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    Fitting Exponential and Logistic Growth Models to Bacterial Cell Count Data
    In this activity, students will model a noisy set of bacterial cell count data using both exponential and logistic growth models. For each model the students will plot the data (or a linear...
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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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    Module M.5 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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    Module M.6 Generalized linear 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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    Module M.4 Simple linear regression analysis
    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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    Introduction to Primate Data Exploration and Linear Modeling with R
    Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology research students on data management and statistical...
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    Investigating human impacts on Southeastern US stream ecology using R
    Adaptation of the "Investigating human impacts on stream ecology: Scaling up from Local to National with a focus on the Southeast" specifically to focus on self-paced R code instruction
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    Graphing bacterial growth rates: semi-log graphs v linear graphs
    In this activity, students will explore the concept of binary fission, generation time, and bacterial growth curves, with an emphasis on the log phase. Students will use semi-log graphs and linear...
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    THE IMPORTANCE OF GREEN SPACES & NATIVE PLANTS TO URBAN AVIFAUNA: A Lesson on how urban residential yards can support birds during their annual cycle
    In this lesson students will learn about the impacts of urbanization, and the conservation challenges it poses to wildlife, in particular avifauna. Introductory ecology topics such as the theory of...
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    Module M.8 Survival analysis
    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.3 Visualizing data with ggplot2
    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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    Uninhibited Growth of Cells
    In this activity, students will explore the concept of binary fission, generation time, and bacterial growth curves, with an emphasis on the log phase. Students will use semi-log graphs and linear...
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    Quantifying Bacterial Growth in the Guts and Hemolymph of Fruit Flies: Mathematical Modeling and Data Interpolation/Extrapolation
    In this activity, students will analyze raw data obtained from an experiment that explores the effect of overexpressing the Ssk protein in order to strengthen the intestinal barrier and prevent...
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    Making “sense” out of surface area to volume relationships
    Using a multimodal approach, the non-linear aspect of the surface area to volume relationship is explored. Students use their their senses of taste and sight to determine how smaller cells and...
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    Calling Bullshit DCS 105 Bates College Figure of the Day
    Students use their number sense to make observations and come up with reasonable guesses or explanations for the patterns shown.
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