MATH 4720

Theory of Statistics

Course Description

Course information provided by the 2026-2027 Catalog.

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

Prerequisites STSCI 3080 or MATH 4710 or equivalent and at least one introductory statistics course.

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

Last 4 Terms Offered 2026SP, 2025FA, 2025SP, 2024FA

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.

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