STAT 320 - Introduction to Probability Theory I

Units: 3
The theory of probability with applications to science and engineering. Selected topics may include: sample spaces; random variables; joint, marginal, conditional distributions; sampling and sampling distributions, expectations; probability distributions (binomial, Poisson, normal, etc.); and moment generating functions.

Prerequisites: MATH 130.
Possible Instructional Methods: On-ground.
Grading: A-F or CR/NC (student choice).
Course Typically Offered: Fall & Spring

Student Learning Outcomes - Upon successful completion of this course students will be able to:

use basic rules of probability theory and their applications to probability modeling.
derive and understand the theory of point and interval estimation and hypothesis testing.
formulate and model practical problems for solutions using these statistical methodologies.
produce relevant computer output using statistical software and interpret results as appropriate.