In this class we will survey a broad range of data analysis methods, with a focus on likelihood-based inference for solving non-standard problems. We will develop skills in building custom model specifications and will build an intuition for when to use custom methods and when standard tools and methods are appropriate.
Much of the benefit of this course will come from interactions with peers and the instructor during class and lab periods and I expect you to do your best to attend and participate wherever possible! That said, if you need to miss class or lab for important reasons (like field work), notify your instructor in advance and work with classmates to get their notes!
Please order the course textbook (Ecological Modeling and Data in R, by Ben Bolker) as soon as possible. You can purchase the textbook on Amazon. All other readings will be posted on WebCampus.
All of you should have R and RStudio installed on your computers. See the links page for some useful references. We will not spend much time learning R in this class, but you are expected to be able to use it to load and visualize data, run analysis, and do basic programming operations.
The UNR Research Data Services program hosts informal weekly sessions for grad students and faculty to discuss data analysis questions. This can be a good opportunity to ask questions, find out more about what types of data and questions your peers are working with, and contribute some insights!
Please take the time to introduce yourself in more detail on WebCampus – I posted a question on the discussion board.
Remember, I need your frequent and honest feedback in order to make sure that the level is appropriate and the topics are useful!