This course provides graduate students with foundation of statistical inference. For more details, please also check the course outline on Blackboard.

• Instructor: Prof. Tony Sit.

• Topics:

  • Random Variables, Their Transformations and Expectations

  • Common Families of Distributions

  • Properties of Random sample

  • Principles of Data Reduction

  • Asymptotics/Large-sample Theory

  • Point Estimation

  • Hypothesis Testing and Interval Estimation

Tutorial Materials

• Tutorial 1.

• Tutorial 2.

• Tutorial 3.

• Tutorial 4.

• Others

Reference and Textbooks

• Lectures:

  • Casella, G. & Berger, R. L. (2002) Statistical inference. Australia ;: Thomson Learning.

  • Keener, R. W. (2010) Theoretical Statistics : Topics for a Core Course. New York, NY: Springer New York.

  • Lehmann, E. L. & Casella, G. (1998) Theory of Point Estimation. Second Edition. New York, NY: Springer New York.

  • Lehmann, E. L. . et al. (2005) Testing Statistical Hypotheses. Third Edition. New York, NY: Springer Science+Business Media, Inc.

  • Others

• Tutorials:

  • Shao, J. (2003) Mathematical Statistics. New York, NY: Springer New York.

  • Shao, J. (2005) Mathematical Statistics: Exercises and Solutions. 1. Aufl. [Online]. Springer Science + Business Media..