BTRY 4090

BTRY 4090

Course information provided by the Courses of Study 2023-2024.

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.

When Offered Fall, Spring.

Prerequisites/Corequisites Prerequisite: BTRY 3080 or MATH 4710 or equivalent and at least one introductory statistics course.
Forbidden Overlaps Forbidden Overlap: due to an overlap in content, students will receive credit for only one course in the following group: BTRY 4090, MATH 4720, STSCI 4090.

Distribution Category (OPHLS-AG)

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

  •  2315 BTRY 4090   LEC 001

    • TR Malott Hall 251
    • Aug 21 - Dec 4, 2023
    • Wegkamp, M

  • Instruction Mode: In Person
    Prerequisite: BTRY 3080 or MATH 4710 or equivalent and at least one introductory statistics course.

  •  2316 BTRY 4090   DIS 201

    • F Warren Hall 151
    • Aug 21 - Dec 4, 2023
    • Wegkamp, M

  • Instruction Mode: In Person