Support

Support Options

  • Knowledge Base

    Find information on common questions and issues.

  • Support Messages

    Check on the status of your correspondences with members of the QUBES team.

Contact Us

About you
About the problem
Close
You are here: Home / Resources / Teaching Materials / Population Demography in Swirl / About

Population Demography in Swirl

By Emily Weigel

Georgia Institute of Technology

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

Listed in Teaching Materials | resource by group Make Teaching with R in Undergraduate Biology Less Excruciating

Version 4.1 - published on 10 Oct 2020 doi:10.25334/J72J-MZ12 - cite this

Licensed under CC Attribution-ShareAlike 4.0 International according to these terms

464 total view(s), 104 download(s)

0 comment(s) (Post a comment)

Description

This lesson centers around comparing the survivorship of two groups using a life table derived from tombstone information. Students will work through calculating some elements by hand via a worksheet alongside working in R. This swirl lesson goes step-by-step to show students how to do basic data manipulations, graphing, visual inspection of the data, and statistical tests as they work an example dataset with respect to a given hypothesis (whether males and females have the same life history curve). Students are then expected to repeat the coding steps they learned in R to test a hypothesis of their own.

Learning objectives:

  1. Complete a prelab reading to familiarize themselves with the goals of the lesson and the background ecological information of life tables
  1. Practice calculations and what the numbers in a life-table mean; generate associated hypotheses
  1. Practice coding elements necessary to generate datasets and test hypotheses based on the data
  1. Apply the coding learned through swirl to their own hypothesis to answer whether two groups in their data have the same survivorship

 

Contents

Cite this work

Researchers should cite this work as follows:

Tags

  1. Activity Length
  2. assessment
  3. bioinformatics
  4. Bioinformatics tools
  5. Concept inventories
  6. concept inventory
  7. Data retrieval
  8. data science
  9. data types
  10. gene expression
  11. gene regulation
  12. Instructional Setting
  13. Lab
  14. microRNAs
  15. More than 1 hour
  16. natural history
  17. Role of bioinformatics
  18. synthetic biology
  19. Teaching material

Notes

Please feel free to adapt this for use with other cemetery, longevity, or death datasets, provided that you are always respectful of the people your data represent.

Note:

Version 2.0 reorders the lessons and has code to get around package-dependences. Also, based on field tests, the lesson plan now includes code to help students with computer-specific issues on package installation found to be specific to Macs/Linux systems.

Version 3.0 builds on the last version by adding in commands which ensure matrices are built correctly in the newest packages. This version also adds a warning to examine the data within a generated matrix, specifically regarding 0's in comparison groups which can cause errors in running chi-square and G-test functions in edge cases. 

Version 4.0 adds additional instructions to aid with the code when run in base R (outside of swirl/RStudio).

Version 4.1 corrects a minor typo and provides an alternate instruction for graphing code use outside of swirl. 

 

Make Teaching with R in Undergraduate Biology Less Excruciating

Make Teaching with R in Undergraduate Biology Less Excruciating group image

When watching a resource, you will be notified when a new version is released.

Adapt 0
Close

Home

Search