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  • All HBS Web  (1,114)
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Show Results For

  • All HBS Web  (1,114)
    • People  (1)
    • News  (177)
    • Research  (623)
    • Events  (18)
    • Multimedia  (5)
  • Faculty Publications  (377)
← Page 8 of 1,114 Results →
  • Article

Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
Keywords: Machine Learning; Algorithms; Fairness; Mathematical Methods
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Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
  • 16 Nov 2020
  • Blog Post

Flatiron School: Reflections from Summer 2020

In the summer of 2020, HBS Career & Professional Development (CPD) partnered with Flatiron School to provide students with an opportunity to gain practical skills, statistics fundamentals, and real-life data science project... View Details
Keywords: All Industries
  • Article

Risk and the Cross-Section of Stock Returns

By: Mark Seasholes, Radu Burlacu, Patrice Fontaine and Sonia Jimenez-Garces
This paper mathematically transforms unobservable rational expectation equilibrium model parameters (information precision and supply uncertainty) into a single variable that is correlated with expected returns and that can be estimated with recently observed data. Our... View Details
Keywords: Risk Premiums; Cross-sectional Asset Pricing; REE Models; Risk and Uncertainty; Asset Pricing; Investment Return
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Seasholes, Mark, Radu Burlacu, Patrice Fontaine, and Sonia Jimenez-Garces. "Risk and the Cross-Section of Stock Returns." Journal of Financial Economics 105, no. 3 (September 2012): 511–522.
  • March 2002
  • Case

Women and Power: Stories From Around the Globe

By: Kathleen L. McGinn, Alexis Lefort and Nicole Nasser
This case uses vignettes and statistics of the broader issue discussed in each vignette to explore some of the ways in which gender is played out in the struggle for power and control. Disenfranchised groups--those not allowed access to critical resources--have little... View Details
Keywords: Equality and Inequality; Gender; Power and Influence
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McGinn, Kathleen L., Alexis Lefort, and Nicole Nasser. "Women and Power: Stories From Around the Globe." Harvard Business School Case 902-203, March 2002.
  • 2024
  • Working Paper

Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference

By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
Keywords: Mathematical Methods; Analytics and Data Science
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Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
  • July 2013
  • Teaching Note

Google's Project Oxygen: Do Managers Matter?

By: David A. Garvin
Google's Project Oxygen started with a fundamental question raised by executives in the early 2000s: do managers matter? The topic generated a multi-year research project that ultimately led to a comprehensive program, built around eight key management attributes,... View Details
Keywords: Organizational Behavior; Business Policy; General Management; Human Resource Management; Management; Leadership; Human Resources
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Garvin, David A. "Google's Project Oxygen: Do Managers Matter?" Harvard Business School Teaching Note 314-016, July 2013.
  • June 2005
  • Case

Billy Beane: Changing the Game

Describes how Billy Beane, general manager of the Oakland A's baseball team, employs statistical methodologies to select who is undervalued in the marketplace. Examines why few teams have imitated his organization's successful strategy. Explores threats to Oakland's... View Details
Keywords: Resource Allocation; Competitive Advantage; Sports; Sports Industry; California
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Roberto, Michael. "Billy Beane: Changing the Game." Harvard Business School Case 305-120, June 2005.
  • March 1993
  • Supplement

Burroughs Wellcome and AZT (C)

By: Willis M. Emmons III
Describes key developments relating to Burroughs Wellcome, AZT and other AIDS drugs, and the AIDS issue in general from late 1989 through 1992. Includes excerpts from Wellcome PLC's financial statements and updated statistics on AIDS in the United States. View Details
Keywords: Health Pandemics; Multinational Firms and Management; Financial Statements; Pharmaceutical Industry; United States
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Emmons, Willis M., III. "Burroughs Wellcome and AZT (C)." Harvard Business School Supplement 793-115, March 1993.

    Jung Koo Kang

    Jung Koo Kang is an assistant professor in the Accounting and Management Unit. He teaches the Financial Reporting and Control course in the MBA required curriculum.

