BTRY 4090

BTRY 4090

Course information provided by the Courses of Study 2018-2019.

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 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)

  • 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: STSCI 4090

  • 4 Credits Graded

  •  1159 BTRY 4090   LEC 001

  • Prerequisites: BTRY 3080 or equivalent and at least one introductory statistics course.

  •  1160 BTRY 4090   DIS 201

  •  4411 BTRY 4090   DIS 202