2b Data Analytics: Frequentist Probability

Lecture about frequentist probability, including probability concepts and operators such as addition rule, multiplication rule, marginalization, conditional and joint probability, and independence. It is all about counting and ratios!
Follow along with the interactive demonstration workflow in Python:
o. Interactive marginal, conditional and joint probability and distribution calculation: github.com/GeostatsGuy/Python...
Follow along with the demonstration workflow in Excel:
o. Marginal, conditional and joint probability calculation: github.com/GeostatsGuy/ExcelN...
Data Analytics and Geostatistics is an undergraduate course that I teach fall and spring semesters at The University of Texas at Austin. We build up fundamental spatial, subsurface, geoscience and engineering modeling, from probability, statistics, heterogeneity measures, spatial continuity models, spatial estimation, spatial simulation, model checking, decision making, up to machine learning basics. I provide accessible content to help you face the digital revolution!
Learn more me and my research program at The University of Texas at Austin at www.michaelpyrcz.com.
I hope you find this course content useful,
Michael J. Pyrcz
Professor
Cockrell School of Engineering
Jackson School of Geosciences
The University of Texas at Austin

[@shrigy]

Hi Michael, great lectures, thanks alot! As the normal working routine during the current Covid-19 home office arrest is abit boring and frustrating, i try to smarten up by absorbing one of your videos per day. Something i normally would never get round to.
I tried to draw a Venn diagram for the case of independant events, but i struggle. Is it possible to draw this without violating the rules for general conditional probabilities?

[@GeostatsGuyLectures]

Howdy Shrigy! Sorry I just saw this. For independence, recall P(B|A) = P(B). I find that drawing 2 rectangles is the easiest way to do this.