Spring 2005
Statistics 415
Advanced Statistical Methods for Research Workers

Time: Class: MF 2:10 - 3 (MOL BIO 1428) Lab: W 2:10 - 4 (McKay 119 or Snedecor 321)
Credit-hours: 3 (Non-major graduate credit)
Prerequisite: Statistics 401 of 328

This course will present advanced modern methods for analyzing experimental and observational data. The course will focus on data analysis, modeling, and interpretation, using examples from a variety of scientific and engineering disciplines. Topics to be covered include:

  • Principles of maximum likelihood estimation and the analysis of censored time-to-event data (Professor Meeker)
  • Logistic and Poisson regression analysis (Professor Stephenson)
  • Resampling and other simulation-based inference methods (Professor Duckworth)
  • Principles of graphical methods for high-dimensional data (Professor Cook)
  • Linear mixed effect models: incorporating multiple sources of variation into an analysis (Professor Dixon)
  • Modeling biological and physical mechanisms with random-parameter models (Professor Kaiser)
  • Model free curve fitting (Professor Koehler)

    Fri Dec 3 17:08:46 CST 2004