- Schedule of Classes - November 18, 2018 7:14PM EST
- Course Catalog - November 18, 2018 7:15PM EST
Course information provided by the Courses of Study 2018-2019.
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.
Distribution Category (MQR-AS)
- 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.
Choose one lecture and one laboratory. Combined with: BTRY 3020
Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
Or send this URL: