brianstock / statsclass_public

Intro to R for fisheries / marine ecology

Intro to R for fisheries / marine ecology

Course materials generated by Brian Stock, Josh Stewart, and Lynn Waterhouse for the "Ecological Data Analysis" workshop (Yelapa, Mexico, Mar 23 -- Apr 2, 2017)

Many thanks to our funders:

Preparation (before arrival)

1. Download and install R: https://www.r-project.org/

2. Download and install R Studio: https://www.rstudio.com/products/rstudio/download/ (at the bottom under 'Installers for Supported Platforms'). If you have trouble downloading or installing R or R Studio, please email us so we can work through any problems ahead of time.

3. Work through the following tutorial so you have some experience with R before the workshop: http://www.cyclismo.org/tutorial/R/ (only chapters 1 through 7; stop after 'Indexing into Vectors')

4. Work through the following exercises: https://www.datacamp.com/courses/free-introduction-to-r (Chapter 1 & 2 will be some repeats of the cyclismo tutorial, but 3-6 will be new)

5. Run in R:install.packages(c("tidyr", "dplyr", "ggplot2", "lubridate", "stringr", "lme4", "ggmap", "FSA", "FSAdata", "car", "multcomp", "plotrix", "nnet", "nlstools"), dependencies = TRUE)

Schedule / Curriculum

Arrival day

Get settled

Pass out pre-test (students do in evening)

Day 1

Morning:

1. Intro to statistics (3 hours)

Afternoon:

Collect tree data (30-45 minutes)

2. Introduction to R (2.5 hours)

Day 2

Morning:

3. Distributions and normality tests

Afternoon:

4. Transformations, T-tests, and non-parametric tests

Day 3

Morning:

5. ANOVA (2 hours)

6. Data wrangling (2 hours)

Afternoon:

Boats (manta surveys, plankton tow, CTD)

Day 4

Morning:

7. Linear regression (3 hours)

Afternoon:

Boats (manta surveys, plankton tow, CTD)

Day 5

Morning:

8. Multiple regression (1.5 hours)

9. Chi-square (1.5 hours)

Afternoon:

10. GLM Binomial (2 hours)

11. GLM Poisson (1 hour)

Day 6

Morning:

12. Tableau (4 hours)

Afternoon:

13. Visual communication skills (2 hours)

Day 7

Review

Day 8

Exam