All Categories (61-80 of 113)

1. 

   Jessica Donnelly

   https://qubeshub.org/community/members/10821

2. 

   Jon Yearsley

   https://qubeshub.org/community/members/5991

3. 

   Kanisorn Sawangsawai

   https://qubeshub.org/community/members/32000

4. 

   Keith John Wojciechowski

   https://qubeshub.org/community/members/8081

5. 

   Kenneth Uche Obiakor

   https://qubeshub.org/community/members/12566

6. Learning Quantitative Genetics: Investigation of Genetic Control for Cold Stress Response in Plants

   22 Feb 2022 | Teaching Materials | Contributor(s):

   By Irina Makarevitch*¹, Rae Goering¹

   Hamline University

   Course-embedded undergraduate research experiences (CUREs) for students have been shown to increase students’ understanding of the process of science, affirm their scientific identity, and...

   https://qubeshub.org/publications/2818/?v=1

7. Learning R for Biologists: A Mini Course Grab-Bag for Instructors

   21 Mar 2023 | Teaching Materials | Contributor(s):

   By Amanda D. Clark¹, Laurie S. Stevison*¹

   Auburn University

   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...

   https://qubeshub.org/publications/3698/?v=1

8. 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

9. 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...

10. 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

11. 

    Liz Lange

    https://qubeshub.org/community/members/36375

12. 

    M. Chantale Damas

    https://qubeshub.org/community/members/12652

13. 

    M. Chantale Damas

    https://qubeshub.org/community/members/12752

14. 

    Melissa C Srougi

    https://qubeshub.org/community/members/7897

15. Microbiology Data Problems 2023

    22 Feb 2023 | Teaching Materials | Contributor(s):

    By Charles E Deutch

    Microbion Research

    This project focuses on the use of data analysis problems to introduce students to specific topics in microbiology and to give them practice in the interpretation of figures and tables of data....

    https://qubeshub.org/publications/3693/?v=1

16. Modeling the Research Process: Authentic human physiology research in a large non-majors course

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

    By Anna K. Strain¹, Mary A. Williams¹, Jane Phillips¹

    University of Minnesota

    Laboratory experiences in large-enrollment introductory science courses often utilize “cookie-cutter style” laboratory experiences due to the relative simplicity of setting up the lab...

    https://qubeshub.org/publications/2516/?v=1

17. 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...

18. 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

19. Online Adaptation to "Gotcha! Which fly trap is the best? An introduction to experimental data collection and analysis"

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

    By Jenna Daypuk¹, Michelle G. Eng¹, Ian Black¹, Danica Levesque², Jesse Petahtegoose¹, Mitchell Slobodian¹, Athena Wallis¹, Joël Dickinson¹, Thomas J.S. Merritt*¹

    1. Laurentian University 2. École Secondaire du Sacré-Coeur

    We present here a simple and engaging experiment capitalizing on the universal need to rid our homes of fruit flies to teach experimental design and analysis. In an earlier paper, we described an...

    https://qubeshub.org/publications/2716/?v=1

20. Performing a Population Viability Analysis from Data Students Collect on a Local Plant

    out of 5 stars 

    23 Sep 2015 | | Contributor(s):: Noah Chamey, Sydne Record

    This resource has been updated - find the current version here: https://qubeshub.org/publications/264During two lab periods, students collect demographic data on perennial plants and then use these data in a matrix model to perform population viability analyses. During the first lab,...