Course content (BIOL 217)


Please use the links below to access the content for each topic (week). Please review the rubric for submitting programming assignments through Blackboard each week prior to submission.

The lecture tutorials provided below are linked directly to the online version of The Worst Stats Text eveR, the text book used for the class. The links below will not open in a new tab unless you tell them to. PDF and eBook formats are coming soon!

Introduction to programming in R


Lecture tutorials

Chapter 1: Introduction to programming in R
Chapter 2: Data Structures

Homework exercises

Introduction to R

Data manipulation and visualization


Lecture tutorials

Chapter 3: Working with data
Chapter 4: Plotting and graphics

Homework exercises

Data manipulation and visualization

Probability and sampling distributions


Lecture tutorials

Chapter 5: Sampling distributions

Homework exercises

Sampling distributions

Introduction to inferential statistics


Lecture tutorials

Chapter 6: Intro to inferential

Homework exercises

Hypothesis testing

Linear models


Lecture tutorials

Chapter 7: Linear models
Chapter 8: General linear models

Homework exercises

Linear models

Diagnostics and effect sizes


Lecture tutorials

Chapter 9: Assumptions of linear models
Chapter 10: Communicating effects

Homework exercises

Diagnostics and effects

Model selection


Lecture tutorials

Chapter 11: Model selection

Homework exercises

Model selection

GLM: Logistic regression


Lecture tutorials

Chapter 12: Logistic regression

Homework exercises

Logistic regression

GLM: Count models


Lecture tutorials

Chapter 13: Count models

Homework exercises

Count models

Generalized linear mixed models


Lecture tutorials

Chapter 14: Linear mixed models
Chapter 15: Generalized linear mixed models

Homework exercises

Generalized linear mixed models




This work is licensed under a Creative Commons Attribution 4.0 International License. Data are provided for educational purposes only unless otherwise noted.