140.773.01 FOUNDATIONS OF STATISTICAL INFERENCE
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.
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
- Monday 8:30 - 9:50
- Wednesday 8:30 - 9:50