BTRY 5020

BTRY 5020

Course information provided by the Courses of Study 2021-2022.

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, STSCI 3200, ILRST 2110, STSCI 2110.

  • 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.

View Enrollment Information

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

  • 4 Credits Stdnt Opt

  • 20382 BTRY 5020   LEC 001

    • TR Warren Hall 175
    • Jan 24 - May 10, 2022
    • Entner, J

  • Instruction Mode: In Person
    Prerequisite: BTRY 3010 or 6010.

  • 20383 BTRY 5020   LAB 401

  • Instruction Mode: In Person

  • 20384 BTRY 5020   LAB 402

  • Instruction Mode: In Person

  • 20385 BTRY 5020   LAB 403

  • Instruction Mode: In Person

  • 20386 BTRY 5020   LAB 404

  • Instruction Mode: In Person