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Department: Biostatistics
Term: 2nd term
Credits: 4 credits
Contact: Charles Rohde
Academic Year: 2013 - 2014
Course Instructor:

Investigates the foundations of statistics as applied to assessing the evidence provided by an observed set of data. Topics include: law of likelihood, the likelihood principle, evidence and the likelihood paradigm for statistical inference; failure of the Neyman-Pearson and Fisherian theories to evaluate evidence; marginal, conditional, profile and other likelihoods; and applications to common problems of inference.

Learning Objective(s):
Upon successfully completing this course, students will be able to:
compare and criticize the basic paradigms of statistical inference
formulate and contrast concepts of statistical evidence

Methods of Assessment: Student evaluation based on problem sets and class presentation of solutions to the problem sets.
Location: East Baltimore
Class Times:
  • Monday 8:30 - 9:50
  • Wednesday 8:30 - 9:50
Enrollment Minimum: 10
Instructor Consent: No consent required


Auditors Allowed: Yes, with instructor consent
Grading Restriction: Letter Grade or Pass/Fail
Frequency Schedule: Every Other Year
Next Offered: 2016-2017