Prerequisite: BTRY 3010 or BTRY 6010.
Applies linear statistical methods to quantitative problems addressed in biological and environmental research. Methods include linear regression, inference, model assumption evaluation, the likelihood approach, matrix formulation, generalized linear models, single-factor and multifactor analysis of variance (ANOVA), and a brief foray into nonlinear modeling. Carries out applied analysis in a statistical computing environment.
- Outcome 1: Students will be able to design a statistical experiment using randomization techniques.
- Outcome 2: Students will be able to analyze multivariate linear and nonlinear data that include quantitative and qualitative variables.
- Outcome 3: Students will be able to apply generalized linear model, generalized additive models, and mixed effects models to appropriately collected data.
- Outcome 4: Students will be able to formulate and evaluate parametric and nonparametric methods for determining model uncertainty.
- Outcome 5: Students will be able to employ matrix methods to effectively design and implement linear models.
- Outcome 6: Students will be able to assess the quality of a statistical analysis.