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USD Year 1 Semester 1 > Business Statistics Exam 3 Terms > Flashcards

Business Statistics Exam 3 Terms Flashcards

1
Q

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

A

Classical Method

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2
Q

A process that generates well-defined outcomes

A

Probability Experiment

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3
Q

A method of assigning probabilities on the basis of judgment

A

Subjective Method

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4
Q

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

A

Relative Frequency Method

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5
Q

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

A

Tree Diagram

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6
Q

A graphical representation for showing symbolically the sample space and operations involving events in which the sample space is represented by a rectangle and events are represented as circles within the sample space

A

Venn Diagram

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7
Q

In an experiment we may be interested in determining the number of ways n objects may be selected among N objects without regard to the order in which the n objects are selected

A

Combination

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8
Q

In an experiment we may be interested in determining the number of ways n objects may be selected from among N objects when the order in which the n objects are selected is important

A

Permutation

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9
Q

The event containing all sample points belonging to or both

A

Union

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10
Q

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

A

Addition Law

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11
Q

Events that have no sample points in common

A

Mutually Exclusive Events

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12
Q

The event consisting of all sample points that are not in

A

Complement

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13
Q

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

A

Intersection

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14
Q

Two events A and B where or ; that is, the events have no influence on each other

A

Independent Events

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15
Q

A probability law used to compute the probability of the intersection of two events. It is or . For independent events it reduces to

A

Multiplication Law

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16
Q

The probability of two events both occurring; that is, the probability of the intersection of two events

A

Joint Probability

17
Q

The values in the margins of a joint probability table that provide the probabilities of each event separately

A

Marginal Probability

18
Q

The probability of an event given that another event already occurred

A

Conditional Probability

19
Q

Initial estimates of the probabilities of events

A

Prior Probabilities

20
Q

Revised probabilities of events based on additional information

A

Posterior Probabilities

21
Q

A method used to compute posterior probabilities

A

Bayes’ Theorem

22
Q

A numerical description of the outcome of an experiment

A

Random Variable

23
Q

A random variable that may assume either a finite number of values or an infinite sequence of values

A

Discrete Random Variable

24
Q

A random variable that may assume any numerical value in an interval or collection of intervals

A

Continuous Random Variable

25
Q

A function, denoted by f(x), that provides the probability that x assumes a particular value for a discrete random variable

A

Probability Function

26
Q

A description of how the probabilities are distributed over the values of the random variable

A

Probability Distribution

27
Q

A discrete probability distribution for which the relative frequency method is used to assign the probabilities

A

Empirical Discrete Distribution

28
Q

A measure of the central location of a random variable

A

Expected Value

29
Q

A measure of the variability, or dispersion, of a random variable

A

Variance

30
Q

The positive square root of the variance

A

Standard Deviation

31
Q

A probability distribution for which each possible value of the random variable has the same probability

A

Discrete Uniform Probability Distribution

32
Q

An experiment having the four properties:
-Consists of n identical trials
-Two outcomes possible on each trial
-Probability of “succses” (p) on each trial is the same
-Trials are independent

A

Binomial Experiment

33
Q

A probability distribution showing the probability of x successes in n trials of a binomial experiment

A

Binomial Probability Distribution

34
Q

A probability distribution showing the probability of x occurrences of an event over a specified interval of time or space

A

Poisson Probability Distribution

35
Q

A probability distribution showing the probability of x successes in n trials from a population with r successes and N - r failures

A

Hypergeometric Probability Distribution

USD Year 1 Semester 1 (6 decks)

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