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    Writing Clean Code in R Workshop
    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.
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    Module M.1 R basics for data exploration and management
    Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology students on data management and statistical analysis...
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    Module M.2 Descriptive statistics
    Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology students on data management and statistical analysis...
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    REMNet Tutorial, R Part 5: Normalizing Microbiome Data in R 5.2.19
    Video on normalizing microbiome data from the Research Experiences in Microbiomes Network
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    Oyster Restoration Success and Water Quality in the James and Rappahannock Rivers of Virginia
    This QUBES lesson uses statistical analysis to test whether or not oyster restoration sites in Virginia are successfully increasing the number of oysters and whether or not water quality is...
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    Cleaning Data with R and the Tidyverse in Swirl
    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...
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    Working with Datasets in R swirl
    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...
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    Learning R for Biologists: A Mini Course Grab-Bag for Instructors
    As biology becomes more data driven, teaching students data literacy skills has become central to biology curriculum. Despite a wealth of online resources that teach researchers how to use R, there...
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