Edward I. George

Edward I. George
  • Universal Furniture Professor
  • Professor of Statistics

Contact Information

  • office Address:

    446 Jon M. Huntsman Hall
    3730 Walnut St.
    Philadelphia, PA 19104

Research Interests: hierarchical modeling, model uncertainty, shrinkage estimation, treed modeling, variable selection, wavelet regression

Links: CV

Overview

Education

PhD, Stanford University, 1981
MS, SUNY at Stony Brook, 1976
AB, Cornell University, 1972

Career and Recent Professional Awards

Elected Fellow of the International Society for Bayesian Analysis (2014); Elected Fellow  of the American Statistical Association (1997); Elected Fellow of the Institute of Mathematical Statistics (1995).
CBA Foundation Award for Outstanding Research Contributions (1998) and the CBA Foundation Award for Research Excellence (1995), The University of Texas at Austin.
Excellence in Education Award (2001) and the Joe D. Beasley Award for Teaching Excellence (1996), The University of Texas at Austin
McKinsey Award for Excellence in Teaching (1987) and the Emory Williams Award for Excellence in Teaching (1987), The University of Chicago.

Academic Positions Held

Wharton: 2001-present (Chairperson, Statistics Department, 2008-2014; named Universal Furniture Professor, 2002)
Previous appointment: University of Texas at Austin, University of Chicago.
Visiting Appointments: Cambridge University; University of Paris; University of Valencia

Professional Leadership

Editor, Annals of Statistics, 2016-2018; Executive Editor, Statistical Science, 2004-2007.

For more information, go to My Personal Page

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Research

Teaching

Past Courses

  • STAT613 - REGR ANALYSIS FOR BUS

    This course provides the fundamental methods of statistical analysis, the art and science if extracting information from data. The course will begin with a focus on the basic elements of exploratory data analysis, probability theory and statistical inference. With this as a foundation, it will proceed to explore the use of the key statistical methodology known as regression analysis for solving business problems, such as the prediction of future sales and the response of the market to price changes. The use of regression diagnostics and various graphical displays supplement the basic numerical summaries and provides insight into the validity of the models. Specific important topics covered include least squares estimation, residuals and outliers, tests and confidence intervals, correlation and autocorrelation, collinearity, and randomization. The presentation relies upon computer software for most of the needed calculations, and the resulting style focuses on construction of models, interpretation of results, and critical evaluation of assumptions.

  • STAT621 - ACC REGRESSION ANALYSIS

    STAT 621 is intended for students with recent, practical knowledge of the use of regression analysis in the context of business applications. This course covers the material of STAT 613, but omits the foundations to focus on regression modeling. The course reviews statistical hypothesis testing and confidence intervals for the sake of standardizing terminology and introducing software, and then moves into regression modeling. The pace presumes recent exposure to both the theory and practice of regression and will not be accommodating to students who have not seen or used these methods previously. The interpretation of regression models within the context of applications will be stressed, presuming knowledge of the underlying assumptions and derivations. The scope of regression modeling that is covered includes multiple regression analysis with categorical effects, regression diagnostic procedures, interactions, and time series structure. The presentation of the course relies on computer software that will be introduced in the initial lectures.

Awards and Honors

  • Fellow, International Society for Bayesian Analysis, 2014
  • Challis Lecturer and Award for Outstanding Contributions to Statistics, University of Florida, 2012
  • Geisser Distinguished Lecturer, University of Minnesota, 2012
  • Palmetto Lecturer, University of South Carolina, 2012
  • Loeb Lecturer, Washington University in St. Louis, 2011
  • Medallion Lecturer, Institute of Mathematical Statistics, 2010
  • Hartley Memorial Lecturer, Texas A&M University, 2007
  • Excellence in Education Award, The University of Texas at Austin, 2001
  • Lawrence Baxter Memorial Lecturer, SUNY at Stony Brook, 1998
  • CBA Foundation Award for Outstanding Research Contributions, The University of Texas at Austin, 1998
  • Fellow, American Statistical Association, 1997
  • Member, International Statistical Institute, 1996
  • Joe D. Beasley Award for Teaching Excellence, The University of Texas at Austin, 1996
  • Fellow, Institute of Mathematical Statistics, 1995
  • CBA Foundation Award for Research Excellence, The University of Texas at Austin, 1995
  • McKinsey Award for Excellence in Teaching, The University of Chicago, 1987
  • The Emory Williams Award for Excellence in Teaching, The University of Chicago, 1987

In the News

Knowledge @ Wharton

Activity

In the News

‘Every Time a Bell Rings …’

It’s a Wonderful Life is a Christmas classic, but Wharton statistics professor Edward George says it should also be required viewing for business leaders.

Knowledge @ Wharton - 2013/04/8
All News

Awards and Honors

Fellow, International Society for Bayesian Analysis 2014
All Awards