BTRY 5090

BTRY 5090

Course information provided by the Courses of Study 2021-2022.

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, STSCI 5090.

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 4090STSCI 4090STSCI 5090

  • 4 Credits Graded

  • 19008 BTRY 5090   LEC 001

    • TR Caldwell Hall 100
    • Jan 24 - May 10, 2022
    • Diciccio, T

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

  • 19009 BTRY 5090   DIS 201

    • F Warren Hall 101
    • Jan 24 - May 10, 2022
    • Diciccio, T

  • Instruction Mode: In Person

  • 19010 BTRY 5090   DIS 202

    • F Warren Hall 101
    • Jan 24 - May 10, 2022
    • Diciccio, T

  • Instruction Mode: In Person