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Show Results For
- All HBS Web
(1,716)
- People (9)
- News (315)
- Research (1,055)
- Events (15)
- Multimedia (10)
- Faculty Publications (864)
- 01 Sep 2010
- News
Faculty Books
The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance by Marshall Fisher and Ananth Raman (Harvard Business Press) Professor Raman and his coauthor explain how to use View Details
- 2023
- Working Paper
PRIMO: Private Regression in Multiple Outcomes
By: Seth Neel
We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
Neel, Seth. "PRIMO: Private Regression in Multiple Outcomes." Working Paper, March 2023.
- April 2023
- Technical Note
An Art & A Science: How to Apply Design Thinking to Data Science Challenges
By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
We hear it all the time as managers: “what is the data that backs up your decisions?” Even local mom-and-pop shops now have access to complex point-of-sale systems that can closely track sales and customer data. Social media influencers have turned into seven-figure... View Details
Parzen, Michael, Eddie Lin, Douglas Ng, and Jessie Li. "An Art & A Science: How to Apply Design Thinking to Data Science Challenges." Harvard Business School Technical Note 623-070, April 2023.
- March 2022 (Revised January 2025)
- Technical Note
Statistical Inference
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an overview of statistical inference for an introductory data science course. First, the note discusses samples and populations. Next the note describes how to calculate confidence intervals for means and proportions. Then it walks through the logic... View Details
Keywords: Data Science; Statistics; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Statistical Inference." Harvard Business School Technical Note 622-099, March 2022. (Revised January 2025.)
- March 2020
- Article
Diagnosing Missing Always at Random in Multivariate Data
By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details
Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods
Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
- November 2019
- Article
How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework
By: Doug J. Chung, Byungyeon Kim and Byoung G. Park
This paper evaluates the short- and long-term value of sales representatives’ detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call... View Details
Keywords: Nerlove-Arrow Framework; Stock-of-goodwill; Dynamic Panel Data; Serial Correlation; Instrumental Variables; Sales Effectiveness; Detailing; Analytics and Data Science; Sales; Analysis; Performance Effectiveness; Pharmaceutical Industry
Chung, Doug J., Byungyeon Kim, and Byoung G. Park. "How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework." Management Science 65, no. 11 (November 2019): 5197–5218.
- February 2011
- Supplement
Dataset for "Slots, Tables, and All That Jazz: Managing Customer Profitability at the MGM Grand Hotel" (CW)
By: Dennis Campbell and Francisco de Asis Martinez-Jerez
Datasets of gaming and hotel customers to perform analysis for the case. View Details
- 01 Mar 2018
- News
Democratizing Data to Favor Farmers
as much for the same seeds. That knowledge would help farmers haggle with dealers, but the real insight would come from analytics that go beyond consolidating seed prices to measuring a seed variety’s potential success. The most important... View Details
Keywords: Sasha Issenberg
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
Keywords: Large Language Model; AI and Machine Learning; Analytics and Data Science; Health Industry
Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- June 2023
- Article
How New Ideas Diffuse in Science
By: Mengjie Cheng, Daniel Scott Smith, Xiang Ren, Hancheng Cao, Sanne Smith and Daniel A. McFarland
What conditions help new ideas spread? Can knowledge entrepreneurs’ position and develop new ideas in ways that help them take off? Most innovation research focuses on products and their reference. That focus ignores the ideas themselves and the broader ideational... View Details
Keywords: Innovation Adoption; Natural Language Processing; Knowledge; Science; Innovation and Invention; Knowledge Sharing; Analytics and Data Science
Cheng, Mengjie, Daniel Scott Smith, Xiang Ren, Hancheng Cao, Sanne Smith, and Daniel A. McFarland. "How New Ideas Diffuse in Science." American Sociological Review 88, no. 3 (June 2023): 522–561.
- November 5, 2021
- Article
Leaders: Stop Confusing Correlation with Causation
By: Michael Luca
We’ve all been told that correlation does not imply causation. Yet many business leaders, elected officials, and media outlets still make causal claims based on misleading correlations. These claims are too often unscrutinized, amplified, and mistakenly used to guide... View Details
Keywords: Behavioral Economics; Data Analysis; Organizations; Decision Making; Analytics and Data Science; Analysis; Learning
Luca, Michael. "Leaders: Stop Confusing Correlation with Causation." Harvard Business Review Digital Articles (November 5, 2021).
