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Vance, Eric

Associate Professor

Positions

Research Areas research areas

Research

research overview

  • Eric Vance researches the micro- and macro-theory of statistics and data science collaboration. He innovates better ways to teach data science by integrating the humanities and employing best practices in team-based learning pedagogy. He supports research throughout the sciences, engineering, and the humanities by providing bespoke solutions to researchers' data science and statistical needs.

keywords

  • statistical collaboration, data science, statistical applications, professional skills, pedagogy

Publications

selected publications

Teaching

courses taught

  • AHUM 1825 - Inclusive Interdisciplinary Data Science for All
    Primary Instructor - Fall 2021 / Fall 2022
    Team-taught module-based course merges data science and the humanities without requiring prior experience in either one. Students will synthesize qualitative and quantitative approaches to urgent research questions and practice putting data to work in the world. They will learn to use data analysis, statistics, and basic programming skills to answer questions of human importance, while applying the central humanities skills of source critique, attention to human motives, contextualization, and argument.
  • APPM 1360 - Calculus 2 for Engineers
    Primary Instructor - Spring 2021
    Continuation of APPM 1350. Focuses on applications of the definite integral, methods of integration, improper integrals, Taylor's theorem, and infinite series. Degree credit not granted for this course and MATH 2300.
  • APPM 2720 - Open Topics in Lower Division Applied Mathematics
    Primary Instructor - Spring 2018
    Provides a vehicle for the development and presentation of new topics that are accessible to lower division Applied Mathematics students. These topics have the potential to be incorporated into the core APPM curriculum. May be repeated up to 6 total credit hours.
  • APPM 4500 - Statistical Collaboration
    Primary Instructor - Spring 2018 / Fall 2018 / Spring 2019 / Fall 2019
    Educates and trains students to become effective interdisciplinary collaborators by developing the communication and collaboration skills necessary to apply technical statistics and data science skills to help domain experts answer research questions. Topics include structuring effective meetings and projects; communicating statistics to non-statisticians; using peer feedback, self-reflection and video analysis to improve collaboration skills; creating reproducible statistical workflows; working ethically. Same as STAT 5680.
  • APPM 5500 - Statistical Collaboration
    Primary Instructor - Spring 2018 / Fall 2018 / Spring 2019 / Fall 2019
    Educates and trains students to become effective interdisciplinary collaborators by developing the communication and collaboration skills necessary to apply technical statistics and data science skills to help domain experts answer research questions. Topics include structuring effective meetings and projects; communicating statistics to non-statisticians; using peer feedback, self-reflection and video analysis to improve collaboration skills; creating reproducible statistical workflows; working ethically. Same as STAT 4680.
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Background

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Github

  • ervance1