Week 4: Linear Models Part 1 (Nate Pope)

Nate Pope will be our guest lecturer for Week 4 and introduce the first part of linear models. This class will cover the math behind linear models and likelihood and how to fit linear models in the R programming language. We will continue with linear models in Week 5.

If you want to follow along with the script for the class, please install the packages 'car' and 'bbmle.' Both of these are in CRAN. If you are unfamiliar with how to install packages, check the home wiki page of this course for instructions.

What you need to know before this class. If you are unfamiliar with these, check with our past lessons and stats resources.

What a probability distribution is.
A general sense of what ANOVA and regression are.
Familiarity with terms like 'predictor variable,' 'covariate', 'response variable', etc.
A general idea of how lease squares works. (Khan academy has a nice demonstration of this https://www.khanacademy.org/math/probability/regression)
What objects and functions are within the R environment.

Class Materials:

Lecture Slides: Linear_Models_Pope.pdf

Example Data: Bombus_pesticide.csv

Example Script: example_script_Sep20.R