Course Detail (Course Description By Faculty)

Probability and Statistics (41901)

This is a PhD course that introduces fundamental statistical concepts for academic research in business and economics. It covers basic topics in probability and statistics, including limit theorems, principles of estimation and inference, linear and logistic regression, and causal inference. Much emphasis is put on large-sample (asymptotic) theory.
Real analysis and linear algebra. BUSN 41901=STAT 32400

There is no required textbook.
Grades are based on a midterm exam and a final exam.
Description and/or course criteria last updated: September 25 2024
SCHEDULE
  • Autumn 2024
    Section: 41901-50
    F 1:30 PM-4:30 PM
    Harper Center
    C04
    In-Person Only

Probability and Statistics (41901) - Kaji, Tetsuya>>

This is a PhD course that introduces fundamental statistical concepts for academic research in business and economics. It covers basic topics in probability and statistics, including limit theorems, principles of estimation and inference, linear and logistic regression, and causal inference. Much emphasis is put on large-sample (asymptotic) theory.
Real analysis and linear algebra. BUSN 41901=STAT 32400

There is no required textbook.
Grades are based on a midterm exam and a final exam.
Description and/or course criteria last updated: September 25 2024
SCHEDULE
  • Autumn 2024
    Section: 41901-50
    F 1:30 PM-4:30 PM
    Harper Center
    C04
    In-Person Only