Oregon Health Sciences University (OHSU) and Portland State University (PSU) School of Public Health

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Course Directory and Schedules

Course Schedules

Academic Year 2022-2023 Planning Schedule

Course Schedules by Term

Summer
Summer 2022 GR Courses (4/18/2022)

Fall 
Fall 2022 GR Courses
Planning Schedule

Winter
Winter 2023 GR Courses
Planning Schedule
(rev. 7.5.22)

 

Spring
Spring 2023 GR Courses
Planning Schedule
(rev. 7.5.22)

Archived GR
Schedules
by
Term

Interprofessional Education Course Schedule

Interprofessional education occurs when students from two or more professions learn about, from, and with each other to enhance collaboration and improve health outcomes. At least 1 credit of interprofessional education is required by all MPH degree programs.

Most courses with OHSU subject code IPE (Inter-Professional Education) or UNI (University Curriculum) satisfy the interprofessional education requirement. Other courses may also serve; consult your advisor. For a list of IPE and UNI courses, descriptions, and their intended schedule, download this spreadsheet.This list is subject to change — contact the course instructor if you would like to enroll.

SPH Course Descriptions

Descriptions of all School of Public Health courses can also be found in the course catalog of the most recent edition of the PSU Bulletin.

Biostatistics Lab – BSTA 530

Course Code Credit

BSTA 510

3

Course Information

The course provides hands-on data analysis and/or biostatistical consulting experience to students outside classroom settings. Students will have opportunities to perform data analysis with inputs from faculty members. Students should have adequate skills in at least one statistical program among STATA, SAS, or R and has finished BSTA 512 linear Models or equivalent. Students meet weekly for 1 hour with the course instructor for discussion on their projects and are also encouraged to have regular meetings with an assigned faculty advisor and/or
consultee(s). Students are expected to work individually or in a team of 2~3 on actual data analysis. The workload will be at least 9 hours per week including all activities (classes, meetings, readings, coding, and analysis).

Prerequisites:

  • BSTA 511/611 Estimation & Hypothesis Testing for Applied Biostatistics
  • BSTA 512/612 Linear Models