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Lasell University
Lasell University

2014 - 2015 Academic Catalog

Mathematics Minor

The Mathematics minor consists of six courses.
Course Code Course Title Credits
Core Courses
MATH205 Calculus I 4
MATH206 Calculus II 4
MATH208 Statistics 3
Choose 2 from the following:
MATH207 Applied Trigonometry 3
MATH210 Math Applied to Science 3
MATH212 Finite Mathematics 3
MATH307 Calculus III 4
MATH320 Differential Equations 4
MATH325 Linear Algebra 3
MATH328 Mathematics Applied to Management 3
MATH330 Mathematical Modeling 3
MATH338 Mathematical Statistics 3
Choose 1 from the following:
MATH307 Calculus III 4
MATH320 Differential Equations 4
MATH325 Linear Algebra 3
MATH328 Mathematics Applied to Management 3
MATH330 Mathematical Modeling 3
MATH338 Mathematical Statistics 3

To count toward the minor, each course must be passed with at least a C.

MATH 205 & MATH 208 may require prior coursework depending upon Math placement.

Credit Requirements for minor: 20 credits

MATH205 - Calculus I

This course is an introduction to limits, continuity, and methods of differentiation. Application to problems in business management and physical science is emphasized. Prerequisite: MATH 203 with a grade of C or better or demonstrated competency through placement testing. Restrictions: not open to students who have completed MATH 206, or any 300 level mathematics courses.

MATH206 - Calculus II

This is a continuation of Calculus I, covering integration, functions of several variables, partial differentiation, maxmin problems, derivatives and integrals of trigonometric functions and differential equations with applications to business, biological sciences, and physical sciences. Prerequisite: MATH 205 with a grade of C or better or demonstrated competency through placement testing. Restrictions: not open to students who have completed MATH 320, MATH 328, or MATH 330.

MATH208 - Statistics

This is an introductory course in descriptive and inferential statistics with an emphasis on applications in business and the social and biological sciences. Topics include: data analysis, and graphical methods of describing data, measures of central tendency and variability, probability, the normal distribution, sampling distributions, confidence intervals, hypothesis testing, correlation, and regression analysis. Prerequisites: MATH 106 with a grade of C or better or demonstrated competency through placement testing and ENG 102.

MATH207 - Applied Trigonometry

This course is an in-depth study of trigonometry with attention to theory, proofs, modeling, and history. Trigonometric and related functions are used to model, analyze, and solve real-life problems. Applications are chosen from disciplines such as agriculture, architecture, astronomy, biology, business, chemistry, earth science, engineering, medicine, meteorology, and physics. Topics covered include a review of trigonometric functions, right triangle trigonometry, analytic trigonometry, vectors and dot products, complex number theory, trigonometric forms of complex numbers, exponential, logarithmic and trigonometric models, Gaussian and logistic growth models, conic sections, and polar equations of conics. Prerequisite: MATH 205 with a grade of C or better.

MATH210 - Math Applied to Science

This course provides a review of fundamental mathematical concepts such as probability and trigonometric, exponential and logarithmic functions and explores the ways that these topics and techniques have been applied to investigations in architecture, calculus, exponential growth and decay, logarithmic scales, earthquake analysis, astronomy, biology, medicine, genetics, radiocarbon dating, chemistry, and Newtonian physics. The course is designed to demonstrate the power and utility of mathematics and explores the development of mathematics during the Middle Ages and the Renaissance, especially in Greek, Hindu and Arabic cultures. Prerequisite: MATH 205 with a grade of C or better.

MATH212 - Finite Mathematics

The focus of this course is to develop mathematical models and to demonstrate the utility of various mathematical techniques that are most applicable to the creation of computer algorithms. Topics include functions and models, linear regression, solving systems of linear equations using matrices, matrix algebra and Leontief Input-Output models, linear programming (graphical and simplex methods), principle of duality, estimated and theoretical probability and Markov Chains. Applications are derived from current real world data and require mastery of Microsoft Excel and graphing calculator technology. Prerequisite: MATH 206 with a grade of C or better.

MATH307 - Calculus III

This course is an introduction to sequences and series, parametric and polar curves, vectors and vector functions, partial derivatives, multiple integration, and vector calculus. Prerequisite: MATH 206 with a grade of C or better.

