Richard A. Berk

Richard A. Berk
  • Professor Emeritus of Criminology

Contact Information

  • office Address:

    483 McNeil Building, 3718 Locust Walk, Philadelphia, PA 19104

Research Interests: applied statistics, causal inference, forecasting, statistical/machine learning

Links: CV

Overview

Education

PhD, The Johns Hopkins University, 1970; BA, Yale University, 1964

Recent Consulting

Philadelphia Adult Department of Probation and Parole; Pennsylvania Board of Probation and Parole; Maryland Department of Public Safety and Correctional Services; Washington, D.C. Police Department; Child Protective Services, Maryland Department of Human Resources; United States District Court for the Eastern District of California; U.S. Bureau of Justice Statistics; Philadelphia Police Department

Career and Recent Professional Awards; Teaching Awards

Elected to the Sociological Research Association; Elected Fellow to the American Association for the Advancement of Science; Paul S. Lazarsfeld Award for methodological contributions from the American Sociological Association; Elected Fellow of the American Statistical Association; Elected Fellow of the Academy of Experimental Criminology

Academic Positions Held

Wharton: 2006-present. University of Pennsylvania:2006-present. Previous appointments: University of California, Los Angles; University of California, Santa Barbara; Northwestern University. Visiting appointments: Ecole Normale Supérieure, Paris, France; Los Alamos National Laboratories, Statistics Group

Professional Leadership 2005-2012

Editor, The Evaluation Review

Corporate and Public Sector Leadership 2005-2012

National Research Council Panel on the Design of the 2010 Census Program of Evaluations and Experiments (CPEX)

For more information, go to My Personal Page

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Research

Teaching

Past Courses

  • CRIM4740 - Modern Regression

    Function estimation and data exploration using extensions of regression analysis: smoothers, semiparametric and nonparametric regression, and supervised machine learning. Conceptual foundations are addressed as well as hands-on use for data analysis. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT4740 - Modern Regression

    Function estimation and data exploration using extensions of regression analysis: smoothers, semiparametric and nonparametric regression, and supervised machine learning. Conceptual foundations are addressed as well as hands-on use for data analysis. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT9740 - Modern Regression

    Function estimation and data exploration using extensions of regression analysis: smoothers, semiparametric and nonparametric regression, and supervised machine learning. Conceptual foundations are addressed as well as hands-on use for data analysis.

In the News

Knowledge @ Wharton

Activity

Latest Research

Richard A. Berk, Andreas Buja, Lawrence D. Brown, Edward I. George, Arun Kumar Kuchibhotla, Weijie Su, Linda Zhao (2020), Assumption Lean Regression, American Statistician, (in press) ().
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In the News

How Dynamic Electricity Pricing Can Improve Market Efficiency

New research co-authored by Wharton's Arthur van Benthem demonstrates how consumers could benefit from aligning electricity prices with the cost of producing and distributing that power.…Read More

Knowledge @ Wharton - 2024/11/12
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