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30 Cards in this Set
 Front
 Back
Bayes’ Theorem

A formula that is used to revise probabilitiesbased on new information.


Bernoulli Process

A process with two outcomes in each of aseries of independent trials in which the probabilities of theoutcomes do not change.


Binomial Distribution

A discrete distribution that describesthe number of successes in independent trials of a Bernoulliprocess.


Classical or Logical Approach

An objective way of assessingprobabilities based on logic.


Collectively Exhaustive Events

A collection of all possibleoutcomes of an experiment.


Conditional Probability

The probability of one event occurringgiven that another has taken place.


Continuous Probability Distribution

A probability distributionwith a continuous random variable.


Continuous Random Variable

A random variable that canassume an infinite or unlimited set of values.


Dependent Events

The situation in which the occurrence ofone event affects the probability of occurrence of someother event.


Discrete Probability Distribution

A probability distributionwith a discrete random variable.


Discrete Random Variable

A random variable that can onlyassume a finite or limited set of values.


Expected Value

The (weighted) average of a probabilitydistribution.


F Distribution

A continuous probability distribution that isthe ratio of the variances of samples from two independentnormal distributions.


Independent Events

The situation in which the occurrenceof one event has no effect on the probability of occurrenceof a second event.


Joint Probability

The probability of events occurringtogether (or one after the other).


Marginal Probability

The simple probability of an event occurring.


Mutually Exclusive Events

A situation in which only oneevent can occur on any given trial or experiment.


Negative Exponential Distribution

A continuous probabilitydistribution that describes the time between customerarrivals in a queuing situation.


Normal Distribution

A continuous bellshaped distributionthat is a function of two parameters, the mean and standarddeviation of the distribution.


Poisson Distribution

A discrete probability distributionused in queuing theory.


Prior Probability

A probability value determined beforenew or additional information is obtained. It is sometimescalled an a priori probability estimate.


Probability

A statement about the likelihood of an eventoccurring. It is expressed as a numerical value between 0and 1, inclusive.


Probability Density Function

The mathematical functionthat describes a continuous probability distribution. It isrepresented by f(X).


Probability Distribution

The set of all possible values of arandom variable and their associated probabilities.


Random Variable

A variable that assigns a number to everypossible outcome of an experiment.


Relative Frequency Approach

An objective way ofdetermining probabilities based on observing frequenciesover a number of trials.


Revised or Posterior Probability

A probability value that resultsfrom new or revised information and prior probabilities.


Standard Deviation

The square root of the variance


Subjective Approach

A method of determining probabilityvalues based on experience or judgment.


Variance

A measure of dispersion or spread of the probabilitydistribution.