MATH320 - Differential Equations

This is an introduction to the many ways of solving various types of differential equations with emphasis on theory, methods of solution and applications. Topics include solutions of first, second and simple higher order differential equations, homogeneous and non-homogeneous equations, solutions of systems of differential equations using the theory of matrices, and determinants. Prerequisite: MATH 206 with a grade of B- or better.

MATH325 - Linear Algebra

This is an introductory course in linear algebra blending the requirements of theory, problem solving, analytical thinking, computational techniques, and applications. Topics include in-depth treatment of matrix algebra, linear systems, vector spaces, linear transformations, determinants and computer methods, as well as applications and modeling of real phenomena in transportation systems, archaeology, economics, communications, demography, weather prediction, connectivity of networks, graph theory, and fractals. Prerequisite: MATH 206 with a grade of C or better.

MATH328 - Mathematics Applied to Management

This course explores the art of mathematical modeling of managerial decision problems and the science of developing the solution techniques for these models. Topics include management science techniques used in today’s businesses, e.g., break-even analysis, presentation models, linear programming, transportation and assignments problems, decision theory, forecasting and inventory models, Markov analysis, and solution of nonlinear models in business using calculus-based optimization. Prerequisite: MATH 206 with a grade of C or better.

MATH330 - Mathematical Modeling

This is an application-oriented course on how to solve real word problems from the social, medical and life sciences, business, and economics by set­ting up a mathematical model of the situation and then developing techniques for analyzing these models and solving them. Topics include the modeling process, linear models, financial models, modeling using proportionality, fitting linear and nonlinear models to data graphically, the least-squared criterion, linear programming models, modeling using the derivative, matrix and probability models, Markov chain models, and modeling interactive dynamic systems. Prerequisite: MATH 206 with a grade of C or better.

MATH338 - Mathematical Statistics

In this introduction to statistical theory, the roles probability and statistics play in business analysis and decision making are investigated. Topics include probability distributions, statistical inference, sampling distribution theory, and applications. Prerequisite: Math 206 with a grade of C or better.

MATH307 - Calculus III

This course is an introduction to sequences and series, parametric and polar curves, vectors and vector functions, partial derivatives, multiple integration, and vector calculus. Prerequisite: MATH 206 with a grade of C or better.

MATH320 - Differential Equations

This is an introduction to the many ways of solving various types of differential equations with emphasis on theory, methods of solution and applications. Topics include solutions of first, second and simple higher order differential equations, homogeneous and non-homogeneous equations, solutions of systems of differential equations using the theory of matrices, and determinants. Prerequisite: MATH 206 with a grade of B- or better.

MATH325 - Linear Algebra

This is an introductory course in linear algebra blending the requirements of theory, problem solving, analytical thinking, computational techniques, and applications. Topics include in-depth treatment of matrix algebra, linear systems, vector spaces, linear transformations, determinants and computer methods, as well as applications and modeling of real phenomena in transportation systems, archaeology, economics, communications, demography, weather prediction, connectivity of networks, graph theory, and fractals. Prerequisite: MATH 206 with a grade of C or better.

MATH328 - Mathematics Applied to Management

This course explores the art of mathematical modeling of managerial decision problems and the science of developing the solution techniques for these models. Topics include management science techniques used in today’s businesses, e.g., break-even analysis, presentation models, linear programming, transportation and assignments problems, decision theory, forecasting and inventory models, Markov analysis, and solution of nonlinear models in business using calculus-based optimization. Prerequisite: MATH 206 with a grade of C or better.

MATH330 - Mathematical Modeling

This is an application-oriented course on how to solve real word problems from the social, medical and life sciences, business, and economics by set­ting up a mathematical model of the situation and then developing techniques for analyzing these models and solving them. Topics include the modeling process, linear models, financial models, modeling using proportionality, fitting linear and nonlinear models to data graphically, the least-squared criterion, linear programming models, modeling using the derivative, matrix and probability models, Markov chain models, and modeling interactive dynamic systems. Prerequisite: MATH 206 with a grade of C or better.

MATH338 - Mathematical Statistics

In this introduction to statistical theory, the roles probability and statistics play in business analysis and decision making are investigated. Topics include probability distributions, statistical inference, sampling distribution theory, and applications. Prerequisite: Math 206 with a grade of C or better.