The objectives for this course are for participants to:

• Describe the roles of descriptive versus inferential statistics;
• Identify characteristics of the research question to help choose the appropriate analytic technique;
• Describe techniques appropriate for handling a single outcome variable and multiple predictor variables; and
• Detect data limitations and their consequences.

Designing Clinical Research (EPI 202), and Biostatistical Methods I (BIOSTAT 200). If BIOSTAT 200 has not been taken, evidence of knowledge of the use of Stata is required. Exceptions to these prerequisites may be made with the consent of the Course Director, space permitting.

1. Lectures: Tuesdays: 10:30 AM to 12:00 PM, Jan. 6 to Mar. 17. Lecture recordings will be available online later in the day.
2. Labs: Thursdays: 10:30 AM to 12:30 PM, Jan. 8 to Mar. 19
3. Problem Review Sessions: Tuesdays, 12:00 PM to 12:50 PM, Jan. 27, Feb. 10, Feb. 24, Mar. 10.

The daily schedule of activities will be posted on the course's online syllabus.

Regression Methods in Biostatistics by E. Vittinghoff, D. Glidden, S. Shiboski, and C. McCulloch. Springer, 2012.

Stata
The statistical software package Stata (Stata Corporation, College Station, TX) is used throughout the TICR Program and is required for this course; version 16 or higher is acceptable. A six-month student license for Stata/BE is the least expensive option that will be suitable to complete all course assignments. For students intending to enroll in courses over 1-2 years, an annual or perpetual license are better long-term options. If your research requires working with more variables, you also may wish to consider Stata/SE. We recommend that you have a personal copy of Stata and bring it on a laptop for all course sessions. Stata may be purchased at a discount for UCSF faculty/staff and official UCSF Students. You must use your ucsf.edu email address to receive the discount. If you do not purchase your own copy of Stata, UCSF faculty/staff/students may request access to Stata through the UCSF Research Analysis Environment.

R

The statistical computing language R is offered as a parallel option for completing computer labs and assignments in this course, though primary instruction and examples will be conducted in STATA.

Books may be purchase either through the publisher or a variety of commercial venues (e.g., Amazon.com).

Grades will be based on five homework assignments (70%) and a final exam (30%). Late work is not accepted.

Students not in full-year TICR Programs who satisfactorily pass all course requirements will, upon request, receive a Certificate of Course Completion.

Only UCSF students (defined as individuals enrolled in UCSF degree or certificate programs) will receive academic credit for courses. Official transcripts are available to UCSF students only. A Certificate of Course Completion will be available upon request to individuals who are not UCSF students and satisfactorily pass all course requirements.

UCSF Graduate Division Policy on Disabilities

AHealth Data Science/Clinical Research (ATCR/MS) and PhD students use the Student Portal to add the course to their study list. 

Students taking individual courses:

Winter 2026 Course Fees
Winter 2026 Schedule

Apply By January 2nd