Simple linear regression
Regression is one of the most important statistical frameworks and although it won’t be obvious to your in BIOL322, it has the same foundation as ANOVAs but it consider two continuous variable. Regressions allow biologists to tackle of multitude of questions.
In this first lecture on regressions, we cover a few biological research examples in which regression was key to generate evidence towards interesting and important hypotheses. We also cover the “anatomy” of a regression model in which its main components, mathematical formulation and interpretation of regression coefficients are provided.
In part 2 of this lecture, we will expand on this introduction towards complex usages of regression models for statistical hypothesis testing. Diagnostic tools to assess whether we should trust of not a regression model for prediction, and understanding assumptions underlying regression models.
This version of the lecture was delivered by Brian Gallagher, PhD candidate in Biology at Concordia as part of their pedagogical training. My version of the lecture, (slides and video) which includes all elements that Brian has presented will be made available below by tomorrow.
My original lecture and Video (Brian Gallagher’s lecture overlaps but my version has a video available and some important additional details)
This is a short lecture (37 m) in only one part.