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Adam Allan

Lecturer

School of Mathematics and Statistics
College of Science

585-475-4149
Office Hours
Monday 8:50 -- 9:50 AM in HLC-2214 Wednesday 8:50 -- 9:50 AM in HLC-2214 Friday 9:50 -- 11:50 AM in HLC-2214
Office Location

Adam Allan

Lecturer

School of Mathematics and Statistics
College of Science

585-475-4149

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My research areas are representation theory and homological algebra.

“Modular Centralizer Algebras Corresponding to p-Groups”. Journal of Algebra 339: 156-171, 2011.

Currently Teaching

MATH-181
4 Credits
This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals.
MATH-182
4 Credits
This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates.
MATH-219
3 Credits
This course is principally a study of the calculus of functions of two or more variables, but also includes the study of vectors, vector-valued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, and includes applications in physics. Credit cannot be granted for both this course and MATH-221.
MATH-251
3 Credits
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.