STSCI 5201

Statistics II

Course Description

Course information provided by the Courses of Study 2024-2025.

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.

When Offered Spring.

Prerequisites/Corequisites Prerequisite: BTRY 3010 or equivalent.
Forbidden Overlaps Forbidden Overlap: due to an overlap in content, students will receive credit for only one course in the following group: BTRY 3020, ILRST 2110, STSCI 2110, STSCI 3200.

Comments Basic knowledge of R programming.

• Students will be able to design a statistical experiment using randomization techniques.
• Students will be able to analyze multivariate linear and nonlinear data that include quantitative and qualitative variables.
• Students will be able to apply generalized linear model, generalized additive models, and mixed effects models to appropriately collected data.
• Students will be able to formulate and evaluate parametric and nonparametric methods for determining model uncertainty.
• Students will be able to employ matrix methods to effectively design and implement linear models.
• Students will be able to assess the quality of a statistical analysis.

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