This space will be used to communicate with students in the Introduction to Biological Statistics Course. Here, you will find copies of lecture materials, exercises and other relevant resources. For more information, contact Nathaniel Pope at npope@coa.edu, spncrfx@gmail.com, or Nichole Bennett at nichole.lynn.bennett@gmail.com.

The goal of this workshop is to provide graduate students early in their studies with a broad set of statistical tools which can be applied to future research problems. The workshop focuses on statistical analysis in R, and we provide basic R instruction for beginners. Past workshops have included broad overviews and workable examples of the following types of analysis: linear models and model fitting, time series analysis, spatial statistics, phylogenetics, population genetics, population dynamics and principal components analysis. This workshop is not meant replace formal course work in statistics. Instead, it provides participants with a foundation of knowledge that can be built upon by future study.

An annotated list of Statistics Resources is available on Google Drive.

This course meets Fridays 1-2:30 pm in GDC 7.514 .

Prerequisite R knowledge assumed for statistics topics lectures:

If you're attending any of the specific statistics topics lectures, we expect that you have a good understanding of the material presented in the first three weeks of class. We also expect that you can do the following in R: access help files for functions, load data, and install R packages. If you need extra practice/instruction in loading data or installing packages, we have the following cheat sheets for you.

Install and Load R Packages

Load Data

Week	Date	Topic	Instructor
1	8/29	Probability and Statistics Refresher	Nichole Bennett
2	9/5	Introduction to R Programming	Nichole Bennett/ Nate Pope
3	9/12	Linear Models	Nate Pope
4	9/19	Generalized Linear Models	Nate Pope
5	9/26	Mixed Models	Nate Pope
6	10/3	Bayesian Statistics	Nate Pope/ Nichole Bennett
7	10/10	Cautions in Using Frequentist Statistics	Martha Smith
8	10/17	Spatial Statistics	Jennifer Miller
9	10/24	qPCR analysis	Rayna Harris
10	10/31	Missing Data	Mike Daniels
11	11/7	D ata Manipulation/Visualization	Sean Maguire
12	11/14	Population Genetics	Antonio Castilla
13	11/21	Network Modeling	Amanda Perofsky
	11/28	NO CLASS (Thanksgiving Holiday)
14	12/5	Multivariate Statistics	Elizabeth Milano

Peer-led Introduction to Biological Statistics by https://utexas.atlassian.net/wiki/display/CCBB/Introduction+to+Biological+Statistics+Course is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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