Full course description
Level: Intermediate
Intermediate courses focus on applying a new analytic tool or framework within the topic area.
Track: Non-Analyst and Analyst
Courses targeted to analysts focus on learning new approaches for managing and analyzing data in statistical software. Courses targeted to non-analysts are more conceptual in nature and do not involve in-depth programming.
Audience: This course is designed for public health professionals, program managers, researchers, and decision-makers involved in planning and evaluating health interventions. Knowledge of basic probability is preferred, as well as previous experience with R.
Overview: This course provides a comprehensive introduction to cost-effectiveness and decision analysis methods used to evaluate public health programs and interventions. Participants will learn how to construct decision trees, estimate quality-adjusted life years (QALYs), conduct cost-benefit analyses, and perform Markov modeling to support evidence-based decision-making. The course emphasizes practical applications, guiding participants through real-world public health scenarios. Hands-on exercises and interactive examples ensure participants gain the skills and confidence to apply these methods in their projects. Participants will also receive the R code needed to implement these analyses effectively.
Time Commitment: The estimated time commitment is 7-8 hours. Participants who complete the course will receive a certificate of completion from UC Berkeley.
Certificate: Upon completion of all videos and an online assessment, participants will be awarded a certificate.
The course is open for enrollment but participants will have access to course materials on March 28.