BTRY 4090

BTRY 4090

Course information provided by the 2025-2026 Catalog.

Introduction to classical theory of parametric statistical inference that builds on the material covered in BTRY 3080. Topics include: sampling distributions, principles of data reduction, likelihood, parameter estimation, hypothesis testing, interval estimation, and basic asymptotic theory.


Prerequisites BTRY 3080 or MATH 4710 or equivalent and BTRY 3010 or equivalent.

Distribution Requirements (DLS-AG, OPHLS-AG), (SDS-AS)

Last 4 Terms Offered 2025FA, 2025SP, 2024FA, 2024SP

Learning Outcomes

  • Describe the general principles of statistical estimation and testing.
  • Design a statistical estimator in a principled way based on a description of a dataset.
  • Analyze the theoretical properties of an estimator and a hypothesis test.
  • Calculate and correctly interpret confidence intervals, p-values, statistical significance, and power.
  • Recognize the general principles underlying common statistical procedures.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: BTRY 5090STSCI 4090STSCI 5090

  • 4 Credits Graded

  •  1483 BTRY 4090   LEC 001

    • TR
    • Aug 25 - Dec 8, 2025
    • Diciccio, T

  • Instruction Mode: In Person

    For Bowers Computer and Information Science (CIS) Course Enrollment Help, please see: https://tdx.cornell.edu/TDClient/193/Portal/Home/

  •  1484 BTRY 4090   DIS 201

    • F
    • Aug 25 - Dec 8, 2025
    • Diciccio, T

  • Instruction Mode: In Person