3 credits
Fall 2026 Lecture
This course provides a critical foundation necessary for understanding Bayesian theory and employing that theory in the analysis of typical data generated in industry. The course will focus specifically on solutions of aviation-related problems through data analysis. Material includes overview and implementation of relevant statistical software applications. Practical skills in presenting advanced analyses to both professional and scientific audiences is a key component of the course. Prerequsites: AT 50700 OR IT 50700 OR STAT 30100 OR STAT 50100 OR STAT 51100. Permission of instructor required.
Learning Outcomes1Articulate and define basic concepts in probability theory, modeling, and Bayesian reasoning.
2Create hierarchical models using Bayesian concepts and use appropriate software to implement those models.
3Demonstrate the differences between Bayesian modeling and null hypothesis significance testing.
4Apply Bayesian models to solve specific aviation problems using realistic data.
Restrictions
made by Purdue students.