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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

    Keywords: VideoMicrobiology EducationR programming languagemicrobiomesresearch in the classroomREMNeturban microbiomes

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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...

    Keywords: graphingRStudioclimate change datatidyverseWorking with datasets

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    Using HHMI Tutorials to Prepare Students for Investigating Authentic Datasets in Biology
    HHMI tutorial modules were modified and condensed to bring all students up to the same skill level, and students took a pre-assessment to demonstrate adequate preparation for class.

    Keywords: Scientific ProcessStatistics and MathScientific Methodology

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    Introduction to Data Management and Metadata using NEON aquatic macroinvertebrate data
    This lesson focuses on understanding metadata, the data about the data, using aquatic macroinvertebrate abundance and species information from a variety of NEON sampling locations.

    Keywords: data managementSpreadsheetmetadata

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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

    Keywords: geneticsstatisticsdata analysisgraphingRStudioVideoexperimental designR programming languagemicrobiomesstudent researchinterdisciplinary educationlimnologyeco-informaticsresearch in the classroomtidyverseWorking with datasetsREMNet

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    Population Demography in Swirl
    The students will learn to generate, test, and graphically represent basic hypotheses on data distributions using large datasets.

    Keywords: ecologyPopulation statisticslife history curves

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    Large Datasets in R - Plant Phenology & Temperature Data from NEON
    This module series covers how to import, manipulate, format and plot time series data stored in .csv format in R. Originally designed to teach researchers to use NEON plant phenology and air...

    Keywords: data in the classroomtool:rstudiophenologydata managementNEONtemperature

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    DataONE Module 01: Why Data Management?
    Trends in data collection, storage and loss, the importance and benefits of data management, and an introduction to the data life cycle.

    Keywords: moduledatain-class activityHandoutproblem setdata managementDataONE

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    Examining human impacts on tusk evolution in elephants using authentic research data
    In this activity students explore and analyze real, authentic research data paired with HHMI’s “Selection for Tuskless Elephants” video in a hands-on investigation of human impacts on elephant...
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    Remote Sensing of Plants and Topography in R (Project EDDIE) for Advanced GIS class
    Students will explore different possible abiotic drivers of plant growth, defined as greenness and height. In the final step, students will analyze data from around the United States and consider...
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    REMNet Tutorial, Excel Part 6: Making Microbiome Column Charts 5.3.19
    Video on creating column charts in Excel from the Research Experiences in Microbiomes Network

    Keywords: ExcelVideoMicrobiology Educationmicrobiomesresearch in the classroomREMNeturban microbiomes

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    Calculating and Comparing Biodiversity Materials Across Sites Using NEON Herbaceous Vegetation Data - a Tutorial
    These materials are intended for use at the undergraduate level. They employ R and Excel software.
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    R Subsetting Tutorial
    The students will practice manipulating data to add to or extract subsets of specific values, rows, columns, or subsets of data contained in existing data files.
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    Using the Project Eddie Module “Paleoclimate and Ocean Biogeochemistry” in the Upper-Division Undergraduate Course “Climate and the Earth System”
    Students explore and compare datasets on modern nutrient concentrations and productivity, as well as paleo datasets to try to answer the question: “How does primary productivity influence global...

    Keywords: BiogeochemistryPaleoclimatepleoceanographygeochemistry

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    Lichens in Diverse Landscapes: EREN-NEON Flexible Learning Project
    This project makes use of publicly-available datasets on lichen presence and abundance and wet deposition, paired with geospatial data on air quality, tree canopy cover, and locally collected field...

    Keywords: NEONNational Ecological Observatory Network

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    Lichens in Diverse Landscapes: EREN-NEON Flexible Learning Project
    This project makes use of publicly-available datasets on lichen presence and abundance and wet deposition, paired with geospatial data on air quality, tree canopy cover, and locally collected field...

    Keywords: NEONNational Ecological Observatory Network

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    Lichens in Diverse Landscapes: EREN-NEON Flexible Learning Project
    This project makes use of publicly-available datasets on lichen presence and abundance and wet deposition, paired with geospatial data on air quality, tree canopy cover, and locally collected field...

    Keywords: NEONNational Ecological Observatory Network

    888

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    Lichens in Diverse Landscapes: EREN-NEON Flexible Learning Project
    This project makes use of publicly-available datasets on lichen presence and abundance and wet deposition, paired with geospatial data on air quality, tree canopy cover, and locally collected field...

    Keywords: NEONNational Ecological Observatory Network

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    431

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    Phenology Trends and Climate Change in Minnesota (Project EDDIE)
    In this module, students will practice answering a specific question about how climate change has affected flowering date in American elm trees. Students can then practice on a species of their own...
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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...

    Keywords: Rdata analysisdata manipulationRStudioManagement Of DataSwirl

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