This video introduced fair division. Site: http://mathispower4u.com
From playlist Fair Division
Discussions of circular inference (a.k.a. biased selection, a.k.a. double-dipping) and how to avoid it during statistical analyses. For more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/
From playlist OLD ANTS #8) Statistics
Random and systematic error explained: from fizzics.org
In scientific experiments and measurement it is almost never possible to be absolutely accurate. We tend to make two types of error, these are either random or systematic. The video uses examples to explain the difference and the first steps you might take to reduce them. Notes to support
From playlist Units of measurement
This lesson introduces the different sample methods when conducting a poll or survey. Site: http://mathispower4u.com
From playlist Introduction to Statistics
Conceptual Questions about Random Variables and Probability Distributions
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Conceptual Questions about Random Variables and Probability Distributions
From playlist Statistics
Sampling (2 of 5: Introduction to Random Samples and Spreadsheets)
More resources available at www.misterwootube.com
From playlist Data Analysis
Variance (4 of 4: Proof of two formulas)
More resources available at www.misterwootube.com
From playlist Random Variables
Sample bias: Response, Voluntary Response, Non-Response, Undercoverage, and Wording of Questions
From playlist Unit 4: Sampling and Experimental Design
Markets for Centralized Allocation Problems - F. Echenique - 1/31/2020
"Markets for Centralized Allocation Problems: Fairness, Efficiency, and Property Rights" Federico Echenique, Allen and Lenabelle Davis Professor of Economics, Caltech Abstract: Economists study naturally occurring markets and their welfare properties, but it is also possible to create art
From playlist HSS Caltech + Finance 2020
Cynthia Dwork - Scoring Functions Pt. 1/2 - IPAM at UCLA
Recorded 12 July 2022. Cynthia Dwork of Harvard University SEAS presents "Scoring Functions" at IPAM's Graduate Summer School on Algorithmic Fairness. Abstract: Scoring functions assign numbers to individuals that are frequently interpreted as probabilities, as in, “What is the probability
From playlist 2022 Graduate Summer School on Algorithmic Fairness
Algorithmic fairness and individual probabilities - Cynthia Dwork, Harvard University
The theory of algorithmic fairness has given rise to new fundamental questions and new insights into old questions. This talk outlines one such question -- what is the meaning of an "individual probability"? -- situating the problem in the context of algorithmic fairness. We propose a noti
From playlist Interpretability, safety, and security in AI
From playlist Mathematics of Sharing
Cynthia Dwork - Affirmative action, Composition Pt. 1/2 - IPAM at UCLA
Recorded 12 July 2022. Cynthia Dwork of Harvard University SEAS presents "Affirmative action, Composition" at IPAM's Graduate Summer School on Algorithmic Fairness. Abstract: Are systems that are composed of pieces that are each fair necessarily fair in the aggregate? We will discuss compo
From playlist 2022 Graduate Summer School on Algorithmic Fairness
Cynthia Dwork - Affirmative action, Composition Pt. 1/2 - IPAM at UCLA
Recorded 12 July 2022. Cynthia Dwork of Harvard University SEAS presents "Affirmative action, Composition" at IPAM's Graduate Summer School on Algorithmic Fairness. Abstract: Are systems that are composed of pieces that are each fair necessarily fair in the aggregate? We will discuss compo
From playlist 2022 Graduate Summer School on Algorithmic Fairness
The Most Powerful Tool Based Entirely On Randomness
We see the effects of randomness all around us on a day to day basis. In this video we’ll be discussing a couple of different techniques that scientists use to understand randomness, as well as how we can harness its power. Basically, we'll study the mathematics of randomness. The branch
From playlist Classical Physics by Parth G
Phebe Vayanos - Integer optimization for predictive & prescriptive analytics in high stakes domains
Recorded 01 March 2023. Phebe Vayanos of the University of Southern California presents "Integer optimization for predictive and prescriptive analytics in high stakes domains" at IPAM's Artificial Intelligence and Discrete Optimization Workshop. Abstract: Motivated by problems in homeless
From playlist 2023 Artificial Intelligence and Discrete Optimization
Cynthia Dwork - Group Fairness and Individual Fairness Pt. 1/2 - IPAM at UCLA
Recorded 11 July 2022. Cynthia Dwork of Harvard University SEAS presents "Group Fairness and Individual Fairness" at IPAM's Graduate Summer School on Algorithmic Fairness. Abstract: The early literature on the theory of algorithmic fairness identified two categories of fairness notions: gr
From playlist 2022 Graduate Summer School on Algorithmic Fairness
MIT 6.001 Structure and Interpretation of Computer Programs, Spring 2005 Instructor: Harold Abelson, Gerald Jay Sussman, Julie Sussman View the complete course: https://ocw.mit.edu/6-001S05 YouTube Playlist: https://www.youtube.com/playlist?list=PLE18841CABEA24090 Streams, Part 2 Despite
From playlist MIT 6.001 Structure and Interpretation, 1986
Discrete Random Variables (1 of 3: Expected value & median)
More resources available at www.misterwootube.com
From playlist Probability and Discrete Probability Distributions