Course Detail

Probability and Statistics (41901)

Course Description by Faculty

  • Kaji, Tetsuya
  • Content
    This is a PhD course that introduces fundamental statistical methods for academic research in business and economics. It covers basic concepts in probability and statistics, including conditional probability, limit theorems, estimation and inference, and linear regression.
    Format
    • Lectures

  • Prerequisites
    Real analysis and linear algebra. BUSN 41901=STAT 32400

  • Materials
    There is no required textbook.
    Resources
    • Canvas Site Available

  • Grades
    Grades are based on a midterm exam and a final exam.
    Assessment & Testing
    • Midterm

    • Final exam (take home)

  • Syllabus
  • Autumn 2021Section: 41901-50W 3:00PM-6:00PMHarper CenterC06In-Person Only
Description and/or course criteria last updated: October 7 2021