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:
  1. Design studies that are statically tractable
  2. Graphically explore data in R
  3. 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