2019-2020 Academic Catalog [Archived Catalog]
Courses
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| Undergraduate Prerequisites |
Course Numbering |
| A “C-” or higher is required in all prerequisite courses |
100-299 - Lower division undergraduate |
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300-499 - Upper division undergraduate |
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500-699 - Graduate |
| Search Tip |
700-799 - Doctoral |
| Use the asterisk (*) key as a wild card. |
| Example: Select “Prefix” NURS and enter 6* in the “Code or Number” field to return all Nursing courses at the 600 level. |
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MATH 100 - Elementary Algebra
Credits: Three (3)
The course is for students who need to refresh basic mathematical skills and elementary algebraic concepts including signed numbers, algebraic laws and operations, linear equations and inequalities and the graphs, exponents, operations of polynomials, factoring, scientific notation, and quadratic equations.
Note: This course does not satisfy the General Education requirement.
General Education Area: Quantitative Reasoning
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MATH 102 - Everyday Data
Credits: Three (3)
Everyday Data course gives a foundation to the world of data science and Excel. There will be no computer science background assumed from students. The sections under study include data collection, data organization, data description, data presentation using Excel and statistical analysis using Excel. The course is designed in such a way that students will gain an understanding on data and statistical analysis by the use of Excel to make and obtain valuable insights.
General Education Area: Quantitative Reasoning
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MATH 115 - Contemporary Mathematics
Credits: Three (3)
A survey of topics in modern mathematics designed for the liberal arts/social science student, the emphasis is on concepts, applications and critical thinking rather than manipulative skills. Technology will be used as a tool in this course. Mathematical topics, with historical perspectives, will include reasoning, probability, statistics, linear programming, graph theory, geometry, consumer mathematics, and number systems.
General Education Area: Quantitative Reasoning
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MATH 116 - Intermediate Algebra
Credits: Three (3)
This course assumes that the student is familiar with elementary algebra. Topics include rational expressions and their operations; complex fractions, applications of rational expressions; systems of linear equations and word problems; compound inequalities in one and two variables; absolute value equations and inequalities; operations of radicals and rational exponents; quadratic equations and applications; functions and graphs.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-100
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MATH 117 - College Algebra
Credits: Three (3)
This course assumes that the student is familiar with the fundamentals of algebraic concepts, expressions, equations, and inequalities. Topics include functions and their graphs; polynomial and rational functions; exponential and logarithmic functions; systems of equations and inequalities; partial fractions; operations with matrices; arithmetic and geometric sequences and series.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-116
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MATH 125 - College Algebra and Trigonometry
Credits: Three (3)
This course meets the math needs of students who major in science, physical therapy, pre-engineering and mathematics. This fast-paced course, in addition to presenting all the features of college algebra, develops the trigonometric functions. Topics include polynomial and rational functions; exponential and logarithmic functions; systems of equations and inequalities; partial fractions; sequences and series; trigonometric functions; trigonometric identities and equations; applications of trigonometry.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-116
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MATH 135 - Mathematics for Scientists
Credits: Three (3)
This course is required for the students who are acquiring degrees in sciences. The topics that will be covered ranges from elementary algebra to trigonometry. Students will learn to apply math skill in real world science applications.
General Education Area: Quantitative Reasoning
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MATH 141 - Elementary Statistics
Credits: Three (3)
This course is an introduction to the basic concepts of both descriptive and inferential statistics. The topics include data collection and sampling techniques; frequency distributions and graphs; data descriptions and boxplots; addition, multiplication and conditional probability and counting rules; discrete probability distributions; binomial distributions; normal distributions and applications; central limit theorem; confidence intervals and sample size; testing of hypotheses.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-117
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MATH 151 - Calculus I
Credits: Four (4)
Topics include concepts of limit and continuity; derivatives and their applications; chain rule; implicit differentiation; linearization and differentials; extreme values of functions; monotony and concavity of functions; the mean value theorem; indefinite integrals and substitution method; fundamental theorems of calculus; definite integrals and applications.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-125
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MATH 152 - Calculus II
Credits: Four (4)
This course should be taken in sequence with MATH 151. Topics include advanced functions; techniques of integration including integration by parts, partial fractions method, and trigonometric substitutions; improper integrals; sequences, series, and Taylor’s formula; and parametrizations of curves, polar coordinates.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-151
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MATH 207 - Algebra for Educators
Credits: Three (3)
This course is designed only for elementary and middle school/secondary math education majors. Topics include rational number representations, algebraic expressions & equations, linear equations, and systems of linear equations. Problem solving and application problems will be incorporated throughout the course.
