rule

Answer 23

used to determine the prob of the intersection of two events

Question 24

mutually exclusive events

Answer 24

events that cannot occur at the same time

Question 25

posterior prob

Answer 25

a prob of an event occurring as determined without any additional info that could affect the event

Question 26

union (of events A and B)

Answer 26

all of the instances in which either event A or event B or both occur

Question 27

combinations

Answer 27

the number of different ways in which objects can be arranged without regard to order

Question 28

fundamental counting principle

Answer 28

this states that if there are k1 choices for the first event, k2 choices for the second event, and kn choices for the nth event, then the total number of possible outcomes are (k1)(k2)(k3)..(kn).

Question 29

permutations

Answer 29

the number of different ways in which objects can be arranged in order