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 TR 8:00-9:15 in HELD 105
For more information email Dr. Blackmon.

Syllabus
R commands

Week	Topic	Material
1	Introduction and motivation	pptx pdf
2	Statistical Principles	pptx pdf RMD file my tuesday fail
3	Principles of data visualization	pptx pdf basics of R Yahtzee in R
4	Intro to R	distributions homework 1 completed basics of R cheat sheet
5	Plotting in R	plotting examples betta fish data homework 2 completed code two categorical variables ppt two categorical variables pdf R categorical examples
5.5	Saturday Fun	gnatocerus file offspring file
6	Simple hypothesis testing	hypothesis testing ppt hypthesis testing pdf
7	Review and midterm	review pdf review doc review script phone-microbes.csv crickets.csv
8	Holiday / test review	extra credit
9-10	ANOVA and linear models	ppt pdf ANOVA video Passcode: s1@uvg2= Linear Models video Passcode: y3.!$eq! model fit r code
11	Linear models and random effects	ppt pdf r code homework file aggression.csv ppt pdf chrysina.csv
12	Bayesian methods and MCMC	ppt pdf homework file mcmclogfile.csv class examples: complex.log.file.csv complex.lm.csv
13	Monte Carlo methods	ppt pdf retrogene.csv retrogene2.csv
14	Holiday	retrogene3.csv
15	PCA	ppt pdf retro.gene.homework.R PCA.rmd PCA.html
16	Review and Final	review MCMC1.csv MCMC2.csv grasshopper Files for final: final.fish.csv final.mcmc.csv final.montecarlo.csv

Extra Resources

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