ISE 301 - Fundamentals of Statistics for Industrial Engineering

This course introduces industrial and systems engineering students to the fundamental concepts and methods of applied statistics used in data-driven decision-making. Topics include descriptive statistics, probability theory, random variables, sampling distributions, confidence intervals, hypothesis testing, regression analysis, and analysis of variance. Students will develop proficiency in data analysis and visualization using Microsoft Excel, while also strengthening their ability to interpret and communicate statistical results in written reports and professional presentations.

Prerequisites & Notes: College-level math course: Calculus III or equivalent
Credits: 4
Grade Mode: Letter