## Contact Information

phone: (716) 839-8541

daemen.edu/math

### Chair

Claudiu Mihai

(716) 839-8319

## Degree Offered

- Bachelor of Arts in Mathematics
- Bachelor of Science in Adolescence Education: Mathematics
- Bachelor of Science in Data Science
**(currently not accepting new students)**

## Minors

All students taking Mathematics courses must take the quantitative skills placement tests. Scores for admission to various courses are determined by the Mathematics faculty.

# Mathematics/Computer Science Goals

I. Develop effective thinking and communication skills

II. Learn to use technological tools

III. Learn to link applications and theory

IV Develop mathematical independence and experience open-ended inquiry

V. Content Specific Goal: Learn the theory and application from calculus; linear algebra; data analysis; computer programming; lab science sequence; and read, analyze and produce proofs.

## Additional goal for mathematics majors seeking adolescent teaching certification:

VI. Demonstrate knowledge and apply the national and state standards for mathematics instruction.

## Specific learning objectives for mathematics Core courses (as outlined in the Quantitative Literacy requirement of the Core Curriculum):

A) Interpret models such as formulas, graphs, tables, and schematics, and draw inferences from them.

(B) Represent information symbolically, visually, numerically, and verbally. Use arithmetical, algebraic, geometric and statistical methods to solve problems.

(C) Estimate and check answers to problems in order to determine reasonableness, identify alternatives, and select optimal results.

(D) Recognize that quantitative methods and statistical methods have limits.

Mathematics Department Goals and Learning Objectives: as outlined by the Mathematical Association of America (MAA), “Mathematical Association of America’s Committee on the Undergraduate Program in Mathematics (CUPM).” http://www.maa.org.

## Data Science Program Objectives and Goals:

- Develop in depth knowledge of the key tools in data science including: data mining; machine learning; data exploration; programming; and statistics.
- Apply data science concepts and methods to produce effective solutions based on a set of data, and effectively communicate these solutions.
- Demonstrate use of team work, leadership skills, decision-making, and communication skills.