General Education Area: Quantitative Reasoning
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MATH 208 - Geometry and Statistics for Educators
Credits: Three (3)
This course is designed only for elementary and middle school education majors. This course includes the study of geometry and data analysis. Geometry topics include measurement, geometric concepts, right triangle geometry, formal & informal proofs, and coordinate geometry. Data analysis topics include random sampling, central tendency, variability, and graphs. Problem solving and application problems will be incorporated throughout the course.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-100
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MATH 220 - Finite Mathematics
Credits: Three (3)
This course meets the needs of students who are majoring in education, business and various majors in the College of Arts and Sciences. Topics included in this course are probability and set theory, permutations and combinations, matrices, linear programming, finance, logic and statistics. Students will apply principles to real world problems.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-125
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MATH 239 - Fund Secondary Teaching
Credits: Three (3)
The course offers an introduction to lesson planning, assessment, pedagogy and curricular standards needed to teach secondary students. It builds the capacity for becoming a secondary teacher through the exploration of curricular and pedagogical practices that foster teaching for conceptual understanding, inquiry skills, 21st century skills of communication, collaboration, critical thinking and creativity.
General Education Area: Quantitative Reasoning
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MATH 245 - Analytics of Baseball
Credits: Three (3)
The course will focus on the different statistical aspects associated with constructing a baseball team. Focus will look at the areas of gathering, analyzing and communicating statistical data for use in determining players for a roster, looking at player performance, in-game strategy and day to day team operations. There will be an emphasis on establishing a personally customized framework for optimum performance to produce a successful team.
General Education Area: Quantitative Reasoning
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MATH 251 - Calculus III
Credits: Four (4)
This is the third course of the calculus sequence. Topics include vector-valued functions; partial derivatives and applications; multiple integrals and applications; double integrals in polar form; substitutions in multiple integrals; line integrals; Green’s Theorem in the plane; surface integrals; Stoke’s Theorem.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-152
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MATH 297 - Special Studies
Credits: One (1) to Four (4)
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MATH 300 - Algebraic Structures and Proofs
Credits: Three (3)
This course introduces the basic mathematical theory and proofs of the fundamental theorems and formulas in preparation for further studies in mathematics, data science, and mathematics education. The course prepares students for the demand of advanced courses while giving students an opportunity to witness and participate in the intrinsic beauty of formal mathematical thought. Topics include logic; set theory and related topics, mathematical induction and recursion; fundamental counting principles; combinatorics; basic study of number theory; and complex numbers.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-151 or AP Calculus AB
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MATH 301 - Math Modeling- VBA
Credits: Three (3)
This course complements and continues the technical computer training offered in DSCI 201. The content focuses on business applications including finance, statistics, and mathematical modeling. The applications provide the context for developing programming skills, using the Visual Basic Applications language as the programming vehicle and potential application in automation.
Prerequisite: DSCI-201
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MATH 311 - Discrete Mathematics
Credits: Three (3)
This course is the logic foundation of mathematics, data science, computer science, (computer) software engineering, electrical engineering, business and economics applications. This course is suitable for those who intend to use computer technology, advanced programming languages, and advanced database knowledge in applications such as data science, business, economics, and variety of science research. This course covers mostly formal logic, algorithms, relational databases, graphs and trees, and mathematical modeling, computations, and other related topics.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-117
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MATH 312 - Number Theory with Applications
Credits: Three (3)
This course covers fundamental principles of number theory. Topics include primes and composites; divisors and multiples, divisibility, remainders; the Euclidean Algorithm; the fundamental theorem of arithmetic; congruencies and applications of congruencies; and continued fractions.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-125
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MATH 316 - Applied Linear Algebra
Credits: Three (3)
This one semester course is designed to introduce the students to the fundamental concepts underlying the study of linear algebra. Topics include matrix algebra; systems of linear equations; vector spaces and subspaces; basis and dimensions; orthogonality; determinants; eigenvalues and eigenvectors; diagonalization of matrices; and linear transformations.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-117
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MATH 320 - Applied Differential Equations
Credits: Three (3)
This course introduces the use of mathematical modeling based on calculus and differential equations. Topics include first-order differential equations; Euler’s method and Runge-Kutta method; linear equations of higher order; non-linear differential equations; systems of equations; transforms; and numerical methods. Practical applications are emphasized and computers will be employed to illustrate the underlying mathematical principles.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-251
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MATH 330 - College Geometry
Credits: Three (3)
This course covers more advanced mathematics in the area of Euclidean and non-Euclidean geometries. Topics include neutral geometry, Euclidean plane geometry, non-Euclidean geometry, and projective geometry.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-125
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MATH 351 - Advanced Calculus
Credits: Three (3)
This course covers the differential calculus in the setting of normed vector spaces, and the calculus of differentiable manifolds of the calculus sequence. Topics include normed vector spaces, differential calculus, differential equations, integration theory, differential manifolds, and integral calculus on manifolds.
