Basic Math for Analytics

Catalog description

Provides students with practical and applied foundational mathematics needed as background for success in data-driven decision making. Topics include sets, functions in single and multiple variables including logarithms, exponentials, and trigonometric; matrix algebra operations; introductory calculus concepts; and basic optimization principles necessary for data analysis. Introduction to applied software driven techniques is included in the course. Prerequisites: MTH 102 or MTH 121 or three years of college preparatory mathematics or permission of department chair. Co-requisites: STA 261 , ISA 225 , or STA 301 . Cross-listed with STA.