Experimental Design

Learning Objective

This course is intended to provide a foundation in the proper design of scientific research projects in the field of biology.

By the end of the course, successful students will be able to:

Design studies that are statically tractable
Graphically explore data in R
Perform standard statistical analyses in the R environment

Class meets MW 4:00-5:15 in HELD 200
For more information email Dr. Blackmon.

Syllabus
R commands
Office hours survey

Week	Topic	Material
1	Introduction and motivation	pptx pdf
2	Statistical Principles	pptx pdf central limit script
3	Principles of data visualization	Holiday - no class monday pptx pdf
4	Intro to R	weekly script
5	Plotting in R	weekly script
6	Simple hypothesis testing 1	Monday - pptx Monday - pdf binomial and chi-square script Wed - pptx Wed - pdf
	HOMEWORK	Homework 2 Homework 3
7	Simple hypothesis testing 2	Midterm Review wed script
8	Wednesday test review	Midterm complete by Sunday midnight 24 hours to complete once started vac.rates.csv mite.count.csv phone-microbes.csv
9-10	ANOVA and linear models	Monday - pptx Monday - pdf betta.csv
11	Linear models and random effects	Monday - pptx Monday - pdf example script logistic.csv oaks.csv GWAS.R
12	Bayesian methods and MCMC	Monday - pptx Monday - pdf mcmc1.csv mcmc2.csv
13	Monte Carlo methods	Monday - pptx Monday - pdf worksheet 1 retrogene.csv monte carlo and mcmc scrip†
14	Model Selection	worksheet 2 smokers.csv betta2.csv
15	RMD files	Holiday - no class Wednesday
16	R Practice Session / Review	mcmc1.csv mcmc2.csv grasshopper.csv retrogene.csv review sheet
Finals	Final Released Monday 4th Dec. 9AM Mon. work on final in class Due Sunday 10th Dec. 11:59 PM	Files for the final: test.mcmc.csv astyanax.csv chrysina.csv

Extra Resources

Examples
R markdown
R style guide
basics of R cheat sheet
base R plotting cheat sheet
ggplot2 cheat sheet
color brewer

Useful R packages

swirl
ggplot2
coda