General Education Area: Quantitative Reasoning
Prerequisite: MATH 251
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MATH 370 - Probability I
Credits: Three (3)
This is the first in a sequence of two one-semester courses on probability. Topics include basic probability concepts, conditional probability, Bayes Theorem, distribution of random variables; moments, moment generating functions, percentiles, mode, skewness, univariate transformations, discrete distributions (binomial, uniform, hypergeometric, geometric, negative binomial, Poisson), and continuous distributions (uniform, exponential). MATH 370 and MATH 371 (along with Calculus) cover all of the learning objectives contained in Examination P (Probability) of the Society of Actuaries.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-151 or AP Calculus
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MATH 372 - Mathematical Statistics
Credits: Three (3)
This course introduces students to basic concepts of inference and main methods of estimation. Topics include statistical inferences such as point and interval estimation of parameters, statistical hypotheses and statistical tests; inferences for single samples; inference for two samples; inferences for proportion and count data; and advance estimation methods including Moment, percentile matching and Maximum Likelihood. This course emphasizes the applications of the theory to statistics and estimation. This is a calculus-based one semester course. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. Students who receive a B- or higher in this course are eligible to receive VEE (Validation by Education Experience) credit from the Society of Actuaries in Mathematical Statistics.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-371
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MATH 397 - Special Studies
Credits: Three (3)
General Education Area: Quantitative Reasoning
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MATH 405 - Statistical Modeling I
Credits: Three (3)
This course focuses on model development, interpretation, understanding assumptions and evaluation of competing models. Topics include simple and multiple linear regressions, hypothesis testing, confidence intervals in linear regression models, testing of models, data analysis and appropriateness of models, linear time series models, moving average, autoregressive and ARIMA models, estimation, data analysis and forecasting with time series models, forecast errors and confidence intervals. This course is intended to cover a majority of the learning objectives for Society of Actuaries (SOA) examination SRM (Statistics for Risk Modeling).
General Education Area: Quantitative Reasoning
Prerequisite: MATH 371
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MATH 406 - Statistical Modeling II
Credits: Three (3)
MATH 406 and ACSC 407 cover the learning objectives from Examination STAM (Short-Term Actuarial Models) of the Society of Actuaries. Topics include constructing empirical models; estimating the parameters of failure time and loss distribution using different methods such as maximum likelihood method of moments, Kaplan-Meier estimator, Nelson- Aalen estimator and kernel density estimators; determining the acceptability of a fitted model; comparing models using graphical procedures, Kolmogorov-Smirnov test, Chi-square goodness of fit test, likelihood ratio test, Schwarz Bayesian criterion, and Akaike Information criterion.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-371
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MATH 420 - Statistics for Science Research
Credits: Three (3)
This course covers research methods, design and statistical analysis for Biology, Chemistry, Physics and other sciences research questions. Topics includes the analysis of variance, regression models, factorial designs, fractional factorial designs, response surface methodology, nested and split-plot designs, the non-normality of response and the Box-Cox method for selecting the form of a transformation.
General Education Area: Quantitative Reasoning
Cross-listed: MATH-520
Prerequisite: MATH-141
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MATH 430 - Fundamental Analysis
Credits: 3
The fundamental Analysis course will cover topics both in real analysis and complex analysis. Topics covered in real analysis include properties of the real numbers, ideas of sets, functions, theory of limits, metric spaces, continuous functions, differentiation, Riemann integration, the method of successive approximations, partial differentiation, and multiple integrals. Topics in complex analysis will cover complex numbers, complex plane with particular emphasis on Cauchy’s Theorem and the calculus of residues.
Prerequisite: MATH-251
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MATH 450 - Matrix Applications
Credits: Three (3)
Matrix and Data frames are essential components of Data analysis and Machine Learning. This course provides a nice head start to students with concepts of matrix computations. Topics covered: Matrix multiplication, Matrix Analysis such as Vector Norms, Matrix Norms, Subspace Matrices and Finite Precision Matrix Computation. Other topics includes Triangular systems, Guassian Elimination, Pivoting, Topics in Special Linear Systems, and Functions. Every chapter is supported by intuitive practice problems. The pseudo codes are available in Matlab.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-316
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MATH 460 - Optimazation
Credits: Three (3)
Optimization is an essential and important technique for solving problems in many disciplines. Topics covered will be linear programming, infeasible linear programming, unbounded linear programming, pivoting and tableaus, integer programming, solving optimization problems on graphs, shortest path problem, minimum cost perfect matching, understanding the formulation of nonlinear programming, traveling salesmen problem. Modern, real-world examples motivate the theory throughout the course. Students will use MATLAB and work on projects to better understand concepts learned.
