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18.655

Mathematical Statistics

3-0-9 units · Graduate

Decision theory, estimation, confidence intervals, hypothesis testing. Introduces large sample theory. Asymptotic efficiency of estimates. Exponential families. Sequential analysis. Prior exposure to both probability and statistics at the university level is assumed.

Spring 2016

Topics

  • Course Overview
  • Statistical Models
  • Bayesian Models
  • Decision Theoretic Framework
  • Prediction
  • Sufficiency
  • Exponential Families I
  • Exponential Families II
  • Methods of Estimation I
  • Methods of Estimation II
  • Bayes Procedures
  • Minimax Procedures
  • Unbiased Estimation and Risk Inequalities
  • Convergence of Random Variables Probability Inequalities
  • Limit Theorems
  • Asymptotics I: Consistency and Delta Method
  • Asymptotics II: Limiting Distributions
  • Asymptotics III: Bayes Inference and Large-Sample Tests
  • Gaussian Linear Models
  • Generalized Linear Models
  • Case Study: Applying Generalized Linear Models

Readings

Prerequisites & course information

Prereq: ( 18.650[J] and ( 18.100A , 18.100A , 18.100P , or 18.100Q )) or permission of instructor G (Spring) 3-0-9 units

Sources