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Is bigger always better? An investigation on the effect of drought on different sizes of trees
11 Dec 2020 | Teaching Materials | Contributor(s):
By Jessica Brzyski
Seton Hill University
This data set was compiled from worldwide data to examine the effects of drought on trees. Included in the dataset are measurements of growth and mortality as they relate to the size category of...
Analysis of Amylase Activity
24 Nov 2020 | Teaching Materials | Contributor(s):
By Allison Carter Burlyn1, Christina Fieber1, Melanie Lenahan2
1. Horry-Georgetown Technical College 2. Raritan Valley Community College
This lab is an exploration of enzyme function and the effects of environmental conditions on the activity of the enzyme amylase. The lab utilizes analytical and graphing skills to assess enzyme...
Cleaning Data with R and the Tidyverse in Swirl
09 Jun 2020 | Teaching Materials | Contributor(s):
By Rachel Hartnett
Oklahoma State University
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...
Earth Analytics in Python Course
01 Nov 2019 | Teaching Materials | Contributor(s):
By Leah Wasser1, Jenny Palomino1, Chris Holdgraf2
1. Earth Lab - University of Colorado, Boulder 2. University of California, Berkeley
Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...
Get Started With GIS in Open Source Python Workshop
15 Oct 2019 | Teaching Materials | Contributor(s):
By Leah Wasser1, Jenny Palomino1, Joe McGlinchy1
Earth Lab - University of Colorado, Boulder
There are a suite of powerful open source python libraries that can be used to work with spatial data. Learn how to use geopandas, rasterio and matplotlib to plot and manipulate spatial data in...
Introduction to Version Control and Git Workshop
By Leah Wasser, Max Joseph
Learn how to use version control with Git to work collaboratively and back up your work.
Writing Clean Code in R Workshop
By Max Joseph1, Leah Wasser
When working with data, you often spend the most amount of time cleaning your data. Learn how to write more efficient code using the tidyverse in R.
Introduction to Earth Data Science Textbook
By Jenny Palomino, Leah Wasser
Introduction to Earth Data Science is an online textbook for anyone new to open reproducible science and the Python programming language. There are no prerequisites for this material, and no prior...
Earth Analytics in R Course
By Leah Wasser
Earth analytics is an advanced, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...
Earth Analytics Bootcamp Course
By Jenny Palomino1, Leah Wasser
The Earth Analytics Bootcamp is a three-week introductory-level course taught by instructors in Earth Lab and is a part of the Professional Certificate in Earth Data Analytics - Foundations at CU...
GMO Review Article
12 Oct 2019 |
Posted by Vedham Karpakakunjaram
Yeast Cell Growth
09 Sep 2019 | Teaching Materials | Contributor(s):
By Claudia Neuhauser
University of Houston
Numbers Count resource using Excel for data analysis
M. Chantale Damas
REMNet Tutorial, R Part 5: Normalizing Microbiome Data in R 5.2.19
28 Aug 2019 | Teaching Materials | Contributor(s):
By Jessica Joyner
CUNY Brooklyn College
Video on normalizing microbiome data from the Research Experiences in Microbiomes Network
REMNet Tutorial, Excel Part 1: Accessing Your Microbiome Data 5.3.19
By Jimiane Ashe
Video on accessing microbiome data from the Research Experiences in Microbiomes Network
Kenneth Uche Obiakor
Processes that Regulate Patterns of Species and Genetic Diversity - Intro Environmental Science
01 Jun 2019 | Teaching Materials | Contributor(s):
By Megan Kelly
Arrupe College of Loyola University Chicago
This activity was adapted for use in an intro non-majors Environmental Science course, with an emphasis on collaborative data collection.