Statistics and Study Design in Ecology and Conservation
- Fundamentals of study design
- Data import and manipulation
- ANOVA and post-hoc testing
- Non-parametric alternatives
- Bootstrap and permutation testing
- Introduction to mixed effects modeling, emphasizing categorical predictors and models for non-independent samples
- Simple linear regression & ANCOVA
- Publication-quality figure creation
- Dates
January 20 – May 11, 2026 | Mason’s Academic Calendar
- Available Formats
Undergraduate (CONS 460, 3 credits)
Graduate (CONS 560, 3 credits)Professional Training (SMSC 0537, 4.5 CEUs)
- Cost
Undergraduate and graduate, see Tuition and Fees.
Professional training: $600.00
- Who is eligible?
Undergraduate or graduate students who have completed an introductory statistics course (BIOL 214, SOCI 313, STATS 250, CONS 404, or equivalent), including both degree-seeking and non-degree seeking students from any accredited college or university who have completed similar coursework.
Professional students are also eligible.
Meet the Faculty
Curriculum
An understanding of statistics and study design is essential to success in the fields of ecology and conservation. However, many of the analyses of greatest utility for ecological data are not addressed in introductory courses, while advanced courses often delve deeply into a limited set of techniques. This course helps to bridge this gap: by covering both traditional core statistical techniques as well as newer advancements such as mixed effects models, all focusing on common data types in these disciplines.
This course addresses the fundamentals of study design, linking choices made when establishing a research project to the types of analyses appropriate to the chosen design, including those common to ecological studies such as repeated measures and blocked designs. Additionally, students will develop skills in data manipulation and analyses using the R statistical computing environment, a popular and powerful tool commonly used in both ecology and conservation.
This is an asynchronous online course comprised of five three-week modules. Each module includes a set of instructional videos and associated exercises, as well as a problem set. An optional, virtual weekly meeting, provides an opportunity to discuss and collaborate on the current assignment.
