MATH 320 Probability
            This is a calculus-based probability course. It covers the following topics. (1) General Probability: set notation and basic elements of probability, combinatorial probability, conditional probability and independent events, and Bayes Theorem. (2) Single-Variable Probability: binomial, geometric, hypergeometric, Poisson, uniform, exponential, gamma and normal distributions, cumulative distribution functions, mean, variance and standard deviation, moments and moment-generating functions, and Chebysheff Theorem. (3) Multi-Variable Probability: joint probability functions and joint density functions, joint cumulative distribution functions, central limit theorem, conditional and marginal probability, moments and moment-generating functions, variance, covariance and correlation, and transformations. (4) Application to problems in medical testing, insurance, political survey, social inequity, gaming, and other fields of interest.
      
							
		
			 
		
	 
	
        
			
			 
		
            Note: Students whose prerequisites are not identified by the system should contact the Math and Statistics Department for an override at MATH@metrostate.edu.
      
	
                
        
            Prerequisites
Special information
												4 Undergraduate credits
																																				                        
                
                					Effective August 16, 2013 to present
Meets graduation requirements for
Learning outcomes
General
- Apply the theory of discrete and continuous random variables to solve problems in probability.
 - Utilize common discrete and continuous probability distributions.
 - Apply multivariate probability distributions, conditional expectations, and covariances.
 
Spring 2026
| Section | Title | Instructor | books | eservices | 
|---|---|---|---|---|
| 50 | Probability | Jacobson, David Willia | Books for MATH-320-50 Spring 2026 | Course details for MATH-320-50 Spring 2026 |