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(1,117)
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- Multimedia (5)
- Faculty Publications (371)
Show Results For
- All HBS Web
(1,117)
- People (1)
- News (169)
- Research (614)
- Events (17)
- Multimedia (5)
- Faculty Publications (371)
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- 1977
- Article
On the Joint Distribution of Left- and Right-sided Outliner Statistics
By: André Perold and D. M. Hawkins
Keywords: Mathematical Methods
Perold, André, and D. M. Hawkins. "On the Joint Distribution of Left- and Right-sided Outliner Statistics." Utilitas mathematica 12 (1977): 129–143.
- December 2002
- Supplement
Basic Statistics from the World Bank's World Development Indicators, 2002
By: David A. Moss and Sarah A. Brennan
Spreadsheet for use with case (9-703-030). Download Only. View Details
- December 2002
- Supplement
Basic Statistics from the World Bank's World Development Indicators, 2002
By: David A. Moss and Sarah A. Brennan
Supplements National Economic Accounting: Past, Present, and Future. View Details
- January 2000
- Supplement
Basic Statistics from the World Bank's World Development Report 1998/1999
By: Julio J. Rotemberg
Supplements National Income Accounting and The Origins of National Income Accounting. View Details
- 2016
- Article
Penalized Fast Subset Scanning
By: Skyler Speakman, Sriram Somanchi, Edward McFowland III and Daniel B. Neill
We present the penalized fast subset scan (PFSS), a new and general framework for scalable and accurate pattern detection. PFSS enables exact and efficient identification of the most anomalous subsets of the data, as measured by a likelihood ratio scan statistic.... View Details
Keywords: Disease Surveillance; Likelihood Ratio Statistic; Pattern Detection; Scan Statistic; Mathematical Methods
Speakman, Skyler, Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. "Penalized Fast Subset Scanning." Journal of Computational and Graphical Statistics 25, no. 2 (2016): 382–404. (Selected for “Best of JCGS” invited session by the journal’s editor in chief.)
- 2025
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
- Teaching Interest
Overview
I served as a Teaching Fellow for the Applied Business Analytics second-year MBA course. This course sought to teach MBA students how businesses can improve their strategic decisions using statistics and machine learning techniques. (e.g., regression models, random... View Details
- August 2015 (Revised January 2017)
- Technical Note
From Correlation to Causation
By: Feng Zhu and Karim R. Lakhani
To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes... View Details
Zhu, Feng, and Karim R. Lakhani. "From Correlation to Causation." Harvard Business School Technical Note 616-009, August 2015. (Revised January 2017.)
- February 2021
- Tutorial
Assessing Prediction Accuracy of Machine Learning Models
By: Michael Toffel and Natalie Epstein
This video describes how to assess the accuracy of machine learning prediction models, primarily in the context of machine learning models that predict binary outcomes, such as logistic regression, random forest, or nearest neighbor models. After introducing and... View Details
- Teaching Interest
Overview
Graduate student instructor, Introduction to Statistics, 2002
Reader, Introduction to Time Series, 2003
Reader, Introductory Probability Theory, 2001 View Details
Reader, Introduction to Time Series, 2003
Reader, Introductory Probability Theory, 2001 View Details
- 2015
- Chapter
Communicating Statistics in the Context of Banking Union – A Macro User's Perspective
By: Jan Kozak and Huw Pill
Kozak, Jan, and Huw Pill. "Communicating Statistics in the Context of Banking Union – A Macro User's Perspective." Chap. 9 in Towards the Banking Union: Opportunities and Challenges for Statistics, 155–162. Frankfurt: European Central Bank, 2015.
- September 2009
- Article
A Detailed Analysis of the Reduction Mammaplasty Learning Curve: A Statistical Process Model for Approaching Surgical Performance Improvement
By: Matthew Carty MD, Rodney Chan, Robert S. Huckman, Daniel C. Snow and Dennis Orgill
Background: The increased focus on quality and efficiency improvement within academic surgery has met with variable success among plastic surgeons. Traditional surgical performance metrics, such as morbidity and mortality, are insufficient to improve the... View Details
Keywords: Experience and Expertise; Health Care and Treatment; Medical Specialties; Outcome or Result; Performance Efficiency; Performance Improvement
Carty, Matthew, MD, Rodney Chan, Robert S. Huckman, Daniel C. Snow, and Dennis Orgill. "A Detailed Analysis of the Reduction Mammaplasty Learning Curve: A Statistical Process Model for Approaching Surgical Performance Improvement." Plastic and Reconstructive Surgery 124, no. 3 (September 2009): 706–714.
- Article
On Market Timing and Investment Performance Part II: Statistical Procedures for Evaluating Forecasting Skills
By: Robert C. Merton and Roy D. Henriksson
Merton, Robert C., and Roy D. Henriksson. "On Market Timing and Investment Performance Part II: Statistical Procedures for Evaluating Forecasting Skills." Journal of Business 54, no. 4 (October 1981): 513–533.
- 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.
- March 2011 (Revised April 2021)
- Case
The Whiz Kids
By: Tom Nicholas and David Chen
In October 1945, Henry Ford II received a telegram in his office at the Ford Motor Company in Dearborn, Michigan written by Charles "Tex" Thornton, a U.S. Air Force colonel. The telegram presented an opportunity for Ford to deploy a system of statistical control which... View Details
Keywords: Ford Motor Company; Statistical Control; Management Systems; Accounting; Operations; Strategy; Mathematical Methods; Auto Industry; United States
Nicholas, Tom, and David Chen. "The Whiz Kids." Harvard Business School Case 811-042, March 2011. (Revised April 2021.)
- 2011
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
- 2013
- Book
Keeping Up with the Quants: Your Guide to Understanding and Using Analytics
By: Thomas H. Davenport and Jinho Kim
Managers today need to be able to analyze and make sense of data. They need to be conversant with analytical technology and methods and to make decisions on quantitative analysis. This book offers a variety of practical tools and examples to improve a manager's... View Details
- 2015
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
Speakman, Skyler, Edward McFowland III, and Daniel B. Neill. "Scalable Detection of Anomalous Patterns With Connectivity Constraints." Journal of Computational and Graphical Statistics 24, no. 4 (2015): 1014–1033.
- 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.
- Article
Fast Subset Scan for Multivariate Spatial Biosurveillance
By: Daniel B. Neill, Edward McFowland III and Huanian Zheng
We present new subset scan methods for multivariate event detection in massive space-time datasets. We extend the recently proposed 'fast subset scan' framework from univariate to multivariate data, enabling computationally efficient detection of irregular space-time... View Details
Neill, Daniel B., Edward McFowland III, and Huanian Zheng. "Fast Subset Scan for Multivariate Spatial Biosurveillance." Statistics in Medicine 32, no. 13 (June 15, 2013): 2185–2208.