Stat 300A – Theory of Statistics

Andrea Montanari, Stanford University, Autumn 2018
Linear regression 

A course on the mathematical foundations of statistics, with focus on general principles and finite sample optimality.

Topics include:

  • Decision theory: loss, risk, admissibility.

  • Bayes estimation; Minimax estimation.

  • Principles of data reduction. Sufficiency. Exponential families.

  • Unbiasedness and equivariance.

  • Hypothesis testing and confidence intervals.

Class Times and Locations

  • Monday and Wednesday, 9:30-11:20AM in Sequoia 200

  • Problem Sessions on Friday, 10:30-11:30AM in Sequoia 200


The midterm will take place on Friday, October 26, 3:30-6:30PM in room 380-380Y.