Denitza Straub Headshot

Denitza Straub

Lecturer

School of Mathematics and Statistics
College of Science

585-475-4351
Office Hours
Monday: 10-10:50 am Wednesday: 10-10:50 am Friday: 9-10:50 am And by appointment
Office Location

Denitza Straub

Lecturer

School of Mathematics and Statistics
College of Science

Education

BA, Colgate University; MS, Ph.D., University of Rochester

585-475-4351

Currently Teaching

MATH-171
3 Credits
This is the first course in a three-course sequence (COS-MATH-171, -172, -173). This course includes a study of precalculus, polynomial, rational, exponential, logarithmic and trigonometric functions, continuity, and differentiability. Limits of functions are used to study continuity and differentiability. The study of the derivative includes the definition, basic rules, and implicit differentiation. Applications of the derivative include optimization and related-rates problems.
MATH-172
3 Credits
This is the second course in three-course sequence (COS-MATH-171, -172, -173). The course includes Riemann sums, the Fundamental Theorem of Calculus, techniques of integration, and applications of the definite integral. The techniques of integration include substitution and integration by parts. The applications of the definite integral include areas between curves, and the calculation of volume.
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-241
3 Credits
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.