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  1. Jennifer Lynn Poulton

    https://qubeshub.org/community/members/4860

  2. Jeremy M Wojdak

    Jeremy is an aquatic community ecologist at Radford University in Virginia. He is currently investigating predator functional diversity and better models to understand how multiple predator species...

    https://qubeshub.org/community/members/1037

  3. Jessie Oehrlein

    I am statistics & math faculty at Fitchburg State University with a background in atmospheric science and an interest in K-16 math modeling and data literacy education.

    https://qubeshub.org/community/members/8042

  4. John J McGee

    https://qubeshub.org/community/members/5994

  5. Jory brinkerhoff

    https://qubeshub.org/community/members/4861

  6. Kate S Boersma

    https://qubeshub.org/community/members/10172

  7. Kim Bjorgo-Thorne

    https://qubeshub.org/community/members/15667

  8. Learning to Pipet Correctly by Pipetting Incorrectly?

    28 Aug 2021 | Teaching Materials | Contributor(s):

    By Stephanie F. Mel1, Melissa K. Micou1, Kshitij Gaur**1, David Lenh**1, Clifford Z. Liu**1, Stanley M. Lo*1

    University of California San Diego

    Beginning undergraduate students in biology need basic laboratory, data analysis, and science process skills to pursue more complex questions in course-based undergraduate research experiences...

    https://qubeshub.org/publications/2620/?v=1

  9. les steven nagy

    https://qubeshub.org/community/members/4544

  10. Linear Models and Linear Mixed Effects in R: Tutorial 1

    20 Oct 2018 | Teaching Materials | Contributor(s):

    By Bodo Winter

    University of California, Merced

    The first of two tutorials that introduce you to linear and linear mixed models.

    https://qubeshub.org/publications/832/?v=1

  11. Linear models and linear mixed effects models in R: Tutorial 1

    out of 5 stars 

    24 Apr 2015 | | Contributor(s):: Bodo Winter

    This resource has been updated - find the current version here: https://qubeshub.org/qubesresources/publications/832Linear models and linear mixed models are an impressively powerful and flexible tool for understanding the world. This tutorial is the first of two tutorials that introduce...

  12. Linear Regression (Excel) and Cellular Respiration for Biology, Chemistry and Mathematics

    03 Dec 2021 | Teaching Materials | Contributor(s):

    By Irene Corriette1, Beatriz Gonzalez1, Daniela Kitanska2, Henriette Mozsolits2, Sheela Vemu3

    1. Santa Fe College 2. Passaic County Community College 3. Waubonsee Community College

    Students typically find linear regression analysis of data sets in a biology classroom challenging. These activities could be used in a Biology, Chemistry, Mathematics, or Statistics course. The...

    https://qubeshub.org/publications/2811/?v=1

  13. Marney Pratt

    https://qubeshub.org/community/members/12436

  14. Michelle Jusino

    https://qubeshub.org/community/members/15779

  15. Modernizing Statistics Education via Biology Applications

    out of 5 stars 

    21 Oct 2015 | | Contributor(s):: Olcay Akman

    This resource has been updated - find the current version here: https://qubeshub.org/publications/254In most traditional statistics courses, instructors use data from different fields in an effort to give the courses an interdisciplinary flavor. They generally fail because these attempts...

  16. Modernizing Statistics Education via Biology Applications

    03 Jan 2018 | Teaching Materials | Contributor(s):

    By Olcay Ackman

    Illinois State University

    Part of the 2015 SMB Minisymposium: Topics in Biomathematics Education

    https://qubeshub.org/publications/254/?v=1

  17. MS in Data Science at University of Delaware

    Collections | 23 Jan 2019 | Posted by Alycia Crall

    https://qubeshub.org/community/groups/edsin/collections/opportunities-in-the-field

  18. Natalie Madeleine Howe

    https://qubeshub.org/community/members/6640

  19. Niels Proctor

    https://qubeshub.org/community/members/5775

  20. Numbers Count!: Statistics course

    out of 5 stars 

    28 Mar 2015 | | Contributor(s):: Claudia Neuhauser

    This resource has been updated - find the current version here: https://qubeshub.org/qubesresources/publications/750This course in the Numbers Count! curriculum introduces the basics of statistical analysis, including basic definitions, data visualization, and application. 

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