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    From Nano to Life: Interpreting graphs from Nanopore sequencing of bacterial genomes
    In this lesson, learners meet several scientists working on sustainable ways of recycling discarded electronics. Through an interactive H5P activity, participants watch videos and complete a series...
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    Coyote Habituation and a Scientist Spotlight on Dr. Christopher Schell
    Dr. Christopher Schell is an ecologist who uses a variety of techniques to study mammalian carnivores in urban areas. This scientist spotlight uses graphs from his study on parental habituation to...
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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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    RAT ATTACK! Population growth
    This module contains exercises focused on the use and interpretation of density independent and density dependent population growth models. Students build logistic and exponential growth models in...
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    Investigating human impacts on stream ecology: locally and nationally
    TIEE Module- How does nutrient pollution impact stream ecosystems locally and nationally? This is an adaptation of the module that includes statistical testing and links sections to a lab report...
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    Nucleoplasmic Index
    This module introduces the nucleoplasmic index in the context of understanding how the volume of organelles and cell contents change during the cell cycle. It is intended for an introductory...
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    Seed Dispersal in Tropical Forests
    In this activity, students use data from published studies to understand patterns of seed dispersal and apply these ideas to the design of a conservation area.
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    Tutorial Combination and Assessment
    The tutorial adaptation specifically addresses data types (i.e., numeric versus categorical variables) and the types of graphs that are used to summarize the different data types.
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    Spreadsheet Data Analysis Tutorial Series
    This series of self-paced tutorials show how to analyze data using a spreadsheet program.
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    Tag You're It: A Lesson Investigating Study Design and Survival Analysis on an American Shad Tagging Study
    In this lesson, students will learn about the various mark-recapture and tagging methods that are used in various scientific disciplines and the information they can gather. Key elements of...
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    Obesity - An Epidemic with Unexpected Causes, Consequences, and Complexity
    This dataset was collected from interviews conducted by the Centers for Disease Control and Prevention. State by state data are provided to explore the interactions of education, income, and...
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    Understanding Global Climate Change: Present, Past, and Future
    Understanding global climate change through the lenses of the present, past, and future, combining modern technology and indigenous knowledge and ways of knowing.
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    Basic Statistics
    The students will practice identifying the appropriate basic statistical tests when given a scenario and learn how to run and interpret those statistical tests in R.
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    Interpreting one-factor ANOVA in R with swirl
    Interpreting One-Factor Analysis of Variance (ANOVA)
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    Two-Way ANOVA
    In this lesson, students will learn the necessary statistical terms to understand two-way ANOVA, how to visualize their data, how to perform two-way ANOVA and interpret their results, and how to...
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    Biogeography of Hantavirus Hosts
    Using QGIS, this module introduces students to zoonotic pathogens, host biogeography, the "One Health" concept, forming hypothesis, and natural history museums within the Hantavirus system.
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    Temperature Balance Equation Activity
    Students learn about the temperature balance equation. They then conduct a thought experiment (with a worksheet) using the components of the equation to manage their heat balance for survival on a...
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    Creating Phylogenetic Trees from DNA Sequences
    This interactive module shows how DNA sequences can be used to infer evolutionary relationships among organisms and represent them as phylogenetic trees.
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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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