Video Index

This page contains links to Playlists and individual videos, organized, roughly, by category. Generally speaking, the videos are organized from basic concepts to complicated concepts, so, in theory, you should be able to start at the top and work you way down and everything will make sense.


  • Statistics Fundamentals – These videos give you a general overview of statistics as well as a be a reference for statistical concepts. Topics include:
    • Histograms
    • What is a statistical distribution?
    • And many more!!!
  • Linear Regression and Linear Models – These videos teach the basics relating to one of statistics most powerful tools.  Linear Regression and Linear Models allow us to use continuous values, like weight or height, and categorical values, like favorite color or favorite movie, to predict a continuous value, like age.
  • Logistic Regression – These videos pick up where Linear Regression and Linear Models leave off. Now, instead of predicting something continuous, like age, we can predict something discrete, like whether or not someone will enjoy the movie Troll 2.
  • Machine Learning – Linear Models and Logistic Regression are just the tips of the machine learning iceberg. There’s tons more to learn, and this play list will help you trough it all, one step at a time.
  • High Throughput Sequence Analysis – If you do high-throughput sequence analysis, this playlist is for you!
  • Statistics in R – If you want to do any of this stuff in R, this playlist is for you, and you only. No one else is allowed to watch it.

Individual Videos are Below

Statistics Fundamentals:

Statistical Tests:

Machine Learning and Dealing with large datasets that have lots and lots of measurements per sample:

(NOTE: All of the linear model and curve fitting stuff in the “Basics” section is also considered to be Machine Learning, so make sure you check out those videos).

High-throughput Sequencing Analysis:

Live Streams:

  • 2020-01-06
    • 0:00 Introduction
    • 1:52 Comment #1 – What’s the difference between a single sample of 20 measurements and 4 samples of 5 measurements each.
    • 6:20 Comment #2 – Is machine learning a subset of statistics?
    • 9:59 Comment #3 – A poem!!!
    • 10:51 Viewer Questions/Comments Also, here’s the link to the Introduction to Statistical Learning:
  • 2020-01-20
    • 0:00 Introduction
    • 1:04 Comment #1 – What is your favorite machine learning algorithm
    • 4:40 Comment #2 – What id data leakage in machine learning?
    • 8:39 Comment #3 – Where do you learn these nitty gritty details?
    • 13:37 Live Question #1 – R-squared and Adjusted R-squared
    • 17:23 Live Question #2 – How are the videos arranged on (simple to complex)
    • 18:26 Live Question #3 – Is it important to learn all of the formulas and equations even though we have advanced software that does the work?
  • 2020-02-03
    • 0:00 Silly Song and Introduction
    • 0:18 A big huge announcement
    • 3:14 Question #1 – Do we use statistical models to predict or explain stuff?
    • 8:31 Question #2 – Can you show the effects of regularization?
    • 9:42 My cat, Poe
    • 15:04 Question #3 – How do I choose the best machine learning algorithm for my data?
    • 21:17 Live Questions
  • 2020-02-17
    • 0:00 Silly Song and Introduction
    • 0:46 Question #1 – What do we do with imbalanced data?
    • 13:24 Question #2 – Post-Hoc Tests for ANOVA
    • 22:11 Live Questions