Students will learn how to set up a population matrix model in R and use it for demographic analysis of a population, including projecting population growth, determining lambda and the stable age distribution, and conducting an elasticity analysis.

Students will use swirl to understand Hardy-Weinberg equilibrium. The lesson starts with observed numbers of individuals for each genotype, and students will work through a number of steps to assess whether or not the population is in equilibrium.

We discuss what tests are appropriate to analyze the data from nutrient simulation experiments. They will conduct one-way ANOVAs and a post hoc test using a dummy dataset and interpret the results.

The overall goal is to help students learn common data cleaning procedures on a dataset once they’ve collected measurements and before they are able to start their analysis. This swirl lesson is designed specifically to deal with missing data.

The students will learn to estimate population sizes and consider assumptions of mathematical models and their applicability to the ecology of an organism/population

This lesson helps students know some of the options for how to graph grouped continuous data (such as those involved in doing a t-test or ANOVA) and how to choose the best option.

This lesson offers an introduction to ANOVA, including 1) how this statistical test can be differentiated from others and 2) a step-by-step guide to conducting and interpreting ANOVA results in R, including assumption testing and post-hoc analysis.

Interpreting One-Factor Analysis of Variance (ANOVA)

How to use the "three-prong" approach to check for normality

One-way analysis of variance (ANOVA), following the text in Chapter 5 of Beckerman et al. (2017) Getting started with R: an introduction for biologists, 2nd edition.

Video on analyzing microbiome data in Excel from the Research Experiences in Microbiomes Network

There are two complementary lessons. The first covers how sampling distributions are made and ID's their key properties. The second covers how null distributions and how the test statistic of a dataset and its p-value are visualized on this distribution.

This short swirl lesson on importing data is designed to 1) get a basic understanding in how tables are read into R and some common issues and 2) develop an individual set of instructions for students to use later to import a table on their own.

This lesson, created for an introductory ecology course, focuses on helping novice R users to import a data file, apply base R plotting functions, and use R Markdown to generate a reproducible report.

Session presentation on using Swirl, an interactive platform for learning and teaching R in the R console