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- Faculty Publications (572)
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- All HBS Web (621)
- Faculty Publications (572)
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods
Bojinov, Iavor I., Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih, and Michael W. Toffel. "Comparing Two Groups: Sampling and t-Testing." Harvard Business School Technical Note 621-044, August 2020.
- Article
How Much Is a Reduction of Your Customers' Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods
In many service industries, companies compete with each other on the basis of the waiting time their customers experience, along with other strategic instruments such as the price they charge for their service. The objective of this paper is to conduct an empirical... View Details
Keywords: Customer Satisfaction; Price; Service Delivery; Mathematical Methods; Competition; Food and Beverage Industry; Service Industry
Allon, Gad, Awi Federgruen, and Margaret P. Pierson. "How Much Is a Reduction of Your Customers' Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods ." Manufacturing & Service Operations Management 13, no. 4 (Fall 2011).
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- 2020
- Working Paper
Demystifying the Math of the Coronavirus
By: Elon Kohlberg and Abraham Neyman
We provide an elementary mathematical description of the spread of the coronavirus. We explain two fundamental relationships: How the rate of growth in new infections is determined by the “effective reproductive number” and how the effective reproductive number is... View Details
Kohlberg, Elon, and Abraham Neyman. "Demystifying the Math of the Coronavirus." Harvard Business School Working Paper, No. 20-112, April 2020. (Revised May 2020.)
Katherine B. Coffman
Katherine Coffman is the Piramal Associate Professor of Business Administration in the Negotiations, Organizations & Markets unit. Before joining HBS, she was an assistant professor of economics at The Ohio State University and a visiting assistant professor of... View Details
- December 2019
- Technical Note
Technical Note on Bayesian Statistics and Frequentist Power Calculations
By: Amitabh Chandra and Ariel Dora Stern
This Technical Note provides an introduction to Bayes’ Rule and the statistical intuition that stems from it. In this note, we review the concepts that underlie Bayesian statistics, and we offer several simple mathematical examples to illustrate applications of Bayes’... View Details
Chandra, Amitabh, and Ariel Dora Stern. "Technical Note on Bayesian Statistics and Frequentist Power Calculations." Harvard Business School Technical Note 620-032, December 2019.
- November 2018
- Case
Sportradar (A): From Data to Storytelling
By: Ramon Casadesus-Masanell, Karen Elterman and Oliver Gassmann
In 2013, the Swiss sports data company Sportradar debated whether to expand from its core business of data provision to bookmakers into sports media products. Sports data was becoming a commodity, and in the future, sports leagues might reduce their dependence on... View Details
Keywords: Sports Data; Data; Sport; Sportradar; Football; Soccer; Gambling; Betting; Betting Markets; Statistics; Odds; Live Data; Bookmakers; Betradar; Visualization; Integrity; Monitoring; Gaming; Streaming; 2013; St.Gallen; Algorithm; Mathematical Modeling; Carsten Koerl; Betandwin; Bwin; Wagering; Probability; Sports; Analytics and Data Science; Mathematical Methods; Games, Gaming, and Gambling; Transition; Strategy; Media; Sports Industry; Technology Industry; Information Technology Industry; Media and Broadcasting Industry; Europe; Switzerland; Asia; Austria; Germany; England
Casadesus-Masanell, Ramon, Karen Elterman, and Oliver Gassmann. "Sportradar (A): From Data to Storytelling." Harvard Business School Case 719-429, November 2018.
Celia Stafford
Celia Stafford is a doctoral student in Health Policy (Management). She received a B.A. in Mathematics and Economics from Emory University in 2017 and an MPH focused in Biostatistics from the University of North Carolina at Chapel Hill in 2020. She is also... View Details
- Research Summary
Valuation Theory and Practice
Timothy A. Luehrman's primary research interest is in the application of valuation methods to companies, businesses, and individual assets. Some of his work involves applications of tools originally developed for valuing derivative securities to the valuation of other... View Details
Elisabeth C. Paulson
Elisabeth Paulson is an Assistant Professor of Business Administration in the Technology and Operations Management Unit at Harvard Business School. She teaches the first year course on Technology and Operations Management in the required curriculum.
View Details
- February 2021
- Tutorial
What is AI?
By: Tsedal Neeley
This video explores the elements that constitute artificial intelligence (AI). From its mathematical basis to current advances in AI, this video introduces students to data, tools, and statistical models that make a computer 'intelligent.' Through an explanation of... View Details
- Article
Bilateral Contracts
By: Jerry R. Green and Seppo Honkapohja
A mathematical characterization of self-enforcing bilateral contracts is given. Contracts where both parties exercise some control over the quantity traded can sometimes be superior to contracts that rest control entirely with one side. Some qualitative characteristics... View Details
Green, Jerry R., and Seppo Honkapohja. "Bilateral Contracts." Journal of Mathematical Economics 11, no. 2 (1983): 171–187.
- Research Summary
Overview
Professor Goh’s primary research interest is applying mathematical models to real-world problems in health care in order to inform, improve, and enhance medical decision making and health policy. His recent work in this domain focuses on developing new methods for... View Details
- 16 May 2015
- Blog Post
Using an MBA to Reimagine the Music Industry
through the case method? Our HBS Takeaways series is an effort to help prospective students understand life at HBS through the experiences of students who are about to graduate. Kiran Gandhi studied mathematics at Georgetown before... View Details
- August 2005 (Revised September 2006)
- Case
Polyphonic HMI: Mixing Music and Math
By: Anita Elberse, Jehoshua Eliashberg and Julian Villanueva
In 2003, Mike McCready, CEO of Barcelona-based Polyphonic HMI, was preparing to launch an artificial intelligence tool that could create significant value for music businesses. The technology, referred to as Hit Song Science (HSS), analyzed the mathematical... View Details
Keywords: Forecasting and Prediction; Music Entertainment; Business History; Leadership; Marketing Strategy; Strategic Planning; Problems and Challenges; Mathematical Methods; Entertainment and Recreation Industry
Elberse, Anita, Jehoshua Eliashberg, and Julian Villanueva. "Polyphonic HMI: Mixing Music and Math." Harvard Business School Case 506-009, August 2005. (Revised September 2006.) (Spanish version also available.)
- 13 Apr 2012
- HBS Seminar
Drazen Prelec, Professor of Management Science and Economics at MIT Sloan School of Management
- Article
Improved Bounds on the Sizes of S.P Numbers
By: Paul Myer Kominers and Scott Duke Kominers
A number which is S.P in base r is a positive integer which is equal to the sum of its base-r digits multiplied by the product of its base-r digits. These numbers have been studied extensively in The Mathematical Gazette. Recently, Shah Ali... View Details
Keywords: Mathematical Methods
Kominers, Paul Myer, and Scott Duke Kominers. "Improved Bounds on the Sizes of S.P Numbers." Mathematical Gazette 94, no. 529 (March 2010): 127–129.
- 2022
- Article
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations
By: Tessa Han, Suraj Srinivas and Himabindu Lakkaraju
A critical problem in the field of post hoc explainability is the lack of a common foundational goal among methods. For example, some methods are motivated by function approximation, some by game theoretic notions, and some by obtaining clean visualizations. This... View Details
Han, Tessa, Suraj Srinivas, and Himabindu Lakkaraju. "Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022). (Best Paper Award, International Conference on Machine Learning (ICML) Workshop on Interpretable ML in Healthcare.)
- 03 Dec 2024
- HBS Seminar