Shane T. Jensen

Shane T. Jensen
  • Professor of Statistics and Data Science

Contact Information

  • office Address:

    415 Academic Research Building
    265 South 37th Street
    Philadelphia, PA 19104

Research Interests: bayesian multi-level modeling, spatial statistics, urban analytics, statistics in sports

Links: CV

Overview

Education

PhD, Harvard University, 2004
AM, Harvard University, 2001
MS, McGill University, 1999
BS, McGill University, 1997

Career and Recent Professional Awards

Savage Award for best thesis, International Society for Bayesian Analysis (2005)
David W. Hauck Award for Outstanding Teaching (2009)
Sports in Statistics Award, American Statistical Association (2011)
JASA Reproducibility Award, American Statistical Association (2023)

Academic Positions Held

Wharton: 2004-present

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Research

Teaching

Past Courses

  • GCB9950 - Dissertation

    Ph.D. students enroll in this course after passing their candidacy exam. They work on their dissertation full-time under the guidance of their dissertation supervisor and other members of their dissertation committee.

  • STAT1020 - Intro Business Stat

    Continuation of STAT 1010 or STAT 1018. A thorough treatment of multiple regression, model selection, analysis of variance, linear logistic regression; introduction to time series. Business applications. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT1110 - Introductory Statistics

    Introduction to concepts in probability. Basic statistical inference procedures of estimation, confidence intervals and hypothesis testing directed towards applications in science and medicine. The use of the JMP statistical package. Knowledge of high school algebra is required for this course.

  • STAT3990 - Independent Study

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

  • STAT4420 - Intro Bayes Data Analys

    The course will introduce data analysis from the Bayesian perspective to undergraduate students. We will cover important concepts in Bayesian probability modeling as well as estimation using both optimization and simulation-based strategies. Key topics covered in the course include hierarchical models, mixture models, hidden Markov models and Markov Chain Monte Carlo. A course in probability (STAT 4300 or equivalent); a course in statistical inference (STAT 1020, STAT 1120, STAT 4310 or equivalent); and experience with the statistical software R (at the level of STAT 4050 or STAT 4700) are recommended.

  • STAT5420 - Bayesian Meth & Comp

    Sophisticated tools for probability modeling and data analysis from the Bayesian perspective. Hierarchical models, mixture models and Monte Carlo simulation techniques.

  • STAT8990 - Independent Study

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

  • STAT9270 - Bayesian Statistics

    This graduate course will cover the modeling and computation required to perform advanced data analysis from the Bayesian perspective. We will cover fundamental topics in Bayesian probability modeling and implementation, including recent advances in both optimization and simulation-based estimation strategies. Key topics covered in the course include hierarchical and mixture models, Markov Chain Monte Carlo, hidden Markov and dynamic linear models, tree models, Gaussian processes and nonparametric Bayesian strategies.

  • STAT9950 - Dissertation

    Dissertation

  • STAT9990 - Independent Study

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

Awards And Honors

  • JASA Reproducibility Award, 2023 Description

    American Statistical Association

  • Wharton Undergraduate Teaching Excellence Award, 2021
  • Wharton Teaching Excellence Award, 2020
  • Wharton Teaching Excellence Award, 2019
  • SABR Analytics Conference Research Award in Contemporary Baseball Analysis, 2016 Description

    for the paper “OpenWAR: an open source system for evaluating overall player performance in major league baseball.”

  • Sports in Statistics Award for Contributions to the Statistics in Sports Community, American Statistical Association, 2011
  • David W. Hauck Award for Excellence in Undergraduate Teaching, The Wharton School, 2009
  • Leonard J. Savage Award for best thesis in Application Methodology from the International Society for Bayesian Analysis, 2005

Activity

Latest Research

Desen Lin, Shane T. Jensen, Susan Wachter (2023), The price effects of greening vacant lots: how neighborhood attributes matter, Real Estate Economics, 51 (), pp. 573-610.
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In the News

Building Stronger Family Offices by Sharing Knowledge and Securing the Future

Wharton management professor discusses the objectives and key takeaways of the Wharton Global Family Alliance’s 2024 Family Office Survey.Read More

Knowledge @ Wharton - 2024/11/21
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Awards and Honors

JASA Reproducibility Award 2023
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