ENVS 812: Statistical Methods in Environment and Sustainability
Instructor: Yanping Li
yanping.li@usask.ca; 306-966-2793, NHRC 1013
Winter Semester 2014, MWF 9:00-11:50am, March 2-30, 2014
Course Description
This course is designed for graduate students to improve their knowledge and
understanding of the application of statistical methods. The course begins with
introductory concepts and moves through to more intermediate problems.
Applications to environmental science problems will be emphasized. Contents will
include classical statistical concepts, exploratory data analysis techniques, continuous
and discrete distributions, hypothesis testing, correlation and regression analysis,
analysis of variance, nonparametric statistics, trend testing, and introduction to
generalized linear models and extreme value theory. The primary objective of the
course is for students to learn a variety of techniques that are applicable across a
range of problems, irrespective of a specific discipline, involving small and large
datasets. At the end of the course, students should be able to apply these techniques
to their own research projects.
Learning Outcomes
- Know the importance of statistical data analysis and be able to apply common
approaches to environmental problems.
- Demonstrate understanding and ability to apply the sequential process of model
building, starting from summary statistics to more advanced techniques.
- Develop abilities to understand and synthesize desired information from data
analyses within published research.
Course Schedule
1: Basic statistics
2: Probability and random variables
3: Continuous and discrete distributions
4: Estimation problems and hypothesis testing
5: Correlation and regression analysis
6: Analysis of variance (one-factor experiments, two or more factors)
7: Nonparametric statistic
8: Introduction to generalized linear models
9: Extreme value theory
10: Multivariate analysis