Chapter 5 Flashcards
Random Variable
Function that assigns numerical values to the outcomes of an experiment
Discrete (random) Variable
Variable that assumes a countable number of values
Continuous Random Variable
Variable that assumes uncountable values in an interval
Probability Distribution
Every random variable is associated with a probability distribution that describes the variable completely.
Probability Mass Function
Provides the probability that a discrete random variable takes on a particular value
Expected Value (Population Mean)
Weighted average of all possible values of a random variable
Risk Neutral
Someone who is indifferent to risk and makes his/her decisions solely on the basis of the expected gain
Risk-Averse Consumer
Someone who takes risk only if it entails a suitable compensation and may decline a risky prospect
Risk-Loving
Someone who may accept a risky prospect even if expected gain is negative
Bernoulli Process
Series of n independent and identical traits of an experiment either success or failure, and each time the trial is repeated, the probabilities of success and failure remain the same
Binomial Random Variable
Number of successes achieved in the n trials of a Bernoulli process
Probability Tree
Graphical representation of the various possible sequences of an experiment
Binomial Distribution
Description of the probabilities associated with the possible values of a binomial random variable
Poisson Distribution
Description of probabilities associated with the possible values of a Poisson random value
Poisson Random Variable
Number of successes over a given interval of time or space in a Poisson process