    Professor Kang’s research focuses on financial technology and innovation, alternative data,... View Details

    • June 2014 (Revised July 2014)
    • Background Note

    An Overview of Project Finance and Infrastructure Finance—2014 Update

    By: Benjamin C. Esty, Carla Chavich and Aldo Sesia
    Provides an introduction to the fields of project finance and infrastructure finance, and gives a statistical overview of project-financed investments over the years from 2009 to 2013. Examples of project-financed investments include the Kashagan oil field development... View Details
    Keywords: Globalization; Capital Expenditures; International Finance; Data; Financial History; Economic Development; Corporate Governance; Contracts; Industry Analysis; Banking; Capital Investments; Municipal Finance; Project Finance; Infrastructure; Investment; Projects; Trends
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    Esty, Benjamin C., Carla Chavich, and Aldo Sesia. "An Overview of Project Finance and Infrastructure Finance—2014 Update." Harvard Business School Background Note 214-083, June 2014. (Revised July 2014.)

      Antonio Moreno

      Antonio (Toni) Moreno is the Sicupira Family Associate Professor in the Technology and Operations Management Unit. He teaches courses related to technology and operations management in the MBA, executive, and doctoral programs. Before joining HBS, he was an... View Details

      Keywords: retailing; internet; e-commerce industry
      • January 2021
      • Case

      The FIRE Savings Calculator

      By: Michael Parzen and Paul Hamilton
      This case follows Carol Muñoz, a member of the Financial Independence, Retire Early (FIRE) lifestyle movement. At the age of 45, Carol is considering retiring and living off the $1 million she has accumulated. Using Monte Carlo simulation, Carol forecasts the... View Details
      Keywords: Analysis; Forecasting and Prediction; Financial Strategy; Investment Portfolio; Investment Return; Personal Finance; Saving; Risk and Uncertainty; Diversification; Theory; Personal Development and Career; Financial Services Industry
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      Parzen, Michael, and Paul Hamilton. "The FIRE Savings Calculator." Harvard Business School Case 621-087, January 2021.
      • June 2021
      • Technical Note

      Introduction to Linear Regression

      By: Michael Parzen and Paul Hamilton
      This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical... View Details
      Keywords: Linear Regression; Regression; Analysis; Forecasting and Prediction; Risk and Uncertainty; Theory; Compensation and Benefits; Mathematical Methods; Analytics and Data Science
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      Parzen, Michael, and Paul Hamilton. "Introduction to Linear Regression." Harvard Business School Technical Note 621-086, June 2021.

        Alberto F. Cavallo

        Alberto Cavallo is the Thomas S. Murphy Professor of Business Administration at Harvard Business School, where he teaches in the Business, Government, and the International Economy (BGIE) unit, a Faculty Research Fellow at the National Bureau of Economic Research, a... View Details

        • 06 Apr 2020
        • Working Paper Summaries

        A General Theory of Identification

        Keywords: by Iavor Bojinov and Guillaume Basse
        • February 2021
        • Tutorial

        T-tests: Theory and Practice

        By: Michael Parzen, Natalie Epstein, Chiara Farronato and Michael Toffel
        This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with... View Details
        Keywords: Data Analysis; Data Analytics; Experiment Design; Experimentation; Analytics and Data Science; Analysis
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        Parzen, Michael, Natalie Epstein, Chiara Farronato, and Michael Toffel. T-tests: Theory and Practice. Harvard Business School Tutorial 621-707, February 2021.
        • 08 Jun 2016
        • News

        Study: Airbnb hosts discriminate

          Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

          We study the data deletion problem for convex models. By leveraging techniques from convex optimization and reservoir sampling, we give the first data deletion algorithms that are able to handle an arbitrarily long sequence of adversarial updates while promising... View Details
          • 08 Jun 2021
          • News

          Harvard Business School Professor Says 65% of Startups Fail for One Reason. Here's How to Avoid It.

          • 07 Aug 2017
          • News

          New Harvard Business Analytics Program

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