APPM 4520  Introduction to Mathematical Statistics
Primary Instructor

Spring 2018
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Same as STAT 5520 and MATH 4520 and MATH 5520.
APPM 5520  Introduction to Mathematical Statistics
Primary Instructor

Spring 2018
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Department enforced prerequisite: one semester calculusbased probability course, such as MATH 4510 or APPM 3570. Same as STAT 4520 and MATH 4520 and MATH 5520.
FYSM 1000  First Year Seminar
Primary Instructor

Fall 2018 / Fall 2020
Provide first year students with an immersive experience in an interdisciplinary topic that addresses current issues including social, technical and global topics. Taught by faculty from across campus, the course provides students with an opportunity to interact in small classes, have project based learning experiences and gain valuable communication skills. Seminar style classes focused on discussion and projects.
MATH 2400  Calculus 3
Primary Instructor

Spring 2020
Continuation of MATH 2300. Topics include vectors, threedimensional analytic geometry, partial differentiation and multiple integrals, and vector analysis. Department enforced prerequisite: MATH 2300 or APPM 1360 (minimum grade C). Degree credit not granted for this course and APPM 2350.
MATH 3001  Analysis 1
Primary Instructor

Spring 2021 / Spring 2022 / Spring 2024 / Fall 2024
Provides a rigorous treatment of the basic results from elementary Calculus. Topics include the topology of the real line, sequences of numbers, continuous functions, differentiable functions and the Riemann integral.
MATH 3850  Seminar in Guided Mathematics Instruction
Primary Instructor

Spring 2020
Provides learning assistants with an opportunity to analyze assessment data for formative purposes and develop instructional plans as a result of these analyses. These formative assessment analyses will build on the literature in the learning sciences. Students gain direct experiences interacting with the tools of the trade, especially with actual assessment data and models of instruction. May be repeated up to 3 total credit hours. Restricted to learning assistants in Math.
MATH 4520  Introduction to Mathematical Statistics
Primary Instructor

Spring 2018 / Spring 2019
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Same as MATH 5520 and STAT 4520 and STAT 5520.
MATH 4530  Theoretical Foundations of Data Science
Primary Instructor

Spring 2024
Introduces theoretical concepts from mathematics, statistics, and computer science required to understand and analyze data. Topics include randomized algorithms, machine learning, streaming, sketching, clustering, random matrices and graphs, graphical models and compressed sensing.
MATH 5520  Introduction to Mathematical Statistics
Primary Instructor

Spring 2019
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Department enforced prerequisite: one semester calculusbased probability course, such as MATH 4510 or APPM 3570. Recommended prerequisite: previous coursework equivalent to APPM 3570 or STAT 3100 or MATH 4510; minimum grade of C for all. Same as STAT 4520 and MATH 4520 and STAT 5520.
MATH 6310  Introduction to Real Analysis 1
Primary Instructor

Fall 2021
Develops the theory of Lebesgue measure and the Lebesgue integral on the line, emphasizing the various notions of convergence and the standard convergence theorems. Applications are made to the classical L^p spaces. Department enforced prerequisite: MATH 4001. Instructor consent required for undergraduates.
MATH 6320  Introduction to Real Analysis 2
Primary Instructor

Spring 2018
Covers general metric spaces, the Baire Category Theorem, and general measure theory, including the RadonNikodym and Fubini theorems. Presents the general theory of differentiation on the real line and the Fundamental Theorem of Lebesgue Calculus. Recommended prerequisite: MATH 6310. Instructor consent required for undergraduates.
MATH 6350  Functions of a Complex Variable 1
Primary Instructor

Fall 2020
Focuses on complex numbers and the complex plane. Includes CauchyRiemann equations, complex integration, Cauchy integral theory, infinite series and products, and residue theory. Department enforced prerequisite: MATH 4001. Instructor consent required for undergraduates.
MATH 6534  Topics in Mathematical Probability
Primary Instructor

Fall 2023
Offers selected topics in probability such as sums of independent random variables, notions of convergence, characteristic functions, Central Limit Theorem, random walk, conditioning and martingales, Markov chains and Brownian motion. Department enforced prerequisite: MATH 6310. Instructor consent required for undergraduates
STAT 4520  Introduction to Mathematical Statistics
Primary Instructor

Spring 2019
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Same as STAT 5520 and MATH 4520 and MATH 5520.
STAT 5520  Introduction to Mathematical Statistics
Primary Instructor

Spring 2019
Examines point and confidence interval estimation. Principles of maximum likelihood, sufficiency, and completeness: tests of simple and composite hypotheses, linear models, and multiple regression analysis if time permits. Analyzes various distributionfree methods. Department enforced prerequisite: one semester calculusbased probability course, such as MATH 4510 or APPM 3570. Recommended prerequisite: previous coursework equivalent to APPM 3570 or STAT 3100 or MATH 4510; minimum grade of C for all. Same as STAT 4520 and MATH 4520 and MATH 5520.