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Show Results For
- All HBS Web
(1,124)
- People (1)
- News (163)
- Research (613)
- Events (17)
- Multimedia (5)
- Faculty Publications (369)
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- March 2022 (Revised July 2022)
- Technical Note
Statistical Inference
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 July 2022.)
- 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 1990 (Revised August 1996)
- Background Note
Sampling and Statistical Inference
An introduction to sampling and statistical inference that covers the main concepts (confidence intervals, tests of statistical significance, choice of sample size) that are needed in making inferences about a population mean or percent. Includes discussion of problems... View Details
Schleifer, Arthur, Jr. "Sampling and Statistical Inference." Harvard Business School Background Note 191-092, November 1990. (Revised August 1996.)
- 2022
- Working Paper
Stories, Statistics and Memory
By: Thomas Graeber, Christopher Roth and Florian Zimmermann
For most decisions, we rely on information encountered over the course of days,
months or years. We consume this information in various forms, including abstract
summaries of multiple data points – statistics – and contextualized anecdotes about
individual instances... View Details
Graeber, Thomas, Christopher Roth, and Florian Zimmermann. "Stories, Statistics and Memory." Working Paper, December 2022.
- Research Summary
Statistical Methodology
William Simpson is developing methods of inference to use when assumptions of standard models are not met. He has created a hypothesis test to use for ipsative variables that adjusts for the non-zero correlations among variables expected under the null hypothesis. ... View Details
- October 1998
- Background Note
Welfare-to-Work Information and Statistics
By: Rosabeth M. Kanter and Ellen Pruyne
Summarizes information on the national issue of hiring people from the welfare roles. Organized by topics relevant to business, this note reviews research findings and statistics and poses questions to assist business decision-makers in assessing a company's current or... View Details
Keywords: Decision Choices and Conditions; Recruitment; Risk Management; Planning; Programs; Research; Welfare
Kanter, Rosabeth M., and Ellen Pruyne. "Welfare-to-Work Information and Statistics." Harvard Business School Background Note 399-064, October 1998.
- 2023
- Working Paper
How People Use Statistics
By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis... View Details
Bordalo, Pedro, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon, and Andrei Shleifer. "How People Use Statistics." NBER Working Paper Series, No. 31631, August 2023.
- Article
Statistical Physics of Human Cooperation
By: Matjaž Perc, Jillian J. Jordan, David G. Rand, Zhen Wang, Stefano Boccaletti and Attila Szolnoki
Extensive cooperation among unrelated individuals is unique to humans, who often sacrifice personal benefits for the common good and work together to achieve what they are unable to execute alone. The evolutionary success of our species is indeed due, to a large... View Details
Keywords: Human Cooperation; Evolutionary Game Theory; Public Goods; Reward; Punishment; Tolerance; Self-organization; Pattern Formation; Cooperation; Behavior; Game Theory
Perc, Matjaž, Jillian J. Jordan, David G. Rand, Zhen Wang, Stefano Boccaletti, and Attila Szolnoki. "Statistical Physics of Human Cooperation." Physics Reports 687 (May 8, 2017): 1–51.
- 2015
- Chapter
Negotiations: Statistical Aspects
'Negotiation analysis' seeks to develop prescriptive theory and useful advice for negotiators and third parties. It generally emphasizes the parties' underlying interests, alternatives to negotiated agreement, approaches to productively manage the inherent tension... View Details
Sebenius, James K. "Negotiations: Statistical Aspects." In International Encyclopedia of the Social & Behavioral Sciences. 2nd ed. Edited by James D. Wright, 430–436. London: Elsevier, 2015.
- August 2005 (Revised April 2008)
- Teaching Note
Store24 (B): Statistics Review with Data Desk (TN)
By: Frances X. Frei
Presents an overview of the statistical analysis covered in the case discussion. View Details
- February 2005 (Revised November 2006)
- Background Note
Using Data Desk for Statistical Analysis
By: Frances X. Frei and Dennis Campbell
Describes how to use the Data Desk software package to perform statistical analysis. View Details
Keywords: Mathematical Methods
Frei, Frances X., and Dennis Campbell. "Using Data Desk for Statistical Analysis." Harvard Business School Background Note 605-060, February 2005. (Revised November 2006.)
- April 1984 (Revised November 1988)
- Background Note
Statistical Quality Control for Process Improvement
Describes systematic methods for process debugging and improvement, based on statistical quality control. Examples are from manufacturing settings, but techniques are also useful for services and sales, and to quantity improvement as well as quality improvement. View Details
Bohn, Roger E. "Statistical Quality Control for Process Improvement." Harvard Business School Background Note 684-068, April 1984. (Revised November 1988.)
- August 2005 (Revised April 2008)
- Teaching Note
Store24 (A): Statistics Review with Data Desk (TN)
By: Frances X. Frei
Presents an overview of the statistical analysis covered in the case discussion. View Details
- August 2005 (Revised April 2008)
- Teaching Note
GuestFirst Hotel (B): Statistics Review with Data Desk (TN)
By: Frances X. Frei
Presents an overview of the statistical analysis covered in the case discussion. View Details
- 2008
- Book
Introduction to Statistical Decision Theory
By: John W. Pratt, Howard Raiffa and Robert Schlaifer
- 1995
- Book
Introduction to Statistical Decision Theory
By: John W. Pratt, Howard Raiffa and Robert Schlaifer
Pratt, John W., Howard Raiffa, and Robert Schlaifer. Introduction to Statistical Decision Theory. MIT Press, 1995.
- August 2005 (Revised April 2008)
- Teaching Note
GuestFirst Hotel (A): Statistics Review with Data Desk (TN)
By: Frances X. Frei
Presents an overview of the statistical analysis covered in the case discussion. View Details
Keywords: Mathematical Methods
- January 2024
- Article
Subset Scanning for Multi-Trait Analysis Using GWAS Summary Statistics
By: Rui Cao, Evan Olawsky, Edward McFowland III, Erin Marcotte, Logan Spector and Tianzhong Yang
Multi-trait analysis has been shown to have greater statistical power than single-trait analysis. Most of the existing multi-trait analysis methods only work with a limited number of traits and usually prioritize high statistical power over identifying relevant traits,... View Details
Cao, Rui, Evan Olawsky, Edward McFowland III, Erin Marcotte, Logan Spector, and Tianzhong Yang. "Subset Scanning for Multi-Trait Analysis Using GWAS Summary Statistics." Bioinformatics 40, no. 1 (January 2024).