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

Syllabus
R commands
Office hours survey


  1. Introduction:

    • Lecture: Why take this course?

    • Lecture: Effective use of AI

    • Worksheet 1: Who are you and why are you here

  2. Basic R:

    • Live Coding: Basic R (syntax, data types)

    • Live Coding: Data management and cleaning 

    • Worksheet 2: Basics of R

  3. Exploratory Data Analysis:

    • Lecture: Descriptive statistics, data visualization

    • Live Coding: Creating plots and summarizing data in R

  4. Probability and Simulation:

    • Lecture: Probability, distributions, and inference

    • Live Coding: Simulating and analyzing distributions in R

    • Worksheet 3: Probability and distributions

  5. Hypothesis Testing:

    • Lecture: Hypothesis testing

    • Live Coding: Performing tests

    • Worksheet 4: Choosing appropriate tests

  6. Test week 1

    • Review

    • Test

  7. Regression Analysis:

    • Lecture: Linear regression and model diagnostics

    • Live Coding: Fitting and diagnosing regression models in R

    • Worksheet 5: Interpreting models and results

  8. Generalized Linear Models and Mixed Models:

    • Lecture: Introduction to GLMs and mixed models

    • Live Coding: Implementing GLMs and mixed models in R

    • Worksheet 6: Developing models in R

  9. Model Selection:

    • Lecture: Model selection

    • Live Coding: Applying model selection techniques in R

  10. Dimensional Reduction:

    • Lecture: PCA

    • Live Coding: PCA

  11. Advanced Topics and Applications:

    • Lecture: Bayesian methods and MCMCs

    • Live Coding: Diagnosing MCMCs

    • Worksheet 7: Are we there yet

  12. Test week 2

    • Review

    • Test

Additional topics will be added as time allows.

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