BNAD 276 Lecture Notes - Lecture 5: Probability Mass Function, Cumulative Distribution Function, Random Variable

• School: University of Arizona
• Department: Business Administration
• Course: BNAD 276
• Professor: brentmarinan

Document Summary

A function that assigns numerical values to the outcomes of a random experiment. Values of the random variable are denoted by corresponding lowercase letters. Corresponding values of the random variable: x1, x2, x3, Discrete: the random variable assumes a countable number of distinct values. Continuous: the random variable is characterized by (infinitely) uncountable values within any interval. Every random variable is associated with a probability distribution that described the variable completely. A probability mass function: is used to describe discrete random variables. A probability density function: is used to describe continuous random variables. A cumulative distribution function: may be used to describe either discrete or continuous random variables.