General Education Area: Quantitative Reasoning
Prerequisite: MATH-316
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MATH 470 - Introduction to Abstract Algebra
Credits: 3
A first introduction to abstract algebra through group theory with an emphasis on concrete examples. The course will introduce groups, subgroups, homomorphisms, quotients groups and prove foundational results including Lagrange’s theorem, Cauchy’s theorem, orbit-counting techniques and the classification of finite abelian groups. The concepts of ring and field will be introduced.
Prerequisite: MATH-316
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MATH 497 - Special Studies
Credits: One (1) to Four (4)
General Education Area: Quantitative Reasoning
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MATH 505 - Statistical Modeling I
Credits: Three (3)
This course focuses on model development, interpretation, understanding assumptions and evaluation of competing models. Topics include simple and multiple linear regressions, hypothesis testing, confidence intervals in linear regression models, testing of models, data analysis and appropriateness of models, linear time series models, moving average, autoregressive and ARIMA models, estimation, data analysis and forecasting with time series models, forecast errors and confidence intervals. This course is intended to cover a majority of the learning objectives for Society of Actuaries (SOA) examination SRM (Statistics for Risk Modeling).
Note: This course is for graduate students only.
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MATH 506 - Statistical Modeling II
Credits: Three (3)
MATH 506 and ACSC 607 cover the learning objectives from Examination STAM (Short-Term Actuarial Models) of the Society of Actuaries. Topics include constructing empirical models; estimating the parameters of failure time and loss distribution using different methods such as maximum likelihood method of moments, Kaplan-Meier estimator, Nelson- Aalen estimator and kernel density estimators; determining the acceptability of a fitted model; comparing models using graphical procedures, Kolmogorov-Smirnov test, Chi-square goodness of fit test, likelihood ratio test, Schwarz Bayesian criterion, and Akaike Information criterion.
Note: This course is for graduate students only
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MATH 520 - Statistics for Science Research
Credits: Three (3)
This course covers research methods, design and statistical analysis for Biology, Chemistry, Physics and other sciences research questions. Topics includes the analysis of variance, regression models, factorial designs, fractional factorial designs, response surface methodology, nested and split-plot designs, the non-normality of response and the Box-Cox method for selecting the form of a transformation.
Note: This course is for graduate students only.
Cross-listed: MATH-420
Prerequisite: MATH-141
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MATH 570 - Probability I
Credits: Three (3)
This is the first in a sequence of two one-semester courses on probability. Topics include basic probability concepts, conditional probability, Bayes Theorem, distribution of random variables; moments, moment generating functions, percentiles, mode, skewness, univariate transformations, discrete distributions (binomial, uniform, hypergeometric, geometric, negative binomial, Poisson), and continuous distributions (uniform, exponential). MATH 370 and MATH 371 (along with Calculus) cover all of the learning objectives contained in Examination P (Probability) of the Society of Actuaries.
Note: This course is for graduate students only.
Cross-listed: MATH-370
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MATH 571 - Probability II
Credits: Three (3)
This course should be taken in sequence with MATH 370. Topics include continuous distributions and their applications; uniform distribution, exponential distribution, Gamma distribution, normal distribution and others; central limit theorem; order statistics; mixed distributions; multivariate distributions; marginal distributions; conditional distributions; joint moment generating functions; double expectation theorems. MATH 370 and MATH 371 (along with Calculus) cover all of the learning objectives contained in Examination P (Probability) of the Society of Actuaries.
Note: This course is for graduate students only.
Cross-listed: MATH-371
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MATH 572 - Mathematical Statistics
Credits: Three (3)
This course introduces students to basic concepts of inference and main methods of estimation. Topics include statistical inferences such as point and interval estimation of parameters, statistical hypotheses and statistical tests; inferences for single samples; inference for two samples; inferences for proportion and count data; and advance estimation methods including Moment, percentile matching and Maximum Likelihood. This course emphasizes the applications of the theory to statistics and estimation. This is a calculus-based one semester course. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. Students who receive a B- or higher in this course are eligible to receive VEE (Validation by Education Experience) credit from the Society of Actuaries in Mathematical Statistics.
Note: This course is for graduate students only.
Cross-listed: MATH-372
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