04b Data Analytics Reboot: Statistical Expectation

Data Analytics and Geostatistics Undergraduate Course, Professor Michael J. Pyrcz Lecture Summary: Lecture on statistical expectation, description, properties and examples. A super powerful concept, essential for doing math with distributions and uncertainty. Also, critical for many statistical proofs. Lecture Python Demonstration Workflow: Statistical Expectation - https://github.com/GeostatsGuy/PythonNumericalDemos/blob/master/PythonDataBasics_Expectation.ipynb Theory and well-documented workflows linked to the lectures and interactive Python dashboards. Course Summary: Data Analytics and Geostatistics is an undergraduate course that I teach 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, and machine learning basics. I provide accessible content to help you face the digital revolution! My Shared Educational Content: YouTube: https://www.youtube.com/GeostatsGuyLectures GitHub: https://github.com/GeostatsGuy Course e-book: https://geostatsguy.github.io/GeostatsPyDemos_Book I share all of my university educational content to support students and working professionals interested to learn data analytics, geostatistics, and machine learning. More About the Author: https://michaelpyrcz.com I hope that you find my educational course content helpful on your data science journey, Professor Michael J. Pyrcz Cockrell School of Engineering Jackson School of Geosciences The University of Texas at Austin #dataanalytics #datascience #geostatistics #machinelearning