Statistics Program

Course Description

Large Sample Theory

  • Course number : 221 M0250
  • Credits : 3 units
  • Required or Requisite : Requisite
  • Time :
  • Prerequisites : Advanced Statistical Inference
  • Course Description :
    1. Central Limit Theorems and the Bootstrap Method.
    2. Sample quantiles and Extreme Order Stadsdcs.
    3. Modes of Convergence and Their Relations.
    4. Laws of Large Numbers and Central Limit Theorem.
    5. Properties of Maximum Likelihood Estimate.
    6. The Cramer-Rao Lower Bound and Efficiency.
    7. Large Sample Tests: LRT, Wald's and Rao's Tests.
    8. Contingency Tables and Pearson Chi-Square Tests.
    9. Wilcoxon Rank-Sum Test.
    10. Asymptotic Distribution of Posterior Distribution.
  • Textbook :
    Chen,Hung. (2003) You can download lectures from http://www.math.ntu.edu.tw/~hchen/.
  • Reference :
  1. Bickel, P.J. and Doksum, K.J. (2001) Mathematical Statistics: Basic Ideas and Selected Topics Volume 1. Prentice Hall.
  2. Ferguson, T.S. (1996) A Course in Large Sample Theory. Chapman & Hall.
  3. Lehmann, E.L. and G. Casella (1998) Theory of Point Estimation, 2nd ed. New York: springer, 1998.

Last updated: August 6, 2003

Address: Department of Mathematics, National Taiwan University, Taipei, Taiwan
Back