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Course Criteria
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3.00 Credits
This course is an introduction to non-technical applications of mathematics in the modern world and is designed to cultivate an appreciation of the significance of mathematics in daily life and to develop students mathematical reasoning. Subjects include Quantitative Information in Everyday Life, Financial Management, Statistics and Probability.
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4.00 Credits
This course is an introduction to non-technical applications of mathematics in the modern world and is designed to study the basic concepts of arithmetic and algebra, cultivate an appreciation of the significance of mathematics in daily life and to develop student's mathematical reasoning. Subjects include Basic Algebra, Problem Solving, Consumer Mathematics, Statistics and Probability.
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4.00 Credits
Math for Liberal Arts
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4.00 Credits
This course contains algebraic techniques, functions, and graphs which are essential in order to understand and use higher level mathematics. Topics include linear and quadratic equations and inequalities, function notation, combinations, translations and graphs of common functions.
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4.00 Credits
This course is an introduction to advanced algebraic techniques, functions and graphs which are essential in order to understand and use higher level mathematics in courses beginning with calculus. Topics include conic sections, rational, exponential, logarithmic, and trigonometric functions.
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3.00 Credits
This course is designed for students who need an elementary knowledge of statistics. The basic ideas of descriptive statistical methods are considered, including frequency distribution, measures of location and variation. It also includes permutation, combination and rules of probability, together with well-known probability distributions such as binomial, poisson, geometric, hyper geometric and multinomial.
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3.00 Credits
This course will teach the foundations of data science and data-driven research. It is designed to serve as an optional elective course for mathematics majors, minors, and other STEM, business, and social science majors who are interested in pursuing data-driven careers or graduate study programs. Students will acquire basic computational skills, basic knowledge of statistical analysis, error analysis, and the basics of machine learning. Students will also be familiarized with good practices for handling small and big data. After this class, students should be able to formulate a question, identify appropriate data to answer the question, prepare and analyze the data, extract knowledge and insights, make decisions and identify the confidence level of decisions. This course will be organized in a modular fashion, with labs and projects assigned to students for group work.
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3.00 Credits
This course is designed for students in the Social Sciences. The goal of the course is to give the student a working knowledge of the areas of mathematics that are most applicable to his or her particular discipline. Among the topics studied will be elementary matrix algebra, linear programming, logarithms, progressions, and the mathematics of finance.
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4.00 Credits
This course studies differential and integral calculus with a focus on its applications to business and economics. Topics to be covered are increments and rates, limits, the derivative, rules of differentiation, logarithmic differentiation, methods of integration, and applications of the definite integral to business and economics.
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4.00 Credits
This is the first course in the calculus sequence designed for students intending to major in mathematics, natural sciences, and engineering. The topics covered will include: the straight line, functions, plane analytic geometry, limits, continuity, derivatives of algebraic and trigonometric functions, with applications to velocity, rates, extreme curve plotting and optimization, differentials, Roll146s theorem, mean-value theorem, and integration.
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