BTRY 5020

BTRY 5020

Course information provided by the 2022-2023 Catalog.

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.


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, STSCI 3200, ILRST 2110, STSCI 2110.

Outcomes

  • 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.

When Offered Spring.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one laboratory. Combined with: BTRY 3020STSCI 3200STSCI 5201

  • 4 Credits Stdnt Opt

  •  2569 BTRY 5020   LEC 001

    • TR Warren Hall 175
    • Jan 23 - May 9, 2023
    • Entner, J

  • Instruction Mode: In Person

    Prerequisite: BTRY 3010 or 6010.

  •  2570 BTRY 5020   LAB 401

  • Instruction Mode: In Person

  •  2571 BTRY 5020   LAB 402

  • Instruction Mode: In Person

  •  2572 BTRY 5020   LAB 403

  • Instruction Mode: In Person

  •  2573 BTRY 5020   LAB 404

  • Instruction Mode: In Person