UCLA Statistics

STAT 251  Winter 2003

Statistical Methods for the Life Sciences


Instructor:
Ivo D. Dinov, Ph.D.
Assistant Professor in Statistics,
Research Scientist, Department of Neurology,
UCLA School of Medicine
E-mail: 		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.

    Lectures:  Life Sciences (LS)  2142,   M W F  9:00 - 9:50 AM

    Discussions Section Information
    Section IDSectionClassroomTimeTA Name
    TBA1No discussion but Stat Computer Lab may be used for projects None

    Instructor Office: Main: MS 8142E (alternative: CHS, UCLA School of Medicine, Reed 4-238, by appt. only)
    TA Offices:  None
    Virtual Office Hours (STAT251 Forum)
     STAT Computer Lab: http://www.stat.ucla.edu/undergraduate/icl/
    Grading policy and basis for Final Grade:
    Project Assignment Policy:

    Textbook: Statistical Research Methods in the Life Sciences, by P.V. Rao, Duxbury Press (1998).
      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.

    Last modified on by .
    Ivo D. Dinov, Ph.D., Departments of Statistics and Neurology, UCLA School of Medicine