Filter Results
:
(1,700)
Show Results For
-
All HBS Web
(1,700)
- People (9)
- News (315)
- Research (1,021)
- Events (12)
- Multimedia (10)
- Faculty Publications (833)
Show Results For
-
All HBS Web
(1,700)
- People (9)
- News (315)
- Research (1,021)
- Events (12)
- Multimedia (10)
- Faculty Publications (833)
- Sep 08 2016
- Testimonial
Aligning Your Company's Strategy
- 06 Dec 2021
- News
HBS Curricula Explore the Complexities of Innovation
of data management and analytics also led HBS to introduce Data Science for Managers, a new Required Curriculum elective for first-year MBA students. Then in their second year, they can choose from a range of data science courses (see...
View Details
Keywords:
Jennifer Gillespie
- 01 Jun 2010
- News
The MBA at a Crossroads
criticized business schools for serving up largely vocational training lacking in the analytical rigor deemed necessary to lay claim to academic respectability. Spurred on by the reports, business schools forged an View Details
- June 2022 (Revised July 2022)
- Technical Note
Causal Inference
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of...
View Details
Keywords:
Causal Inference;
Causality;
Experiment;
Experimental Design;
Data Science;
Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Technical Note 622-111, June 2022. (Revised July 2022.)
- October 2017
- Case
Quantopian: A New Model for Active Management
Keywords:
Big Data;
Hedge Fund;
Crowdsourcing;
Investment Fund;
Quantitative Hedge Fun;
Algorithmic Data;
Analytics and Data Science
Fleiss, Sara, Adi Sunderam, Luis M. Viceira, and Caitlin Carmichael. "Quantopian: A New Model for Active Management." Harvard Business School Case 218-046, October 2017.
- Article
Selecting the Right Growth Metrics: Fewer but Better
Keywords:
Supply Chains;
Big Data;
Corporations;
Franchising;
Performance Metrics;
Analytics and Data Science
Schlesinger, Leonard A. "Selecting the Right Growth Metrics: Fewer but Better." Stanford Social Innovation Review (website) (April 21, 2017).
- Sep 23 2015
- Interview
Interview with Faculty Chair Frank Cespedes
- Web
Creating Value in Business and Government (HKS-HBS Joint Degree Seminar) - Course Catalog
their third year. Its purpose is to integrate the perspectives and analytic tools provided by the HKS core curricula in the MPP or MPA/ID programs with the perspectives and analytic tools provided by the...
View Details
- Article
Beyond Statistics: The Economic Content of Risk Scores
By: Liran Einav, Amy Finkelstein, Raymond Kluender and Paul Schrimpf
"Big data" and statistical techniques to score potential transactions have transformed insurance and credit markets. In this paper, we observe that these widely-used statistical scores summarize a much richer heterogeneity, and may be endogenous to the context in which...
View Details
Einav, Liran, Amy Finkelstein, Raymond Kluender, and Paul Schrimpf. "Beyond Statistics: The Economic Content of Risk Scores." American Economic Journal: Applied Economics 8, no. 2 (April 2016): 195–224.
- February 25, 2016
- Article
The Hodgepodge Principle in U.S. Privacy Policy
By: John A. Deighton
Data, says Professor Lawrence Summers, is the new oil, "a hugely valuable asset essential to economic life." Personal data, the kind of data that invites thoughts of privacy, is a big part of that. The European Union saw this economic fuel source coming long ago and...
View Details
Keywords:
Data;
Privacy;
Technology;
Big Data;
Personal Data;
Marketing;
Information Technology;
Analytics and Data Science
Deighton, John A. "The Hodgepodge Principle in U.S. Privacy Policy." Harvard Law and Policy Review Blog (March 2, 2016). http://harvardlpr.com/2016/03/02/the-hodgepodge-principle-in-us-privacy-policy/.
- Aug 12 2015
- Testimonial
Building Connections and Advancing Careers
- 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
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.
- May 2020
- Article
Scalable Holistic Linear Regression
By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting...
View Details
Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
- August 2018 (Revised April 2019)
- Supplement
Chateau Winery (B): Supervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those...
View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
- August 2018 (Revised April 2019)
- Case
Chateau Winery (A): Unsupervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case follows Bill Booth, marketing manager of a regional wine distributor, as he applies unsupervised learning on data about his customers’ purchases to better understand their preferences. Specifically, he uses the K-means clustering technique to identify groups...
View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
- 25 Aug 2017
- Blog Post
HBS Interns: Summer Takeovers
in technology at the Sephora Innovation Lab. Jenn researched the impacts of artificial intelligence on the retail industry and participated in idea hackathons to brainstorm creative new ways for the brand to innovate. Adam Behrens, View Details
Keywords:
All Industries
- Article
Fast Generalized Subset Scan for Anomalous Pattern Detection
By: Edward McFowland III, Skyler Speakman and Daniel B. Neill
We propose Fast Generalized Subset Scan (FGSS), a new method for detecting anomalous patterns in general categorical data sets. We frame the pattern detection problem as a search over subsets of data records and attributes, maximizing a nonparametric scan statistic...
View Details
Keywords:
Pattern Detection;
Anomaly Detection;
Knowledge Discovery;
Bayesian Networks;
Scan Statistics;
Analytics and Data Science
McFowland III, Edward, Skyler Speakman, and Daniel B. Neill. "Fast Generalized Subset Scan for Anomalous Pattern Detection." Art. 12. Journal of Machine Learning Research 14 (2013): 1533–1561.
- October–December 2023
- Article
A Practical Guide to Conversation Research: How to Study What People Say to Each Other
By: Michael Yeomans, Katelynn Boland, Hanne K. Collins, Nicole Abi-Esber and Alison Wood Brooks
Conversation—a verbal interaction between two or more people—is a complex, pervasive, and consequential human behavior. Conversations have been studied across many academic disciplines. However, advances in recording and analysis techniques over the last decade have...
View Details
Yeomans, Michael, Katelynn Boland, Hanne K. Collins, Nicole Abi-Esber, and Alison Wood Brooks. "A Practical Guide to Conversation Research: How to Study What People Say to Each Other." Advances in Methods and Practices in Psychological Science 6, no. 4 (October–December 2023).
- May 2013
- Teaching Note
Launching Krispy Natural: Cracking the Product Management Code (Brief Case)
By: Frank V. Cespedes and Heather Beckham
This case study concerns a review and interpretation of test market results for a new packaged good product. The purpose of the case is to provide students with practice and guidelines in the analysis of quantitative test market data while illustrating the roles of...
View Details
- 29 Jun 2015
- HBS Case
Consumer-centered Health Care Depends on Accessible Medical Records
Charlotte, which in 2014 owned and managed hospitals and acute care facilities in three states. In 2011, Carolinas launched Dickson Advanced Analytics, which incorporated complex clinical, financial, demographic, and claims data to develop View Details