Dean P. Foster

Dean P. Foster
  • Marie and Joseph Melone Professor Emeritus of Statistics

Contact Information

  • office Address:

Research Interests: machine learning, statistical nlp., variable selection

Links: Personal Website



PhD, University of Maryland, 1988
MSc, Rutgers University, 1984
MA, University of Maryland, 1982
BSc, University of Maryland, 1980

Academic Positions Held

Wharton: 1992-present (named William H. Lawrence Professor, 2007).
Previous appointment: University of Chicago.

For more information, go to My Personal Page

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All Courses

  • STAT3990 - Independent Study

    Written permission of instructor and the department course coordinator required to enroll in this course.

  • STAT4710 - Modern Data Mining

    With the advent of the internet age, data are being collected at unprecedented scale in almost all realms of life, including business, science, politics, and healthcare. Data mining—the automated extraction of actionable insights from data—has revolutionized each of these realms in the 21st century. The objective of the course is to teach students the core data mining skills of exploratory data analysis, selecting an appropriate statistical methodology, applying the methodology to the data, and interpreting the results. The course will cover a variety of data mining methods including linear and logistic regression, penalized regression (including lasso and ridge regression), tree-based methods (including random forests and boosting), and deep learning. Students will learn the conceptual basis of these methods as well as how to apply them to real data using the programming language R. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT7010 - Modern Data Mining

    Modern Data Mining: Statistics or Data Science has been evolving rapidly to keep up with the modern world. While classical multiple regression and logistic regression technique continue to be the major tools we go beyond to include methods built on top of linear models such as LASSO and Ridge regression. Contemporary methods such as KNN (K nearest neighbor), Random Forest, Support Vector Machines, Principal Component Analyses (PCA), the bootstrap and others are also covered. Text mining especially through PCA is another topic of the course. While learning all the techniques, we keep in mind that our goal is to tackle real problems. Not only do we go through a large collection of interesting, challenging real-life data sets but we also learn how to use the free, powerful software "R" in connection with each of the methods exposed in the class. Prerequisite: two courses at the statistics 4000 or 5000 level or permission from instructor.

  • STAT9910 - Sem in Adv Appl of Stat

    This seminar will be taken by doctoral candidates after the completion of most of their coursework. Topics vary from year to year and are chosen from advance probability, statistical inference, robust methods, and decision theory with principal emphasis on applications.

  • STAT9950 - Dissertation

  • STAT9990 - Independent Study

    Written permission of instructor and the department course coordinator required to enroll.

In the News


In the News

Gaming the System: Are Hedge Fund Managers Talented, or Just Good at Fooling Investors?

Hedge funds are key players in the world's financial markets, but no one knows exactly what they're up to. Critics and supporters tend to share an assumption, however, that hedge funds are run by talented people who merit their hefty management fees. But new research by Wharton statistics professor Dean P. Foster and Brookings Institution senior fellow H. Peyton Young questions that idea, arguing that it's easy for hedge funds to fool their investors into believing the managers are better than they really are. The industry "risks being inundated by managers who are gaming the system ... which could ultimately lead to a collapse in investor confidence," they say.Read More

Knowledge at Wharton - 4/2/2008
All News

Wharton Magazine

Final Exam

Suppose you put the following ten letters—S, T, A, T, I, S, T, I, C and S—in a bag.

Wharton Magazine - 04/01/2011