140.763.01 | AY 2013-2014 - 4th Term | 3 Credit(s)
TTh 1:30:00 PM
  • Contact Information
  • Course Learning Objectives

    Upon successfully completing this course, students will be able to:

    • develop Bayesian models for the analysis of complex problems, including repeated measurement data and latent data models;
    • create computer programs to run analyses;
    • calculate posterior distributions of parameters of scientific interest;
    • conduct Bayesian analyses of complex data sets.
  • Course Description

    Builds upon the foundation laid in Bayesian Methods I (140.762). Discusses further current approaches to Bayesian modeling and computation in statistics. Describes and develops models of increasing complexity, including linear regression, generalized linear mixed effects, and hierarchical models. Acquaints students to advanced tools for fitting Bayesian models, including non-conjugate prior models. Includes examples of real statistical analyses.

  • Intended Audience

    Biostatistics degree candidates

  • Methods of Assessment

    Grading Policy: Student evaluation based on homework and a final project.

    Grading Restrictions: Letter grade

  • Prerequisites


  • Academic Ethics Code

    The code, discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class:

    Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.

  • Disability Support Services

    If you are a student with a documented disability who requires an academic accommodation, please contact Betty H. Addison in the Office of Student Life Services:, 410-955-3034, or 2017 E. Monument Street.