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Tags: R

Teaching Materials (1-20 of 34)

  1. A Quick Guide to Teaching R Programming to Computational Biology Students

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

    By Stephen Elgen

    University of Cambridge

    An introduction from an experienced educator in teaching R to computational biology graduate students.

    https://qubeshub.org/publications/838/?v=1

  2. A Very Basic Tutorial for Performing Linear Mixed Effects Analyses: Tutorial 2

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

    By Bodo Winter

    University of California, Merced

    The second of two tutorials that introduce you to linear and linear mixed models. This tutorial serves as a quick boot camp to jump-start your own analyses with linear mixed effects models.

    https://qubeshub.org/publications/833/?v=1

  3. An evolution curriculum designed around understanding the rise and spread of drug-resistant pathogens

    07 Jun 2018 | Teaching Materials | Contributor(s):

    By Aditi Pai1, Amanda Gibson2

    1. Spelman College 2. Emory University

    Poster on teaching concepts in evolution and data science skills in an upper level Biology elective at Spelman College presented at the 2018 QUBES/BioQUEST Summer Workshop

    https://qubeshub.org/publications/609/?v=1

  4. An introduction to population matrix models: a swirl lesson

    15 Jun 2020 | Teaching Materials | Contributor(s):

    By Jennifer Apple

    SUNY Geneseo

    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...

    https://qubeshub.org/publications/1926/?v=1

  5. An Introduction to the R Programming Environment

    04 Jan 2019 | Teaching Materials | Contributor(s):

    By K. A. Garrett1, P. D. Esker1, A. H. Sparks1

    Kansas State University

    An online module introducing students and biologists to R, published in American Phytopathological Society

    https://qubeshub.org/publications/1002/?v=1

  6. BIO 181G: The information age

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

    By Rachel Schwartz1, Linda Forrester1

    University of Rhode Island

    Course materials for BIO181G: The information age

    https://qubeshub.org/publications/883/?v=1

  7. BIO 263 Ecological Data Analysis

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

    By Rachel Schwartz1, Linda Forrester1

    University of Rhode Island

    Course materials for BIO 263 Ecological Data Analysis

    https://qubeshub.org/publications/885/?v=1

  8. BIO 439/539: Big Data Analysis

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

    By Rachel Schwartz1, Linda Forrester1

    University of Rhode Island

    Course materials for BIO 439/539: Big Data Analysis

    https://qubeshub.org/publications/884/?v=1

  9. BIO103R: Bio 103 and 104 Labs in R at URI

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

    By Rachel Schwartz1, Linda Forrester1

    University of Rhode Island

    GitHub repository for Bio 103 and 104 Labs in R at University of Rhode Island

    https://qubeshub.org/publications/886/?v=1

  10. Cleaning Data with R and the Tidyverse in Swirl

    09 Jun 2020 | Teaching Materials | Contributor(s):

    By Rachel Hartnett

    Oklahoma State University

    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...

    https://qubeshub.org/publications/1891/?v=1

  11. Coding Club: A Positive Peer-Learning Community

    22 Apr 2020 | Teaching Materials | Contributor(s):

    By Gergana Daskalova1, Sandra Angers-Blondin1, John Godlee1, Izzy Rich1, Beverly Tan1, Declan Valters1, Haydn Thomas1, Pedro Miranda1, Gabriela Hajduk1, Kat Keogan1, Isla Myers-Smith1, Kyle Dexter1, Christina Coakley1

    University of Edinburgh

    Free and self-paced tutorials and courses for learning to code out of the University of Edinburgh

    https://qubeshub.org/publications/1816/?v=1

  12. Computational Biology using R

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

    By Hong Qin

    University of Tennessee Chattanooga

    This is an introductory level course on computational biology.

    https://qubeshub.org/publications/907/?v=1

  13. Cookbook for R

    11 Sep 2018 | Teaching Materials | Contributor(s):

    By Winston Chang

    The goal of the cookbook is to provide solutions to common tasks and problems in analyzing data.

    https://qubeshub.org/publications/780/?v=1

  14. Data Analysis for the Life Sciences

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

    By Rafael A Irizarry1, Michael I Love1

    Harvard University

    An online stats book written completely in R

    https://qubeshub.org/publications/841/?v=1

  15. DataCamp

    05 Nov 2018 | Teaching Materials

    DataCamp: The Easiest Way to Learn Data Science Online

    https://qubeshub.org/publications/913/?v=1

  16. Ecology and Epidemiology in R

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

    By Paul Esker

    Kansas State University

    Ecology and epidemiology in R: Modeling dispersal gradients.

    https://qubeshub.org/publications/837/?v=1

  17. Introduction to R Course

    05 Nov 2018 | Teaching Materials

    Free Introduction to R Course at DataCamp

    https://qubeshub.org/publications/914/?v=1

  18. IPMpack: an R package for Integral Projection Models

    11 Sep 2018 | Teaching Materials | Contributor(s):

    By C. Jessica E. Metcalf1, Sean M. McMahon2, Roberto Salguero-Gómez3, Eelke Jongejans4, Cory Merow5

    1. University of Oxford 2. Smithsonian Tropical Research Institute 3. University of Queensland 4. Radbound University Nijmegen 5. STRI and University of Connecticut

    IPMpack is an R package (R Development Core Team 2013) that allows users to build and analyse Integral Projection Models.

    https://qubeshub.org/publications/779/?v=1

  19. 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

  20. NEON Data in the Classroom: Quantifying Spatial Patterns

    23 Jul 2020 | Teaching Materials | Contributor(s):

    By Kusum Naithani

    University of Arkansas, Fayetteville, AR 72701

    Students build on fundamental concepts of spatial patterns and combine this knowledge with the open-data from the National Ecological Observatory Network to quantify spatial autocorrelation and...

    https://qubeshub.org/publications/1398/?v=1