- 2021
- Working Paper
Time Dependency, Data Flow, and Competitive Advantage
Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government... View Details
Keywords: Economics Of AI; Value Of Data; Perishability; Time Dependency; Flow Of Data; Data Strategy; Analytics and Data Science; Value; Strategy; Competitive Advantage
Valavi, Ehsan, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, and Karim R. Lakhani. "Time Dependency, Data Flow, and Competitive Advantage." Harvard Business School Working Paper, No. 21-099, March 2021.
- September 2024
- Exercise
Assessing the Value of Unifying and De-Duplicating Customer Data
By: Elie Ofek and Hema Yoganarasimhan
This exercise provides an opportunity for students to gain hands on experience with assessing the value of unifying various customer databases that a firm may have (e.g., across the different brands it markets) and of properly identifying customers to avoid duplication... View Details
Keywords: Customer Relationship Management; Measurement and Metrics; Analytics and Data Science; Value
Ofek, Elie, and Hema Yoganarasimhan. "Assessing the Value of Unifying and De-Duplicating Customer Data." Harvard Business School Exercise 525-023, September 2024.
- October 1994
- Article
When Worlds Collide: The Implications of Panel Data-Based Choice Models for Consumer Behavior
By: R. S. Winer, R.E. Bucklin, J. A. Deighton, J. Erdem, P.S. Fader, J.J. Inman, H. Katahira, Katherine N. Lemon and A. Mitchell
Winer, R. S., R.E. Bucklin, J. A. Deighton, J. Erdem, P.S. Fader, J.J. Inman, H. Katahira, Katherine N. Lemon, and A. Mitchell. "When Worlds Collide: The Implications of Panel Data-Based Choice Models for Consumer Behavior." Marketing Letters 5, no. 4 (October 1994).
- Article
Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates
By: J. Peter Scoblic
Would-be forecasters have increasingly extolled the predictive potential of Big Data and artificial intelligence. This essay reviews the career of Sherman Kent, the Yale historian who directed the CIA’s Office of National Estimates from 1952 to 1967, with an eye toward... View Details
Keywords: National Security; Analytics and Data Science; Analysis; Forecasting and Prediction; History
Scoblic, J. Peter. "Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates." Texas National Security Review 1, no. 4 (August 2018).
- December 2017
- Teaching Note
Yemeksepeti: Growing and Expanding the Business Model through Data
By: William R. Kerr and Alexis Brownell
Teaching Note for HBS No. 817-095. View Details
- Profile
Amanda Pratt
were very analytical and process oriented," she says. But there's another side to Amanda, one that wants to explore options and is willing to embrace novelty. Instead of going to a traditional engineering school, she chose a new... View Details
Keywords: Healthcare/Biotech
- Profile
Colt Stander
he says. “But the summer Analytics program really helped. It was a boot camp that boosted my confidence as well as my quantitative skills.” And upon reflection, design and business share similar challenges. The pathways aren’t clear,”... View Details
- 2023
- Article
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
- November–December 2015
- Article
Active Postmarketing Drug Surveillance for Multiple Adverse Events
By: Joel Goh, Margrét V. Bjarnadóttir, Mohsen Bayati and Stefanos A. Zenios
Postmarketing drug surveillance is the process of monitoring the adverse events of pharmaceutical or medical devices after they are approved by the appropriate regulatory authorities. Historically, such surveillance was based on voluntary reports by medical... View Details
Keywords: Drug Surveillance; Health Care; Stochastic Models; Queueing; Diffusion Approximation; Brownian Motion; Health Care and Treatment; Analytics and Data Science; Analysis
Goh, Joel, Margrét V. Bjarnadóttir, Mohsen Bayati, and Stefanos A. Zenios. "Active Postmarketing Drug Surveillance for Multiple Adverse Events." Operations Research 63, no. 6 (November–December 2015): 1528–1546. (Finalist, 2012 INFORMS Health Applications Society Pierskalla Award.)