This page features a selection of embedded Youtube videos. It starts with a selection of educational videos for econometrics, mathematics, and statistics.
It continues with a selection of Youtube videos about varies topics that have my interest.
All the video captions belong to the respective Youtube videos, I did not write them.

Selected educational videos

Ben Lambert: A full course in econometrics - undergraduate level

This selection of videos takes individuals through a full course in econometrics.
It starts at the absolute beginning assuming no prior knowledge, and will eventually build up to more advanced topics in regression analysis.

Statistics 110: Probability - Harvard University

Statistics 110 (Probability) has been taught at Harvard University by Joe Blitzstein (Professor of the Practice in Statistics, Harvard University) each year since 2006.
The on-campus Stat 110 course has grown from 80 students to over 300 students per year in that time.
Lecture videos, review materials, and over 250 practice problems with detailed solutions are provided.
This course is an introduction to probability as a language and set of tools for understanding statistics, science, risk, and randomness.
The ideas and methods are useful in statistics, science, engineering, economics, finance, and everyday life.
Topics include the following. Basics: sample spaces and events, conditioning, Bayes' Theorem.
Random variables and their distributions: distributions, moment generating functions, expectation, variance, covariance, correlation, conditional expectation.
Univariate distributions: Normal, t, Binomial, Negative Binomial, Poisson, Beta, Gamma.
Multivariate distributions: joint, conditional, and marginal distributions, independence, transformations, Multinomial, Multivariate Normal.
Limit theorems: law of large numbers, central limit theorem.
Markov chains: transition probabilities, stationary distributions, reversibility, convergence.
Prerequisite: single variable calculus, familiarity with matrices.

Selected personal favorites

The history of top chess players over time

Note: The y-axis is a rating of how well chess players compete against each other.
This rating varies over time, from EDO to CMR to ELO, because different data sources cover different periods of time.
I used cubic interpolation between data points when necessary (EDO and ELO) and applied a 6-month blur to the CMR data to make the lines smoother and easier to follow.