Course Detail

Business Statistics (41000)

Course Description by Faculty

  • Deb, Nabarun
  • Content
    Data science. Machine learning. Statistics. Predictive Analytics. No matter what it’s called, modern business runs on data. This course is an introduction to the fundamentals of probability and statistics with an aim towards building foundational skills in modern data science. Topics to be covered include 1) Exploratory data analysis and descriptive statistics, 2) Basic probability, common pitfalls and fallacies, 3) Statistical modeling, inference, p-values, and A/B testing, and 4) Prediction, regression, and classification. Emphasis will be placed on ethics and privacy in data analysis as well as real-world applications and case studies.

  • Prerequisites
    No undergraduates (including Dougan Scholars). Other non-Booth students require faculty permission.
    • No non-Booth Students

  • Grades
    No pass/fail grades. No auditors.
    • No auditors

    • No pass/fail grades

  • No Syllabus Available
  • Spring 2024Section: 41000-01MW 8:30AM-9:50AMHarper CenterC05In-Person Only
  • Spring 2024Section: 41000-02MW 10:10AM-11:30AMHarper CenterC05In-Person Only
Description and/or course criteria last updated: June 28 2023