Description
Introduction to the philosophy of Bayesian inference; practical experience applying to biological data. Model formulation, identification of appropriate priors and resulting posteriors given priors and data, and the practice of drawing inferences from these posteriors.
Prerequisites
- Prerequisite(s): An advanced course in applied biostatistics (e.g. BIOL 5407 ) or permission of the Department and good standing in a Carleton University Biology or Biochemistry Graduate Program.
Conditions and arrangements
- Prerequisite(s): An advanced course in applied biostatistics (e.g. BIOL 5407 ) or permission of the Department and good standing in a Carleton University Biology or Biochemistry Graduate Program.
Reference text in its original language
Introduction to the philosophy of Bayesian inference; practical experience applying to biological data. Model formulation, identification of appropriate priors and resulting posteriors given priors and data, and the practice of drawing inferences from these posteriors.
- Prerequisite(s): An advanced course in applied biostatistics (e.g. BIOL 5407 ) or permission of the Department and good standing in a Carleton University Biology or Biochemistry Graduate Program.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/grad/courses/BIOL/