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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. A wide range of biological experiments will be covered, and each type of experiment will be explored with an eye toward choosing the appropriate statistical technique for analysis. By the end of the course, successful students will be able to design biological studies that are statistically tractable and perform basic statistical analyses using the programming language R.

Class meets in BSBW room B25 TR 2:20-3:35.
For more information email Dr. Blackmon.


Lecture Topics

Week Topic Reading
1 Introduction to R and statistics WS CH. 1-2
beyond the bar
p-value crisis
2 Using R horned-beetle-data
3 Summaries and estimates WS CH. 3-4
4 Probability and Bayes' theorem WS CH. 5
McElreath chap 2
5 Proportions and categories WS CH. 6-9
6 Continuously distributed variables WS CH. 10-13
cricket data
7 Experimental Design, ANOVA, Correlation WS CH. 14-16
8 Exam 1
Spring Break
9 Regression and GLM WS CH. 17-18
10 Mixed models
11 perils of stepwise modelling whittingham-2006
12 Dimensional reduction
13 Journal reading and plot discussions Bickel-1975
plot examples
14 Final Exam Rmd rubric

Lab Activities and Homeworks

homework 1
homework 2
Lab week 3 & homework 3
HW3 - examples from class
Lab week 4 & homework 4
Example of plots
Lab week 5 & homework 5
Lab week 6 & homework 6
Lab week 7 & homework 7
Lab week 8 AZ.csv
Lab week 9 hiC.data.csv
PCA example

Extra Resources

Google R style guide
R cheat sheet