The Hub

The Community of Minds

  • The Hub
  • About TheCOM™
    • Testimonials
    • About The Founder: Bethany Huot
  • TheCOM Center for Educative Research™
    • Educative Research™
    • The BIOME Project
  • FAQ
  • The Whiteboard
  • Strategic Career Management (SCM)
    • SCM: Identify
    • SCM: Defining The Void
    • SCM: Commit
    • SCM: Community Perspectives
  • The Resources
    • Digital Identity Management
    • Networking & Science Communication (#SciComm)
    • Writing & Peer Review
    • Bioinformatics & Statistics
    • Methods & Technologies
    • Teaching & Learning (T&L)
      • T & L Communities
      • T & L Training Programs/Fellowships
      • T & L Career Path Prep
      • T & L Tools & Resources
    • Career Prep
    • Job Hunting
  • The Vault (Archive)
    • The File Cabinet
      • The Pub Club Files:
        • The News
        • The Pub Club
          • The Mission
          • The People
          • The Mug Club
            • The Coaster Club
          • The Python Group
          • The Publications
            • Favorite Pubs
            • Papers of Interest…
            • Scoop.it
        • 2017 Summer – Summaries & Docs
        • 2017 Spring – Summaries & Docs
        • 2016 Fall – Summaries & Docs
        • 2016 Summer – Summaries & Docs
        • 2016 Spring – Summaries & Docs
        • 2015 Fall – Summaries & Docs
        • 2015 Summer – Summaries & Docs
        • 2015 Spring – Summaries & Docs
        • 2014 Fall – Summaries & Docs

Bioinformatics & Statistics

If you have useful links to share, please share them using the Comment Box (below). We will review and add them here.

Related Posts:

  • Science Alert: Statistics in Biology
  • Data Presentation Beyond the Bar Graph

  • Cognitive bias in research…

  • Misuse of p-values

  • Shifting from the t-test to ANOVA

  • Robin’s Resources

  • MSU Courses in Statistics & Computer Science

MSU Courses:

Statistics
  • Statistics for Biologists (STT464): This course is a step1 for individuals with no background in statistics. The course covers the basics of the importance of statistical analysis, experimental design, ttests, ANOVAs, chi-squared tests and the like. I found this course particularly helpful when it came to the broad introduction. There is a BRIEF introduction to R/Rstudio. It is setup very much like an undergrad course in statistics would be but is ~90% graduate students.  ~ information from Shawna Rowe
  • Advanced Statistics for Biologists (STT814): This course is largely an introduction to experimental design and SAS. The course runs on the assumption that 464 was completed previously, but doesn’t require many tedious by hand calculations and (in my opinion) serves as a sufficient introduction to many statistical methods and covers more detailed types of tests that may be useful. The caveat is that it is done THROUGH the use of SAS, which is often times frustrating since many have moved to R (rightfully so, in my opinion). ~ information from Shawna Rowe

Computer Science
  • Computer Science for Evolutionary Biologists (CSE801): Don’t be fooled by the course name! This is a small class that is required for students receiving a particular type of BEACON funding. Evolution is mentioned and appreciated but not the focus of the course in the slightest. It is able to be audited and served as a phenomenal introduction to python and the usefulness of knowing a language. The class is very small and the students sit around and learn python as a group— taught by a computer scientist (often times one that studies artificial intelligence or evolution using digital organisms and the like). The end project requires the development of some sort of model or writing a program that is capable of performing a tedious task (i.e. maze generation and solving or automated sequence alignments). Those who audit the course do not complete the final project and can skedaddle with fresh python skills and no additional gray hairs sprouted as a consequence of completing the final project. ~ information from Shawna Rowe

Tutorials:

UNIX
  • UNIX/Linux Tutorial for Beginners
Python
  • The Python Tutorial
  • Python Programming Tutorial
R
  • Cyclismo R tutorial
  • An R Introduction to Statistics
  • Quick-R
  • Introduction to using R: The Statistical Programming Language
  • Code School: R

Resources:

Statistics
  • MSU CANR Biometry Group Statistical Consulting Center – Get expert help on your experimental design and data analysis. This resource was shared by TPC member, Amy Baetsen-Young, who reported getting great help from Chun-Lung Lee at the Consulting Center.
  • Points of Significance (Nature)
UNIX
  • Unix Toolbox
  • Basic Unix Commands
  • Treebeard’s Unix Cheat Sheet
Python
  • Think Python: How to Think Like a Computer Scientist
  • Learn Python The Hard Way
R
  • R home page
  • R archive (download R)
  • R FAQ
  • R manuals
  • An Introduction to R
  • R Studio download

Share this:

  • Tweet
  • Email
  • Share on Tumblr

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Pages

  • The Hub
  • About TheCOM™
    • Testimonials
    • About The Founder: Bethany Huot
  • TheCOM Center for Educative Research™
    • Educative Research™
    • The BIOME Project
  • FAQ
  • The Whiteboard
  • Strategic Career Management (SCM)
    • SCM: Identify
    • SCM: Defining The Void
    • SCM: Commit
    • SCM: Community Perspectives
  • The Resources
    • Digital Identity Management
    • Networking & Science Communication (#SciComm)
    • Writing & Peer Review
    • Bioinformatics & Statistics
    • Methods & Technologies
    • Teaching & Learning (T&L)
      • T & L Communities
      • T & L Training Programs/Fellowships
      • T & L Career Path Prep
      • T & L Tools & Resources
    • Career Prep
    • Job Hunting
  • The Vault (Archive)
    • The File Cabinet
      • The Pub Club Files:
        • The News
        • The Pub Club
          • The Mission
          • The People
          • The Mug Club
            • The Coaster Club
          • The Python Group
          • The Publications
            • Favorite Pubs
            • Papers of Interest…
            • Scoop.it
        • 2017 Summer – Summaries & Docs
        • 2017 Spring – Summaries & Docs
        • 2016 Fall – Summaries & Docs
        • 2016 Summer – Summaries & Docs
        • 2016 Spring – Summaries & Docs
        • 2015 Fall – Summaries & Docs
        • 2015 Summer – Summaries & Docs
        • 2015 Spring – Summaries & Docs
        • 2014 Fall – Summaries & Docs

The Hub: By Extension

copyright 2021 Bethany Huot/TheCOM,LLC / Powered by WordPress | theme SG Double