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    Chapter 1: Introduction to R and RStudio
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    Chapter 3: Visualizing data
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    Chapter 10: Two-way analysis of variance
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    Chapter 8: Comparing two means: the t-test
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    Chapter 7: The normal distribution
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    Chapter 6: Population proportions and the binomial distribution
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    Chapter 5: Hypothesis testing
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    Chapter 4: Probability distributions
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    An Introduction to the R Programming Environment
    An online module introducing students and biologists to R, published in American Phytopathological Society
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    Introduction to R Course
    Free Introduction to R Course at DataCamp
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    REMNet Tutorial, R Part 1: Getting Started in R with Microbiome Data 5.3.19
    Video on the basics of R software from the Research Experiences in Microbiomes Network
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    Chapter 9: One-way analysis of variance
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    Chapter 2: Data sampling, accuracy, and precision
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    REMNet Tutorial, R Part 2: Importing Your Microbiome Data into R 5.3.19
    Video on importing data into R from the Research Experiences in Microbiomes Network
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    Earth Analytics in R Course
    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...
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    Module M.7 Generalized linear mixed-effects models
    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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    Chapter 11: Correlation and regression analyses
    Biostatistics Using R: A Laboratory Manual was created with the goals of providing biological content to lab sessions by using authentic research data and introducing R programming language....
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    REMNet Tutorial, R Part 3: Creating Alpha Diversity Plots in R 5.2.19
    Video on creating alpha diversity plots in R from the Research Experiences in Microbiomes Network
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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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    Checking Normality in R with swirl
    How to use the "three-prong" approach to check for normality
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