BTRY 4090

BTRY 4090

Course information provided by the Courses of Study 2022-2023.

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.

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Syllabi:
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: BTRY 5090STSCI 4090STSCI 5090

  • 4 Credits Graded

  •  1064 BTRY 4090   LEC 001

    • MW Warren Hall 175
    • Jan 23 - May 9, 2023
    • Diciccio, T

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

  •  1065 BTRY 4090   DIS 201

    • F Warren Hall B75
    • Jan 23 - May 9, 2023
    • Diciccio, T

  • Instruction Mode: In Person

  •  2007 BTRY 4090   DIS 202

    • F Warren Hall B75
    • Jan 23 - May 9, 2023
    • Diciccio, T

  • Instruction Mode: In Person