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140.771.01 Advanced Statistical Theory I

1st term
4 credits
Academic Year:
2013 - 2014
East Baltimore
Class Times:
  • Tu Th,  1:30 - 2:50pm
Grading Restriction:
Letter Grade or Pass/Fail
Daniel Scharfstein
Course Instructor:

140.673-674, 140.692-694, and knowledge of laws of large numbers and central limit theorem


Examines statistics as a discipline along the path towards making decisions. First examines the justification of statistics from axioms on informed preferences and its close connection to Bayesian theory, and then examines the role of standardizing intermediate steps, through various additional restrictions on estimation, and studies the properties of the resulting methods.

Learning Objectives:

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

  1. be introduced to the role of statistics as a path towards inference and making decisions
  2. Discuss basic decision theory, including the properties of Bayes rules and other ordering of decision strategies
  3. justify decision theory on simple axioms, and examine reasons for studying restricted estimation strategies
  4. examine properties of unbiased estimation and functions
Methods of Assessment:

Student evaluation based on one mid-term exam and one project per term.

Instructor Consent:

No consent required

Special Comments:

Grade for 140.771 and 772 given at completion of 140.772.