Zongming Ma

Zongming Ma
  • Associate Professor of Statistics and Data Science
  • Statistics PhD Coordinator for Enrolled Students

Contact Information

  • office Address:

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

Research Interests: high-dimensional statistics, nonparametric statistics, network data analysis, statistical methods in genomics and imaging.

Links: Personal Website

Overview

Education

PhD, Stanford University, 2010
BS, Peking University, 2005.

Academic Positions Held

Wharton: 2010-present

For more information, go to My Personal Page

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Research

Teaching

Current Courses (Fall 2022)

  • STAT4310 - Statistical Inference

    Graphical displays; one- and two-sample confidence intervals; one- and two-sample hypothesis tests; one- and two-way ANOVA; simple and multiple linear least-squares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodness-of-fit tests. A methodology course. This course does not have business applications but has significant overlap with STAT 1010 and 1020. This course may be taken concurrently with the prerequisite with instructor permission.

    STAT4310002 ( Syllabus )

    STAT4310001 ( Syllabus )

All Courses

  • 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.

  • STAT3990 - Independent Study

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

  • STAT4310 - Statistical Inference

    Graphical displays; one- and two-sample confidence intervals; one- and two-sample hypothesis tests; one- and two-way ANOVA; simple and multiple linear least-squares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodness-of-fit tests. A methodology course. This course does not have business applications but has significant overlap with STAT 1010 and 1020. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT4320 - Mathematical Statistics

    An introduction to the mathematical theory of statistics. Estimation, with a focus on properties of sufficient statistics and maximum likelihood estimators. Hypothesis testing, with a focus on likelihood ratio tests and the consequent development of "t" tests and hypothesis tests in regression and ANOVA. Nonparametric procedures. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT5150 - Adv Stat Inference I

    STAT 5150 is aimed at first-year Ph.D. students and builds a good foundation in statistical inference from the first principles of probability.

  • STAT9250 - Multivariate Analy: Theo

    This is a course that prepares PhD students in statistics for research in multivariate statistics and high dimensional statistical inference. Topics from classical multivariate statistics include the multivariate normal distribution and the Wishart distribution; estimation and hypothesis testing of mean vectors and covariance matrices; principal component analysis, canonical correlation analysis and discriminant analysis; etc. Topics from modern multivariate statistics include the Marcenko-Pastur law, the Tracy-Widom law, nonparametric estimation and hypothesis testing of high-dimensional covariance matrices, high-dimensional principal component analysis, etc.

  • STAT9710 - Intro To Linear Stat Mod

    Theory of the Gaussian Linear Model, with applications to illustrate and complement the theory. Distribution theory of standard tests and estimates in multiple regression and ANOVA models. Model selection and its consequences. Random effects, Bayes, empirical Bayes and minimax estimation for such models. Generalized (Log-linear) models for specific non-Gaussian settings.

  • 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.

Awards and Honors

  • Wharton Teaching Excellence Award, 2020
  • Alfred P. Sloan Research Fellowship, 2016
  • NSF CAREER Award, 2014

Activity

Latest Research

Chao Gao and Zongming Ma (2022), Testing equivalence of clustering, The Annals of Statistics, 50, pp. 407-429.
All Research