This week we'll focus on the theoretical background in probability and statistics necessary for the rest of this course. The in class lesson will go very quickly, but we provide a lot of resources below if you need a refresher.

Background Materials:  We won't be going over these lecture slides. If you need a reminder on the basics of statistics and samples, how to describe your data, and some basic classical tests, these lecture slides and accompanying R exercises should get you up to speed. I've also included a "Probability Cheat Sheet" to jumpstart your thinking for this course. 

Probability and Statistics Refresher (lecture)

Probability and Statistics Refresher (R code) 

Probability Cheat Sheet

Course Materials: Coming Soon

Resources:

• Khan Academy has some excellent probability and statistics videos if you want to brush up on a certain topic https://www.khanacademy.org/math/probability.
• Schluter and Whitlock's Analysis of Biological Data serves as an excellent primer of probability and statistics.
• Dr. Martha Smith's website Common Mistakes in Statistics http://www.ma.utexas.edu/users/mks/statmistakes/StatisticsMistakes.html
• Motulsky's Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking is great for wrapping your head around statistical thinking
• Zar's Biostatistical Analysis and Sokal and Rohlf's Biometry are both good, but rather dry, references. 
• Coursera has two online courses: Mathematical Biostatistics Bootcamp I https://www.coursera.org/course/biostats and Mathematical Biostatistics Bootcamp II  https://www.coursera.org/course/biostats2