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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

Keywords: Algorithms; Disease Surveillance; Event Detection; Scan Statistics; Spatial Scan

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March 2022 (Revised January 2025)
Technical Note

Exploratory Data Analysis

By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton

This module note provides an overview of exploratory data analysis for an introduction to data science course. It begins by defining the term "data", and then describes the different types of data that companies work with (structured v. unstructured, categorical v.... View Details

Keywords: Data Analysis; Data Science; Statistics; Data Visualization; Exploratory Data Analysis; Analytics and Data Science; Analysis

2016
Article

Does volunteering improve well-being?

By: A.V. Whillans, Scott C. Seider, Lihan Chen, Ryan J. Dwyer, Sarah Novick, Kathryn J. Gramigna, Brittany A. Mitchell, Victoria Savalei, Sally S. Dickerson and Elizabeth W. Dunn

Does volunteering causally improve well-being? To empirically test this question, we examined one instantiation of volunteering that is common at post-secondary institutions across North America: community service learning (CSL). CSL is a form of experiential learning... View Details

Keywords: Prosocial Behavior; College Students; Bayesian Statistics; Education; Well-being

2022
Article

Nonparametric Subset Scanning for Detection of Heteroscedasticity

By: Charles R. Doss and Edward McFowland III

We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning... View Details

Keywords: Scan Statistics; Anomaly Detection; Regression; Model Diagnostics

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March 2020
Article

Is This My Group or Not? The Role of Ensemble Coding of Emotional Expressions in Group Categorization

By: Amit Goldenberg, Timothy D. Sweeny, Emmanuel Shpigel and James J. Gross

When exposed to others’ emotional responses, people often make rapid decisions as to whether these others are members of their group or not. These group categorization decisions have been shown to be extremely important to understanding group behavior. Yet, despite... View Details

Keywords: Categorization; Ensemble Coding; Summary Statistical Perception; Social Cognition; Emotions; Perception; Groups and Teams

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August 2021
Article

Multiple Imputation Using Gaussian Copulas

By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use... View Details

Keywords: Missing Data; Bayesian Statistics; Imputation; Categorical Data; Estimation

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August 2020 (Revised September 2020)
Technical Note

Assessing Prediction Accuracy of Machine Learning Models

By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne

The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details

Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods

July–August 2024
Article

Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals

By: Ta-Wei Huang and Eva Ascarza

Firms are increasingly interested in developing targeted interventions for customers with the best response, which requires identifying differences in customer sensitivity, typically through the conditional average treatment effect (CATE) estimation. In theory, to... View Details

Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy

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Article

Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error

By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III

Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details

Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science

29 Aug 2022
Op-Ed

Income Inequality Is Rising. Are We Even Measuring It Correctly?

finding ways to reduce inequality to create a more just and equal society for all. In making decisions on how to best intervene, policymakers commonly rely on the Gini coefficient, a statistical measure of resource distribution, including... View Details

Keywords: by Jon M. Jachimowicz, Kristin Blesch, and Oliver P. Hauser

November 2018
Case

Sportradar (A): From Data to Storytelling

By: Ramon Casadesus-Masanell, Karen Elterman and Oliver Gassmann

In 2013, the Swiss sports data company Sportradar debated whether to expand from its core business of data provision to bookmakers into sports media products. Sports data was becoming a commodity, and in the future, sports leagues might reduce their dependence on... View Details

February 1986 (Revised June 2007)
Background Note

Constructing and Using Process Control Charts

Summarizes how to construct and use statistical process control charts. Gives several examples. Discusses tolerances using control charts for debugging. View Details

Keywords: Production; Analysis

July 1994 (Revised May 1995)
Background Note

Note on Retail Economics

By: David E. Bell

Reviews some elementary statistics on financial ratios that are commonly used to evaluate retailing companies. View Details

Keywords: Economics; Retail Industry

Research Summary

Models of Industry Evolution

Through a series of large-scale statistical studies and case studies on specific industries, Anita M. McGahan is developing a framework for evaluating industry evolution. Her work has generated a number of statistical studies, several co-authored with Michael E.... View Details

Article

Learning from Potentially Biased Statistics: Household Inflation Perceptions and Expectations in Argentina

By: Alberto Cavallo, Guillermo Cruces and Ricardo Perez-Truglia

When forming expectations, households may be influenced by perceived bias in the information they receive. In this paper, we study how individuals learn from potentially biased statistics using data from both a natural experiment and a survey experiment during a... View Details

Keywords: Inflation Expectations; Bayesian Estimation; Inflation and Deflation; Information; Household; Behavior; Argentina

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May 2013 (Revised July 2014)
Background Note

Private Equity Exits

By: Paul A. Gompers and Timothy Dore

This note presents statistics on private equity exits and discusses important issues relating to the most common exit routes. View Details

Keywords: Private Equity

April 2013 (Revised October 2013)
Case

Google's Project Oxygen: Do Managers Matter?

By: David A. Garvin, Alison Berkley Wagonfeld and Liz Kind

Google's Project Oxygen started with a fundamental question raised by executives in the early 2000s: do managers matter? The topic generated a multi-year research project that ultimately led to a comprehensive program, built around eight key management attributes,... View Details

Keywords: Organizational Behavior; Business Policy; General Management; Human Resource Management; Management; Leadership; Human Resources

September 1986 (Revised February 1990)
Background Note

A Note on Quality: The Views of Deming, Juran, and Crosby

By: David A. Garvin

Describes the three distinct approaches to quality management represented by W. Edwards Deming, Joseph Juran, and Philip B. Crosby. Designed to introduce students to the elements of statistical quality control, structured approaches to quality improvement, and zero... View Details

Keywords: Quality; Performance Improvement; Mathematical Methods

2014
Working Paper

De Gustibus non est Taxandum: Heterogeneity in Preferences and Optimal Redistribution

By: Benjamin B Lockwood and Matthew Weinzierl

The prominent but unproven intuition that preference heterogeneity reduces redistribution in a standard optimal tax model is shown to hold under the plausible condition that the distribution of preferences for consumption relative to leisure rises, in terms of... View Details

Keywords: Spending; Policy; Taxation; Theory; United States

September 1974 (Revised April 1975)
Case

Ocean Spray Cranberries, Inc. (B)

A consumer attitude survey involving more than 1,000 cranberry users has been conducted. Multivariate statistical procedures including factor analysis, cluster analysis and multiple discriminant analysis have been employed to suggest four attitude segments in the... View Details

Keywords: Surveys; Product Positioning; Mathematical Methods; Consumer Behavior; Agriculture and Agribusiness Industry; Food and Beverage Industry

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