Study of Variability

"General linear models with one or more explanatory random variables: translating the figure that answers the biological question into a statistical model—that is, taking into account numerous effects and knowing how to interpret them"

general properties examined through regression and one-way ANOVA (R², F, ddl, least squares, likelihood, diagnostics, validation, goodness of fit, interpretation of effect sizes); ANOVA with nested and crossed factors, multiple regression (concepts of parameters, effects, and interactions)

"accounting for the dependence of explanatory random variables, confounding effects (quantitative for multiple regression, and unbalanced designs for ANOVA)"

Construction of linear models with one or more explanatory variables that are appropriate for the structure of biological data derived from an experimental protocol or collected from natural populations (including data with dependency, multicollinearity, and spatial or temporal structure).

Mastered hypothesis testing; see DESINF course unit (or equivalent)

Comprehensive ongoing assessment: 100%