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This course is designed to introduce students to applications of mathematics used in a variety of disciplines. The course requires students to use critical thinking skills and mathematical models in order to make sound decisions and problem-solve. Topics include inductive and deductive reasoning, algebraic problem-solving, networks and graph theory, financial management, sequences, series, voting, and apportionment.

This course introduces students to topics in mathematics, which challenge their skills of analysis and logical thinking. Topics include critical thinking, sets, logic, and linear modeling.

This course emphasizes statistical reasoning, sampling methodology, probability, descriptive statistics, and inference. It includes analysis and interpretation of statistical data generated in the fields of sociology, criminal justice, allied health and hospitality. Common errors in sampling, data interpretation, and research design will be addressed. Topics include statistical thinking, descriptive statistics, the normal distribution, frequency distributions, confidence interval estimates, hypothesis testing, data interpretation and analysis and an introduction to research design.

This course is for students who plan to continue their education and need the prerequisite skills for higher-level math courses. Topics include: a review of polynomial functions, trigonometric functions and their graphs, trigonometric formulas and identities, as well as sequences and series.

This course is a survey of statistical techniques and their applications to business. Topics include: frequency distributions, sampling techniques, confidence intervals and hypothesis testing, and laws of probability theory. Examples are extensively used to demonstrate and apply these techniques to cases relevant to business and may include applications such as analysis and interpretation of profitability, marketing, and production line quality.