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    Mysterious Occurrences: Representation, Resiliency, and Redundancy in Native Plant Populations
    Meet Dr. Rachel Hackett, a conservation plant biologist at the Michigan Natural Features Inventory.  We learn about Rachel's job and the restoration of threatened and endangered species. Rachel...

    Keywords: digital resourcesendangered speciesconservation sciencePlant Resilienceplant biodiversitydata skills

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    Investigating Evidence for Climate Change (Project EDDIE) with CO2 and 13CO2 data: adapted for R
    This is an adaptation to work in R of Investigating Evidence for Climate Change (Project) by Hage, M. 2020. Students will investigate geologic and modern evidence for global temperature and...

    Keywords: climate changeGlobal Temperature Changeco2ice core datastable isotopesR software

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    Modeling Changes in Probability of Presence of Myotis lucifugus Due to White Nose Syndrome: An Introduction to Logistic Regression in R
    In this lesson, students will learn more about the wildlife disease known as white nose syndrome and how it affects certain bat species more than others. Students will learn about the important...

    Keywords: ecologyconservationRStudiobatslogistic regressionGLMWildlife DiseaseWhite nose syndromelittle brown batsmyotis lucifugus

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    Pennies to The Moon Data Byte Series
    This series of Rbyte activities explores the concept of debunking using Fermi Estimation, R, and ChatGPT.

    Keywords: RprogrammingOpen SourceOpen Sciencedata literacycalling bullProgramming practiceFermi EstimationChatGPTGoogle CoLab

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    Setting Up Nonparametric Tests
    This swirl lesson will show you how to rearrange your data within R from one that shows a multiple factor design (2 x 2) to a single factor (4 levels) to allow for data analyses that require...
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    Interpreting one-factor ANOVA in R with swirl
    Interpreting One-Factor Analysis of Variance (ANOVA)

    Keywords: biostatisticsR programming languageSwirl

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    Computational Biology using R
    This is an introductory level course on computational biology.

    Keywords: simulationmoduleRcourseprojectsolutions

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    An introduction to population matrix models: a swirl lesson
    Students will learn how to set up a population matrix model in R and use it for demographic analysis of a population, including projecting population growth, determining lambda and the stable age...

    Keywords: population dynamicsRpopulation growthonlinedemographypopulation projection modelquantitative biologypopulation modelmatrix modelspopulation ecologyage structurepopulation biologypopulation modelingSwirlDemographic processespopulationLeslie matrix

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    Working with plant phenology data and fitting a nonlinear model using least squares in R
    A participatory live-coding lesson on working with NEON phenology data and fitting a sine-wave model to determine when different species get and lose their leaves.

    Keywords: modelingRphenologyNEONRstatscodeparticipatory live-coding

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    2014-Jiri_Lebl-Notes_on_Diffy_Qs_Differential_Equations_for_Engineers
    There is a pdf and html version of the text as well as a purchasable paperback version. The text has pretty much all the basics, but has only a few exercises and there is very little modeling.

    Keywords: differential equationstextbookengineering

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    2-001-NumericalMethodsComparisons-TechniqueNarrative
    This material teaches the basics of numerical methods for first order differential equations by following graphical and numerical approaches. We discuss the order of accuracy of the methods and...

    Keywords: Euler's methodimproved Euler's methodRK3 methodsRK4 methodsorder of accuracyabsolute errorCPU time

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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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    DataCamp
    DataCamp: The Easiest Way to Learn Data Science Online

    Keywords: statisticsRcurriculumdata visualizationdata scienceonline learningcoursemachine learningpythonlab protocol

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    Investigating human impacts on stream ecology: Intro to R
    This resource uses the Human Impact on Stream Ecology data set, background and questions and provides students an very general introduction to using R. Students perform basic summary statistics and...

    Keywords: graphingdata visualizationR programming languagedescriptive statisticsundergraduate environmental science

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    Ingestion of Microplastics by Coral
    QUBES lesson on ingestion of microplastics by coral. Lesson will give environmental background and then use R for hands-on statistical analyses, followed by critical thinking questions.

    Keywords: statisticsRenvironmentmicroplastic pollutioncoralwilcoxon

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    Value of Mistakes. Making Mistakes Using R
    This module allows students to frame mistakes and frustrations during their first introduction to R in terms of improved learning and growth mindset.

    Keywords: growth mindsetmath attitudesResources @ BIOMAAPmistakesvalue of mistakes

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    Drugging SARS-CoV-2
    This case study leads students through the process of proposing a drug for a novel protein. The Mpro protease of SARS-CoV-2 is explored in detail within the PDB. Aligns with first semester...

    Keywords: viruscoronavirusPDBSARS-CoV-2proteasedrug design

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    2009-Eriksson- Estep-Hansho-Johnson-Computational Differential Equations
    Differential Equations and Advanced Computational Differential Equations, presents a unified approach to computational mathematical modeling using differential equations based on a principle of a...

    Keywords: Galerkin

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    Home sweet home for warblers: Graphing and Analysis using R
    This resource expands on the Data Nugget "Trees and bushes, Home Sweet Home for Warblers". The analyses and graphing is done in R and there are questions that ask about the management implications.

    Keywords: graphingCommunity Ecologydata interpretationR software

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    Exploring the functionality of R
    Students work with example data to generate a length-weight plot and use lm() to obtain regression coefficients. Base plot functions are used to plot both the data and the regression line.
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