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Show Results For
- All HBS Web
(4,777)
- People (10)
- News (1,049)
- Research (2,921)
- Events (70)
- Multimedia (35)
- Faculty Publications (1,687)
- March 2022 (Revised January 2025)
- Technical Note
Linear Regression
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to... View Details
Keywords: Data Science; Linear Regression; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Linear Regression." Harvard Business School Technical Note 622-100, March 2022. (Revised January 2025.)
- 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.)
- 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.)
- 13 Jun 2017
- Blog Post
7 Reasons Why the New MS/MBA: Engineering Sciences Program at Harvard is Next Level
companies now. i.e. This is bigger than just you. Interested in learning more about the MS/MBA? Here are four things you need to know. -- Anita Mehrotra is a Class of 2018 HBS student (Section I!) and was previously a data scientist at... View Details
- May 2017
- Other Article
Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis
By: Andrew Hill, Po-Ru Loh, Ragu B. Bharadwaj, Pascal Pons, Jingbo Shang, Eva C. Guinan, Karim R. Lakhani, Iain Kilty and Scott Jelinsky
BACKGROUND:
The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes.... View Details
Keywords: Crowdsourcing; Genome-wide Association Study; Logistic Regression; Open Innovation; PLINK; Collaborative Innovation and Invention
Hill, Andrew, Po-Ru Loh, Ragu B. Bharadwaj, Pascal Pons, Jingbo Shang, Eva C. Guinan, Karim R. Lakhani, Iain Kilty, and Scott Jelinsky. "Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis." GigaScience 6, no. 5 (May 2017).
- Winter 2017
- Article
Why Big Data Isn't Enough
By: Sen Chai and Willy C. Shih
There is a growing belief that sophisticated algorithms can explore huge databases and find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and... View Details
Keywords: Big Data; Science-based; Science; Scientific Research; Data Analytics; Data Science; Data-driven Management; Data Scientists; Technological Innovation; Analytics and Data Science; Mathematical Methods; Theory
Chai, Sen, and Willy C. Shih. "Why Big Data Isn't Enough." Art. 58227. MIT Sloan Management Review 58, no. 2 (Winter 2017): 57–61.
- August 2001
- Article
Technology as a Complex Adaptive System: Evidence from Patent Data
Fleming, L., and O. Sorenson. "Technology as a Complex Adaptive System: Evidence from Patent Data." Research Policy 30, no. 7 (August 2001).
- Research Summary
Overview
My current research focuses on the role of AI in shaping organizational knowledge production, learning, and innovation processes. I run field experiments to study early-stage idea generation and evaluation in entrepreneurial context. View Details
- 2016
- Working Paper
Pivoting Isn't Enough: Principled Pragmatism and Strategic Reorientation in New Ventures
By: Rory McDonald and Cheng Gao
New technology ventures often experience deviations from their original plans that oblige them to reorient in pursuit of better fit between their evolving products and target customers. Yet research is largely silent on how entrepreneurs explain and justify their... View Details
Keywords: Strategic Reorientation; Technology Entrepreneurship; Innovation; Product Development Processes; Organizational Adaptation; Qualitative Methods (General); Information Technology; Organizational Change and Adaptation; Communication; Entrepreneurship; Alignment; Innovation and Invention; Product Development
- August 2003
- Case
Mercury Computer Systems: The Evolution from Integrated Technology to Open Standard
By: Rebecca Henderson and Nancy Confrey
For 20 years, Mercury Computer Systems has thrived, providing products and services that support ultrafast processing of real time data. Now Jay Bertelli, the CEO, faces a critical question: How can the firm compete once the standards on which its products are based... View Details
Keywords: Analytics and Data Science; Open Source Distribution; Strategic Planning; Competitive Strategy; Competitive Advantage; Information Technology; Information Technology Industry
Henderson, Rebecca, and Nancy Confrey. "Mercury Computer Systems: The Evolution from Integrated Technology to Open Standard." Harvard Business School Case 704-424, August 2003.
- August 2018 (Revised September 2018)
- Supplement
LendingClub (C): Gradient Boosting & Payoff Matrix
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details
Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (C): Gradient Boosting & Payoff Matrix." Harvard Business School Supplement 119-022, August 2018. (Revised September 2018.)
- 24 May 2017
- Working Paper Summaries
Digital Labor Markets and Global Talent Flows
- 12 Nov 2018
- Working Paper Summaries
Product Quality and Entering Through Tying: Experimental Evidence
- Web
Lupoli Companies: Riverwalk – Making an Impact | Information Technology
Sal Lupoli talks about the history of Lawrence his vision for revitalization. “The case study so clearly shows the impact of business and how business done right can be so impactful for a community —... View Details
Rethinking the Profession Formerly Known as Advertising: How Data Science Is Disrupting the Work of Agencies
Speaker's Box, Journal of Advertising Research
“Speaker’s Box” invites academics and practitioners to identify potential areas of research affecting marketing and advertising. Its intention is to bridge the gap between the length... View Details
- 03 Jan 2017
- Research & Ideas
5 New Year's Resolutions You Can Keep (With the Help of Behavioral Science Research)
conduct sociological and psychological studies to get a true handle on what motivates people to do what they do—and what motivates them to do better. With that, we share some well-researched tips—based on... View Details
Keywords: by Carmen Nobel