This is a survey course of discrete mathematics for non-physical science majors. Topics include systems of inequalities, linear programming, probability and probability distributions, and an introduction to descriptive statistics. The course emphasizes problem solving through the use of computer spreadsheets.
1. Identify and solve linear programming problems.
2. Write and analyze algebraic models for business and other applications.
3. Solve business and biological applications using probability distributions.
Math of Biological/Management/Social Sciences presents intuitive development of the calculus of polynomial, exponential and logarithmic functions, and extrema theory and applications.
1. Apply calculus to solve problems with confidence, persistence, and openness to alternate approaches.
2. Interpret and communicate the concepts of rates of change and derivatives.
3. Connect the graphical behavior, numerical patterns and symbolic representations of function and derivatives.
4. Collaborate to solve calculus problems related to their field of study.
5. Recognize when and how to proficiently apply calculus tools to solve problems in business management, social sciences and and biological sciences.
6. Use a graphing calculator and/or other technology to solve applied problems.
A survey course in mathematics for students in the liberal arts and other non-science majors. Topics are selected from areas such as management science, statistics, social choice, the geometry of size and shape, and computers and their applications. Emphasizes the application of mathematics to the problems of contemporary society and the critical role these applications play in economic, political and personal life.
1. Formulate questions that can be addressed with data, then organize, display and analyze relevant data to address these questions and communicate results.
2. Apply the basic principles of study design to develop and analyze the validity of simple experiments.
3. Demonstrate numeric and algebraic reasoning skills to support statistical analysis and financial literacy.
4. Construct, use, and interpret mathematical models, specifically linear, quadratic, logarithmic, and exponential functions, to represent relationships in quantitative data.