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Description

Harrison QuickPhD, MS
Associate Professor
Division of Biostatistics & Health Data Science
School of Public Health, University of Minnesota

Hierarchical Bayesian methods combine information from various sources and are increasingly used in biomedical and public health settings to accommodate complex data and produce readily interpretable output. This course will introduce students to Bayesian methods, emphasizing the basic methodological framework, real-world applications, and practical computing.

This non-credit course meets with the academic course PubH 6431-101 as part of the 2025 Public Health Institute.

Enrollment for this course will open on February 27, 2025.

Additional information can be found on the Public Health Institute website.

 

Objectives

Upon completion of the course, students will be able to

  • Formulate research questions,
  • Develop Bayesian approaches to these questions,
  • Implement models using available software,
  • Interpret statistical output, and
  • Understand advanced Bayesian methods applied in the scientific literature to complex data sets.

Competencies

The core competencies for public health professionals are a consensus set of skills identified by the Council on Linkages (CoL) between academia and public health practice as being desirable for the delivery of the essential public health services. The CoL competencies identified for this course are:

Domain 1: Analytic/Assessment Skills

  • 1.4 Uses methods and instruments for collecting valid and reliable quantitative and qualitative data
  • 1.9 Interprets quantitative and qualitative data
  • 1.10 Makes community-specific inferences from quantitative and qualitative data
  • 1.12 Uses data to address scientific, political, ethical, and social public health issues

Domain 6: Public Health Science Skills

  • 6.4. Applies the basic public health sciences (including, but not limited to biostatistics, epidemiology, environmental health sciences, health services administration, and social and behavioral health sciences) to public health policies and programs
  • 6.9. Contributes to building the scientific base of public health

Registration & Cancellation

The registration fee for this course is $595. You will receive an email letter outlining program logistics two weeks prior to the start of the course.

Requests for refunds will be honored in full if a written cancellation request is received prior to the course start date. An administration fee of $50 will be charged to all refund requests received after the first day of class. The Centers for Public Health Education and Outreach (CPHEO) reserves the right to cancel any course. In the event of a course cancellation, registrants will receive a full refund of the program registration fee. CPHEO is not responsible for refund of travel or other costs incurred by registrants.

The Centers for Public Health Education and Outreach will provide a certificate of attendance verifying 1.5 CEUs (15 contact hours) offered for this program. This course is eligible for 15 CPH recertification credits.

All courses are approved for CPH Recertification Credits by the National Board of Public Health Examiners.

Contact & Questions

phi@umn.edu
 

 

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Enroll Now - Select a section to enroll in
Section Title
Topics in Hierarchical Bayesian Analysis
Type
Lecture
Days
T
Time
9:00AM to 12:00PM
Dates
May 27, 2025
Campus
Twin Cities (US Central Time)
Building
Blegen Hall
Type
Lecture
Days
W, Th, F
Time
8:00AM to 12:00PM
Dates
May 28, 2025 to May 30, 2025
Campus
Twin Cities (US Central Time)
Building
Blegen Hall
Schedule and Location
Contact Hours
15.0
Delivery Options
Lecture  
Course Fee(s)
Full Pay $595.00
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