Statistical Inference

Master the fundamentals of point estimation, confidence intervals, and hypothesis testing. Learn to draw meaningful conclusions from data and make informed engineering decisions.

Regression Analysis

Explore simple and multiple linear regression techniques to model relationships between variables. Apply these methods to predict outcomes and understand factor effects in engineering systems.

Design of Experiments

Learn systematic approaches to planning and analyzing experiments. Understand ANOVA, factorial designs, and how to efficiently extract maximum information from experimental data.

Course Information

Key details about the course:

  • Instructor: Mansur M. Arief
  • Department: Industrial and Systems Engineering, College of Computing and Mathematics
  • Prerequisites: ISE 205 or STAT 319
  • Textbook: D.C. Montgomery and C. Runger, "Applied Statistics and Probability for Engineers", 6th Edition
  • Visit the course page for the full syllabus, schedule, and grading information.
  • Check out the resources page for additional learning materials and references.
  • Questions? Visit the contact page for office hours and communication guidelines.