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 in class. These cheat sheets, lectures, and R exercises (along with our suggested resources) should get you up to speed for this class.

Probability and Statistics Refresher (lecture)

Probability and Statistics Refresher (R code)

Probability Cheat Sheet

Correlation (lecture)

Correlation (R code)

One and Two Sample Tests (lecture)

One and Two Sample Tests (R code)

EnvironmentalConditions.csv (data file)

bodytemp.txt (data file)

drugs.txt (data file)

Distributions (lecture)

Distributions (R code)

Hypothesis Testing (lecture)

Hypothesis Testing (R code)

Which Test Should I Use? Cheat Sheet

Transformations Cheat Sheet

Examples from the Literature

Course Materials:

Week 1 Lecture

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

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