Course Overview

This course offers a basic introduction to Monte Carlo methods and Bayesian modeling & computational techniques to prepare undergraduate students (statistics and data science majors and minors) and graduate students in fields other than statistics to apply Bayesian methods in practice. The course is application-oriented and addresses practical skills for principled data analysis.

Grades are based on weekly quizzes on Canvas, biweekly homework, one midterm exam, and one final project (groups of 2-4). For the final project, students are expected to apply Bayesian methods to analyze real data and write up a thorough report on the modeling, computation, and interpretation of the statistical analysis.

Prerequisites: (STATS 412 or STATS 425) and (STATS 306 or EECS 280).

Textbook: Kruschke, John. Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Academic Press, 2014.

Office Hours and Contact Information

Instructor: Yang Chen

GSI: Daniel Iong

Course Outline

Course Policy

Academic Misconduct

The University of Michigan community functions best when its members treat one another with honesty, fairness, respect, and trust. The College of LSA promotes the assumption of personal responsibility and integrity, and prohibits all forms of academic dishonesty and misconduct. All cases of academic misconduct will be referred to the Office of the Assistant Dean for Undergraduate Education. Being found responsible for academic misconduct will usually result in a grade sanction, in addition to any sanction from the College. For more information, including examples of behaviors that are considered academic misconduct and potential sanctions, please see

Accommodations for Students with Disabilities

If you think you need an accommodation for a disability, please let me know at your earliest con- venience. Some aspects of this course, the assignments, the in-class activities, and the way the course is usually taught may be modified to facilitate your participation and progress. As soon as you make me aware of your needs, we can work with the Services for Students with Disabili- ties (SSD) office to help us determine appropriate academic accommodations. SSD (734-763-3000; typically recommends accommodations through a Verified Individualized Services and Accommodations (VISA) form. Any information you provide is private and confiden- tial and will be treated as such.

Other resources

As a student, you may experience a range of issues that can negatively impact your learning, such as anxiety, depression, interpersonal or sexual violence, difficulty eating or sleeping, loss/grief, and/or alcohol/drug problems. These mental health concerns or stressful events may lead to diminished academic performance and affect your ability to participate in day-to-day activities. In order to support you during such challenging times, the University of Michigan provides a number of confidential resources to all enrolled students, including Counseling and Psychological Services (CAPS) (734.764.8312), Sexual Assault Prevention and Awareness Center (SAPAC) (24-Hour Crisis Line: 734.936.3333), Psychiatric Emergency Services (734-996-4747), and Services for Students with Disabilities (734.763.3000; 734.615.4461 [TDD]; 734.619.6661 [VP]).