UCLA STAT 251 (section 1) Winter 2002

Statistical Methods for the Life Sciences


UCLA Department of Statistics
STAT 251 - Statistical Methods

Ivo D. Dinov, Ph.D.
Assistant Professor in Statistics,
Research Scientist, Department of Neurology,
UCLA School of Medicine
Teaching Assistants:
  • None (for now) E-mail: none@stat.ucla.edu

  • Brief Description:

    This will be a modern graduate course in statistics for life science and biomedical students. We will present the most popular statistical tools for data analysis and support those with an elaborate framework of simulations, applets, compute-engines, movies and real-time Internet tools. A number of course projects (papers) will help the students gain a hands-on experience on design of scientific experiments, data acquisition, processing, integration, statistical analysis and presentation.
    Textbook: Statistical Research Methods in the Life Sciences, by P.V. Rao, Duxbury Press.
      Tentative order of topics covered
    1. Variables, measurements, statistics and parameters.
    2. Normal, Binomial and Poisson distributions.
    3. Basic statistics, 5-number summaries.
    4. Central Limit Theorem.
    5. Confidence Intervals.
    6. Inferences About One Or Two Populations.
    7. Design of studies and experiments.
    8. Analysis Of Variance (ANOVA).
    9. Regression and Correlation.
    10. Principle component analysis (if time permits!).
    11. Hypothesis Testing.

    Ivo D. Dinov, Ph.D., Departments of Statistics & Neurology, UCLA