Nicholas Boyce
Contact
Rec Facilities Attndnt, VPFO CCR Programming
- nboyce@ualberta.ca
Courses
REN R 480 - Applied Statistics for Environmental Sciences
Focuses on problem formulation, method selection, and interpretation of statistical analysis. Covers data management and data visualization, statistical tests for parametric, non-parametric and binomial data, linear and non-linear regression approaches. Participants will gain general statistical literacy and learn how to visualize and analyze data with open-source software packages. Prerequisite: 60 units. 3 units in introductory statistics recommended.
REN R 580 - Applied Statistics for Environmental Sciences
Focuses on problem formulation, method selection, and interpretation of statistical analysis. Covers data management and data visualization, statistical tests for parametric, nonparametric and binomial data, linear and non-linear regression approaches. Participants engage in problem-based learning by analyzing data from their thesis research project. Students without a suitable dataset should enroll in two or more 1 unit REN R 58X courses instead. Prerequisite: 3 units in introductory statistics recommended.
REN R 690 - Multivariate Statistics and Machine Learning for the Environmental Sciences
Covers methods for visualization, analysis and prediction for complex biological or environmental data. Includes classical and modern approaches to ordination and classification, analysis of multivariate relationships, and the application of deep neural networks and other machine learning tools for prediction. Participants engage in problem-based learning by analyzing data from their thesis research project. Students without a suitable dataset should enroll in two or more 1 unit REN R 58X courses instead. Prerequisite: 3 units introductory statistics recommended.