INTRODUCTION TO PROBABILITY AND MATHEMATICAL STATISTICS II

Prerequisites & course information

Requisites: ( STAT/MATH 309 , STAT 311 , STAT/MATH 431 , or MATH 531 ) and ( STAT 240 , STAT 301 , STAT 302, STAT 324 , STAT 371 , or ECON 310 ), or graduate/professional standing Course Designation: Core GenEd - Natural Science & Wellness Breadth - Natural Science Level - Advanced L&S Credit - L&S Liberal Arts and Science Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Construct point estimators including maximum likelihood estimators, understand the theoretical properties of point estimation methods, and evaluate their performance Audience: Undergraduate 2. Construct hypothesis tests including likelihood ratio tests, interpret their results, evaluate their performance, and understand the theoretical properties of hypothesis testing methods Audience: Undergraduate 3. Construct interval estimators to quantify uncertainty, understand the theoretical properties of interval estimation methods, and interpret their results Audience: Undergraduate 4. Mathematically derive key quantities required for statistical inference methods and be familiar with simulation-based techniques for obtaining those quantities Audience: Undergraduate 5. Describe the Bayesian approach to inference and contrast it with the frequentist approach Audience: Undergraduate 6. Identify and describe the assumptions underlying methods of statistical inference and explain their importance Audience: Undergraduate Learning Outcomes: 1. Construct point estimators including maximum likelihood estimators, understand the theoretical properties of point estimation methods, and evaluate their performance Audience: Undergraduate 2. Construct hypothesis tests including likelihood ratio tests, interpret their results, evaluate their performance, and understand the theoretical properties of hypothesis testing methods Audience: Undergraduate 3. Construct interval estimators to quantify uncertainty, understand the theoretical properties of interval estimation methods, and interpret their results Audience: Undergraduate 4. Mathematically derive key quantities required for statistical inference methods and be familiar with simulation-based techniques for obtaining those quantities Audience: Undergraduate 5. Describe the Bayesian approach to inference and contrast it with the frequentist approach Audience: Undergraduate 6. Identify and describe the assumptions underlying methods of statistical inference and explain their importance Audience: Undergraduate