Warren Ewens

Warren Ewens
  • Professor Emeritus of Biology

Contact Information

  • office Address:

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

Teaching

Past Courses

  • BIOL3999 - Independent Study

    Laboratory research with a faculty member in the Department of Biology. Research may also be conducted elsewhere on campus but co-sponsored by a faculty member in Biology. A final paper is required. Apply at the Biology Academic Office, 102 Leidy Labs.

  • BIOL4999 - Adv. Independent Study

    A second semester of independent study, in most cases extending the research undertaken for the BIOL 3999. Apply at the Biology Academic Office, 102 Leidy Labs.

  • GCB7990 - Independent Study

    Independent study course

  • 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.

  • 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.

  • STAT5120 - 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.

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Inside Time’s Best Inventions and Innovation Selection Process

Editorial director at Time explains how influential innovations are evaluated, selected, and celebrated for real-world impact.…Read More

Knowledge @ Wharton - 2025/12/18
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