Instructor: Dr. Andrew Bateman
Overview: Did you enjoy second-year statistics? Don’t worry! There exists a world beyond t-tests and z tables. This course will take students beyond the basics to fuse models with data from ecological systems. Students will learn how to formulate models on paper and code them in R, use models to simulate data and make predictions, write a likelihood function, fit models to data to estimate parameters and compare different model structures. Efforts will be made to link course material to local ecological systems and data, with opportunities to get into the field. The latter part of the course will be devoted to student research projects. Students are encouraged to collect data in the field for their projects, but may come with pre-existing datasets or use model simulation to generate data. Students will present their projects in an open symposium at the end of the course.
Research Skills: The abilities to translate ecological questions into quantitative models and connect models with data are key to the modern scientific process.
Practical Skills: In an age of technology, ecology is rapidly becoming a data-rich science. Being comfortable using large datasets to answer ecological questions will set you apart for a job in research, consulting or government. This course also develops skills communicating research, through presentation of data and models in written and oral form.
Boat Use: You will be given the opportunity to drive boats if you choose to do so. Boat driving is recommended but not required for Ecological Models and Data. Students may wish to drive boats so they can collect data by boat. Students who wish to drive boats at BMSC must hold a PCOC and valid first aid certificate and will participate in an introductory boat check-out on the first day of orientation.
Prerequisites: (1) Second year statistics, (2) introductory calculus and (3) introductory ecology, or permission of the instructor. Students lacking any of these pre-requisites should be prepared to do some additional legwork. All students should be willing to learn some math and coding!
Physical Requirements: Students must be comfortable on open boats, walking rugged shorelines in all types of weather and working long hours at a computer.
Textbook (required): Ecological Models and Data in R, Ben Bolker (2008) We recommend buying hard copy, but if you’re tight on cash, older pdfs of individual chapters can be downloaded from http://ms.mcmaster.ca/~bolker/emdbook/Apply Now
Students from Ecological Models & Data 2014 say:
“It was material I have been meaning to tackle for a long time, as well as learning a bit of R, and what better place to slog through hours of coding than in a library overlooking mountains and an inlet.”
“Absolutely needed an R course. This one looked great. Its great to immerse yourself in one topic for 3 straight weeks (learn much more that way). “
“To complete a course requirement in 3 weeks vs. an entire semester – ideal for grad students with busy field schedules. This course was not offered at my home university, so i had been planning to take it at BMSC for the last year of my degree.”
“This course was an absolute lifesaver and was the sole reason I was able to accomplish my research goals in grad school. In only three weeks, I developed an understanding of modeling that was essential to interpret my own data and complete my thesis. It was very hard to fit in a stats course at my home institution due to the nature of time-sensitive field work schedules, this three-week course was a perfect immersion experience to learn it all so quickly and at a convenient time that worked for me. I came away from the course with a deeper knowledge of R and ecological models as well as code that was directly applicable to my own thesis! Andrew was an amazing instructor! I highly recommend this course to all grad students and undergrads; undergrads will gain such an advantage in all of their future courses and especially in grad school!”