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  1. Chi-squared test of independence between two categorical variables

    Chi-squared test of independence between two categorical variables

    2020-02-13 17:07:38 | Teaching Materials | Contributor(s): Matthew Aiello-Lammens | doi:10.25334/EM4Y-X154

    In this lesson, students will have the opportunity to work through a chi-squared test of independence between two categorical variables.

  2. Population Demography in Swirl

    Population Demography in Swirl

    2020-02-12 20:27:04 | Teaching Materials | Contributor(s): Emily Weigel | doi:10.25334/NANC-M515

    The students will learn to generate, test, and graphically represent basic hypotheses on data distributions using large datasets.

  3. Population Ecology in Swirl: Estimating Population Sizes

    Population Ecology in Swirl: Estimating Population Sizes

    2020-02-12 20:18:35 | Teaching Materials | Contributor(s): Mary E McWhirt, Emily Weigel | doi:10.25334/ABP7-GA97

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

  4. Basic Statistics

    Basic Statistics

    2020-01-27 21:11:02 | Teaching Materials | Contributor(s): Emily Weigel, Alycia Lackey | doi:10.25334/N0T7-DD80

    The students will practice identifying the appropriate basic statistical tests when given a scenario and learn how to run and interpret those statistical tests in R.

  5. Graphing grouped continuous data in R with swirl

    Graphing grouped continuous data in R with swirl

    2020-01-13 20:13:06 | Teaching Materials | Contributor(s): Marney Pratt | doi:10.25334/FM8B-PM89

    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.

  6. Conducting Analysis of Variance (ANOVA) in R with swirl

    Conducting Analysis of Variance (ANOVA) in R with swirl

    2020-01-13 20:00:00 | Teaching Materials | Contributor(s): Kevin Geyer | doi:10.25334/92KV-EH29

    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.

  7. Interpreting one-factor ANOVA in R with swirl

    Interpreting one-factor ANOVA in R with swirl

    2020-01-13 19:37:01 | Teaching Materials | Contributor(s): Jeremy Claisse | doi:10.25334/SA4D-PF95

    Interpreting One-Factor Analysis of Variance (ANOVA)

  8. Checking Normality in R with swirl

    Checking Normality in R with swirl

    2020-01-13 19:30:34 | Teaching Materials | Contributor(s): Bill Morgan | doi:10.25334/PQ79-N018

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

  9. One-way ANOVA in R with swirl

    One-way ANOVA in R with swirl

    2020-01-13 19:18:39 | Teaching Materials | Contributor(s): Bengt Allen | doi:10.25334/2MRV-SA62

    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.

  10. Island Biogeography

    Island Biogeography

    2020-01-01 21:47:29 | Teaching Materials | Contributor(s): Daniel Lauer, Emily Weigel | doi:10.25334/ABY7-GQ05

    The students will practice the basic code to test MacArthur and Wilson’s (1967) Island Biogeography model, focusing on how island size, distance, and perturbation affect species numbers.

  11. R Subsetting Tutorial

    R Subsetting Tutorial

    2020-01-01 21:18:30 | Teaching Materials | Contributor(s): Mary Kho, Emily Weigel | doi:10.25334/GZCA-S726

    The students will practice manipulating data to add to or extract subsets of specific values, rows, columns, or subsets of data contained in existing data files.

  12. Optimal Foraging in Swirl

    Optimal Foraging in Swirl

    2019-10-08 18:15:05 | Teaching Materials | Contributor(s): Mary Elizabeth McWhirt, Emily Weigel | doi:10.25334/2YEK-ZY02

    This lesson centers around the marginal value theorem (MVT, Charnov 1976), which describes how animals should forage in patches. It serves as a pre-lab to teach MVT basics, vectors, ANOVA, and basic plotting.

  13. Working with Datasets in R swirl

    Working with Datasets in R swirl

    2019-05-15 15:14:22 | Teaching Materials | Contributor(s): Caitlin Hicks Pries | doi:10.25334/Q4KF2V

    The goal of this lesson is to learn how to import datasets into R, understand variable types, make adjustments to variables, perform basic calculations, and begin data visualization. The exercise uses an over 100 year time series of climate data.

  14. Sampling Distributions and Null Distributions: two swirl lessons in R

    Sampling Distributions and Null Distributions: two swirl lessons in R

    2019-05-10 21:50:18 | Teaching Materials | Contributor(s): Rachel Hartnett | doi:10.25334/Q4KJ04

    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.

  15. Importing Data into R

    Importing Data into R

    2019-05-10 16:05:13 | Teaching Materials | Contributor(s): Rachel Hartnett | doi:10.25334/Q4W161

    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.

  16. Avian Censys Analysis

    Avian Censys Analysis

    2019-01-23 21:59:44 | Teaching Materials | Contributor(s): Darcy Taniguchi | doi:10.25334/Q4H44W

    This Swirl course uses ecological data of bird counts and habitat variables to estimate inter-observer variability and the relationship of birds with habitat variables.

  17. Exploring the functionality of R

    Exploring the functionality of R

    2019-01-23 21:53:55 | Teaching Materials | Contributor(s): Austin Happel | doi:10.25334/Q4MT7V

    Students work with example data to generate a length-weight plot and use lm() to obtain regression coefficients. Base plot functions are used to plot both the data and the regression line.

  18. Evolutionary Ecophysiology swirl lesson

    Evolutionary Ecophysiology swirl lesson

    2019-01-23 21:46:13 | Teaching Materials | Contributor(s): Nadia Aubin-Horth | doi:10.25334/Q4RM8D

    Uses swirl to walk students through how to use R and analyze their own data.

  19. Binomial test

    Binomial test

    2019-01-23 21:41:27 | Teaching Materials | Contributor(s): Stephen Gosnell | doi:10.25334/Q4WB30

    This lesson focused on introducing students to binomial data analysis and reinforcing concepts of confidence intervals, p-value interpretation, and one- vs two-sided tests.

  20. Two-Way ANOVA

    Two-Way ANOVA

    2019-01-23 21:18:11 | Teaching Materials | Contributor(s): Didem Ikis | doi:10.25334/Q45T6F

    In this lesson, students will learn the necessary statistical terms to understand two-way ANOVA, how to visualize their data, how to perform two-way ANOVA and interpret their results, and how to check for the ANOVA assumptions.