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Resources: Teaching Materials

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1. 2020-02-13 17:07:38 | 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. 2020-02-12 20:27:04 | 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. 2020-02-12 20:18:35 | 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. 2020-02-10 22:18:37 | Contributor(s): Talisin Hammond, Rachel E. Walsh, Eileen Lacey | doi:10.25334/BEY3-QH48

A series of three modules using data from natural history museum collections to examine responses to climate change in multiple chipmunk species. Elevation and morphological data, beginner skills in R, ecological niche modeling in Maxent, and more.

5. 2020-01-27 21:11:02 | 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.

6. 2020-01-23 01:18:35 | Contributor(s): Shuchismita Dutta | doi:10.25334/EE3E-S080

Caffeine is a very common stimulant consume worldwide as tea, coffee, mate, cocoa, and chocolate. Ever wondered why plants make caffeine? Do all caffeine producing plants have the same enzymes for caffeine biosynthesis?

7. 2020-01-22 13:53:21 | Contributor(s): Serghei Mangul, Kristen Butela, Michael Sierk, Lihua Stefan | doi:10.25334/H7TG-G648

A laboratory module for an upper-level undergraduate biology course in which students will be able to carry out simple tasks using the Unix command-line environment.

8. 2020-01-13 20:13:06 | 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.

9. 2020-01-13 20:00:00 | 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.

10. 2020-01-13 19:37:01 | Contributor(s): Jeremy Claisse | doi:10.25334/SA4D-PF95

Interpreting One-Factor Analysis of Variance (ANOVA)

11. 2020-01-13 19:30:34 | Contributor(s): Bill Morgan | doi:10.25334/PQ79-N018

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

12. 2020-01-13 19:18:39 | 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.

13. 2020-01-10 21:29:24 | Contributor(s): Darlene Panvini | doi:10.25334/731M-8788

This PowerPoint presentation guides instructors and students through the key background information for the module.

14. 2020-01-10 20:52:41 | Contributor(s): Darlene Panvini | doi:10.25334/RN01-VX30

In this module, students will be introduced to some emerging biodiversity data resources. They will be asked to think critically about the strengths and utility of these data resources and apply what they have learned to research a question.

15. 2020-01-10 01:47:33 | Contributor(s): Erin R. Morris | doi:10.25334/YY9D-4W75

Genome Solver began as a way to teach undergraduate faculty some basic skills in bioinformatics; no coding or scripting is required. These activities have modified Lesson 1: Introduction to Genome Solver.

16. 2020-01-09 21:35:48 | Contributor(s): Selene Nikaido | doi:10.25334/Z8VP-G378

This lesson introduces the student to the Influenza Research Database. Students will select Influenza genome sequences to see how they are related. Students tests hypotheses about evolutionary ideas involving reassortment in Influenza.

17. 2020-01-09 21:32:41 | Contributor(s): Selene Nikaido | doi:10.25334/2ANZ-SV60

This exercise is an adaptation of the Annotation Lesson by Rosenwald et al. It introduces the use of bioinformatics tools to extract information from genome databases. It is a basic lesson on genome annotation databases.

18. 2020-01-08 04:30:57 | Contributor(s): Shawna Reed | doi:10.25334/JX5K-4E39

Genome Solver modules were combined to make one project for students using tools within NCBI BLAST to explore phylogenetics and horizontal gene transfer from phage to Chlamydia.

19. 2020-01-07 19:12:30 | Contributor(s): HHMI BioInteractive | doi:10.25334/2ZQV-7Y23

A short film explores the evolutionary connection between an infectious disease, malaria, and a genetic condition, sickle cell anemia. The animation explores the genetic causes and biological effects of sickle cell disease.

20. 2020-01-03 13:24:38 | Contributor(s): Robin Bulleri, Kristine Grayson, Melissa Csikari | doi:10.25334/GW48-XB61

A workshop on using HHMI BioInteractive data activities to teach science content and quantitative skills

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