PHDA 02 - Epidemiological Statistics

"I found Epidemiological Statistics (PHDA02) useful to my work as a research associate at the Centre for Addictions Research of BC. I would recommend this course for anyone who is working in public health and uses epidemiological methods in their employment.

The course covered a wide range of topics from calculating relative risk to meta-analysis. The instructor took the time to ensure all students were able to do the assignments and the course reading provided useful references." 

Gina Martin, Research Associate, Centre for Addictions Research of BC


Next course delivery: May to July 2018

Course description

This is a basic course in epidemiology which also covers a variety of analytic topics not commonly addressed in elementary statistics courses. This course will introduce students to the field of epidemiology. Students will critically evaluate articles in the epidemiologic literature and examine epidemiologic methods including:

  • data collection
  • study design and statistical analysis
  • ratios
  • relative risk
  • contingency tables
  • logistic and Poisson
  • measurement error and exposure misclassification
  • imputation of missing values
  • multilevel regression models in epidemiology

Learning objectives

  • Explain basic concepts in descriptive epidemiology such as incidence, prevalence, mortality, morbidity and effect.
  • Distinguish among common epidemiological designs such as case-control, cohort, cross-sectional and randomized controlled studies.
  • Identify major categories of bias that can affect the validity of epidemiological studies.
  • Apply common measures of association such as relative risk, odds and odds ratios, attributable risk, attributable risk percentage and population attributable risk to epidemiological data.
  • Employ common tools of epidemiological statistics such as logistic and Poisson regression and become oriented to multilevel regression models to analyze appropriate data.


Admission to the Professional Specialization Certificate in Population Health Data Analysis or permission of the Faculty Advisor.

Working knowledge of how to interpret P values, null hypothesis and confidence intervals and some experience with SAS, Excel, linear regression models and natural logarithms including exponentiation using a calculator or the “exp” function in Excel.

A solid grasp of high school math skills, including the ability to use logarithms capably and to work competently with percentages and ratios.


Instructor: Larry Frisch, MD, MPH

Larry Frisch is a clinical associate professor at the University of British Columbia in the School of Population and Public Health and an adjunct Professor of Biomedical Informatics at Nova Southeastern University. A pediatrician and clinical epidemiologist, Larry is assistant director of the Vancouver Coastal Health Research Institute and serves on the board of the BC Environmental and Occupational Health Research Network. His research interests range from nursing language, to childhood injury, to patient safety, including elements of large database analysis, natural language processing, and longitudinal data analysis. Most of Larry's recent teaching is on-line and (in addition to “epidemiological statistics”) has included courses in communicable disease epidemiology, biostatistics, environmental health, global climate change, healthcare economics, and public health informatics. Larry is the co-author of a popular textbook on psychiatric mental health nursing and a chapter editor for the upcoming 2nd edition of Public Health Informatics and Information Systems. When not involved in all of the above he plays upright bass in “Bistro Jazz” and in “The Spiral Swing Orchestra.”


This course is offered in partnership with the Division of Continuing Studies and Department of Geography at the University of Victoria.


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Page last revised: January 4, 2018