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    1999-Lomen-Lovelock-Data Sets from text Differential Equations Graphics-Models-Data
    Data selected by field is presented, e.g., chemistry, electricity, growth, motion, population, miscellaneous.

    Keywords: dataEstimate

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    Keep It Shrimple: An Adaptable Student-Driven Research Project for the Introductory Biology Laboratory
    A challenge in introductory biology laboratory courses is to provide students with authentic, engaging research opportunities that allow them to take ownership of their experiments. We present a...
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    Coloring and Keying Great Lakes Trees
    In this set of activities, you will use the Michigan Trees Coloring book to learn and practice plant identification. You will also simulate some of the steps of specimen preparation by keying an d...
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    Evaluating Representation in Science Through a Peer-Reviewed Research Study
    The demographic representation of scientists featured in biology curricular materials do not match that of the undergraduate biology student population or of the U.S. population. In this lesson, we...
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    Learning R for Biologists: A Mini Course Grab-Bag for Instructors
    As biology becomes more data driven, teaching students data literacy skills has become central to biology curriculum. Despite a wealth of online resources that teach researchers how to use R, there...
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    Serenity now! Keep calm and do science with real data in the classroom
    Presentation on a free web application currently under development on QUBES called Serenity at the 5th Life Discovery Conference
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    Consumable Science – Teaching Students to Translate Science for the General Public
    Poster about assignments with an emphasis on non-technical writing for a general audience. Presented at the 2021 BIOME Institute.
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    What is Science?
    This video has a philosophical focus and explores the nature of science. We’ll hear about how science is both a body of knowledge and a process. Peer review and confirmation bias will also be covered.
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    More In Depth Spreadsheet Management Adaptation of Data Management using NEON Small Mammal Data
    This adaptation consists of three exercises that introduce students to 1) format spreadsheet data tables, 2) carry out spreadsheet quality control, and 3) count/sort/filter data of interest in...
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    Bad Science: Exploring the unethical research behind a putative memory supplement
    As members of society, students must be able to evaluate scientific claims across a wide variety of media to make sound decisions about health and wellness. However, students - and most members of...
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    NEON_PDSI
    Users access and manipulate drought data and visualize these data to learn about historical drought patterns.
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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.
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    Introduction to Python for Data Science Course
    Free Introduction to Python for Data Science Course at DataCamp
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    Phenology publications
    Collection of modifications to TIEE phenology module from Data Discovery FMN

    Keywords: phenology

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    Remote sensing data processing – NEON airborne data
    Concepts of remote sensing and data logistics, and NEON remote sensing data are introduced. Students learn how to apply spatial data processing and visualization skills using R coding program to...
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    Yeast Cell Growth
    Numbers Count resource using Excel for data analysis
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    Data from: Agent-based and Individual-based Modeling: A Practical Introduction, Chapter 5, Section 5.5 [Elevation]
    Elevation data input file for Section 5.5 (tab-separated plain text).
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    Earth Analytics in Python Course
    Earth analytics is an intermediate, 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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    Summer 2019 Biobytes
    This series includes the four Biobytes that were piloted at the 2019 BioQUEST / QUBES Summer Workshop titled, “Evolution of Data in the Classroom: From Data to Data Science”.
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    Statistical Exploration of Climate Data
    In this module the students will learn some basic concepts in statistical thinking about data, with emphasis on exploratory data analysis.
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