P8332: Advanced Analytic Methods in Environmental Health Sciences
Course description
This seminar course will introduce advanced methods and tools used in Environmental Health Sciences.
These topics include advanced regression techniques especially pertinent to environmental health, mixtures methods, Bayesian statistics, prediction and forecasting techniques, and attribution science in public health.
Each class will have two components: a lecture and a coding lab.
Although other courses in the School and other Departments might also present some of the methods covered here, the emphasis of this course will be on applications in EHS specifically and the appropriateness, assumptions, strength, limitations and interpretation of results in the EHS framework. R will be used for all coding, with GitHub for code and lecture material co-ordination.
Course learning objectives
By the time you complete this course, you should be able to:
MPH/MS-specific competencies:
Critically evaluate the current literature in environmental health sciences including identifying gaps and uncertainties in the knowledge base and in the methodological approaches to solving environmental health problems
Communicate effectively in writing and orally a knowledge of environmental hazards to other professionals and the public, including effective risk communication
Apply data science methods to solving issues in the environmental health sciences
Identify sources of data and demonstrate the ability to clean and organize data
Synthesis complex environmental health challenges from a public health perspective
Distinguish and appropriately apply data analysis statistical tools
General competencies:
Analyze Environmental Health-relevant data employing advanced analytic approaches
Identify when each method is appropriate to use, given the research question
Apply the advanced methods presented in class using R (please see the course schedule for a list of the methods that will be introduced) and coordinating material with GitHub
Critically evaluate scientific literature by assessing the strengths and limitations of scientific papers
Evaluate whether the conclusions drawn reflect the initial hypothesis and results in published journal articles
Conduct a research project from design to implementation
Compose components of a publishable scientific paper