ACCT.2010 Accounting/Financial (3cr)
Presents a comprehensive, detailed exposure to basic accounting theory. Beginning with the accounting equation, students are introduced to the accounting cycle, preparation of the statement of financial position and the income statement, accounting for assets, liabilities, and stockholders' equity of the firm, and cash flow and financial statement analysis.
COMP.1010 Computing I (3cr)
Introduction to computing environments: introduction to an integrated development environment; C, C++, or a similar language. Linear data structures; arrays, records, and linked lists. Abstract data types, stacks, and queues. Simple sorting via exchange, selection, and insertion, basic file I/O. Programming style documentation and testing. Ethical and social issues. Effective Fall 2013, Co-req 91.103 Computing 1 Lab.
COMP.1020 Computing II (3cr)
Computing II focuses on the implementation and applications of data structures, including arrays, linked lists, stacks, queues, trees, binary trees, binary search trees, heaps, graphs, and hash tables. Recursive approaches are used. Performance analysis is discussed. Attention is paid to programming style, documentation, and testing. This course includes extensive laboratory work. Effective Fall 2013, Co-req: Computing 2 Lab.
COMP.1030L Computing I Lab (1cr)
This is the lab class for COMP.1010 Computing I. This class must be taken with COMP.1010 Computing I in the same semester.
COMP.1040L Computing II Lab (1cr)
This is a lab class for 91.102 Computing II. This class must be taken with 91.102 Computing II in the same semester.
Requirements:
COMP.1020 Co-req.
ECON.2010 Principles of Microeconomics (3cr)
Studies the principles of production and exchange. An introduction to demand, supply, pricing, and output under alternative market structures. Derived demand and resource markets are introduced. Meets Core Curriculum Essential Learning Outcome for Quantitative Literacy (QL).
ECON.2020 Principles of Macroeconomics (3cr)
This course studies national accounts, inflation, and aggregate unemployment, as well as the driving forces behind business cycles and long-run growth in the context of aggregate demand and aggregate supply. In addition, it examines monetary and fiscal policy, the Federal reserve, and select additional topics, such as an introduction to open-economy macroeconomics.
ENGL.1010 College Writing I (3cr)
A workshop course that thoroughly explores the writing process from pre-writing to revision, with an emphasis on critical thinking, sound essay structure, mechanics, and academic integrity. Students will read, conduct rhetorical analyses, and practice the skills required for participation in academic discourse. Students will write expository essays throughout the semester, producing a minimum of four formal essays.
ENGL.1020 College Writing II (3cr)
A workshop course that thoroughly explores the academic research writing process with an emphasis on entering into academic conversation. Building on the skills acquired in College Writing I, students will learn to write extensively with source material. Key skills addressed include finding,assessing, and integrating primary and secondary sources, and using proper documentation to ensure academic integrity. Students will produce analytical writing throughout the semester, including a minimum of four formal, researched essays.
FINA.3010 Financial Management (3cr)
Principles of financial management, including working and fixed capital, sources of funds, financial statements, financial planning and capital structure.
Requirements:
ECON2010, ACCT2010 pre; BU min
FINA.3210 Investment and Portfolio Analysis (3cr)
This course is a survey of investments for business students. Topics include the investment environment, markets and instruments, securities trading, market indexes, risk, diversification, the capital asset pricing model, market efficiency, introductory valuation of bonds stocks options and futures, mutual funds, behavioral finance, and strategies for individual investors. Meets Core Curriculum Essential Learning Outcome for Critical Thinking & Problem Solving (CTPS) and Information Literacy (IL).
FINA.3310 Principles of Corporate Finance (3cr)
Advanced study of the principles of financial analysis. Covers topics such as acquisition of long-term assets, capital budgeting models, and the analysis of mutually exclusive projects.
Requirements:
FINA.3110 pre-req
INFO.2030 Introduction to Programming with Python (3cr)
This course examines the fundamentals of computer programming while using the Python programming language. Python is a popular scripting language that is commonly used for a myriad of applications including machine learning, scientific computing, scripting, web applications, and data processing. Course topics will include programming fundamentals, such as Boolean logic, program organization, input and output, and loops. We'll cover the syntax of Python (the rules that govern the language) as well as industry standards best practices.
INFO.2110 Introduction to Programming W/C I (3cr)
Offers an introduction to the processing of information by computer. Computer logic, memory, input/output processing, and programming in the 'C' language.
Students may not receive credit for both the INFO.2110/INFO.2120 sequence and INFO.2670. 3 credit(s).
Prerequisite: No previous programming experience
required.
Notes:
Students may not receive credit for both the 90.211/90.212 sequence and 90.267
This course qualifies for free MSDNA software!
Requirements:
No previous programming experience required
INFO.2120 Introduction to Programming with C - Part II (3cr)
Serves as a continuation of INFO.2110. Additional topics will include pointers, dynamic memory allocation, file handling techniques and libraries. Students may not receive credit for both the INFO.2110/INFO.2120 sequence and INFO.2670.
Notes:
Students may not receive credit for both the 90.211/90.212 sequence and 90.267. This course qualifies for
free MSDNA software
Requirements:
INFO.2110
INFO.2670 C Programming (3cr)
Introduces students to the techniques of programming in C. The language syntax, semantics, its applications, and the portable library are covered. This course is an introductory course in programming. It does not assume previous programming experience.
Notes:
Students may not receive credit for both the
INFO.2110/INFO.2120 sequence and INFO.2670
This course qualifies for
free MSDNA software!
INFO.2680 C++ Programming (3cr)
This course will cover the C++ language and show the student how to use the language. We will cover class construction, operator overloading, virtual functions, templates, and introduce the student to the IO streams. Inheritance and its use in creating extendible libraries will be presented. Object-oriented concepts will be presented in the context of the C++ language and its support for object-oriented programming.
Notes:
This course qualifies for
free MSDNA software!
Requirements:
P: INFO.2670 or INFO.2120; requires C++ compiler software
INFO.2820 Python Programming (3cr)
This course introduces the fundamentals of Python including data types, expressions, control structures, file input and output, lists, dictionaries, functions, object oriented program design, simple graphics development, and the development of Graphical User Interfaces (GUIs) in Python. Students will problem solve, explore real-world software development challenges, and create practical and contemporary applications. This course assumes previous programming experience.
INFO.3600 Intro. to Data Structures with C (3cr)
This course introduces students to the fundamental concepts of data structures such as stacks, queues, linear and linked lists, trees, graphs, hashing, etc., using the C programming language. Algorithms for manipulating these structures, such as sorting and searching techniques, will also be covered.
Requirements:
INFO 2670 C Programming or INFO 2120 Intro to Programming with C- part II.
INFO.3640 Problem Solving with C (3cr)
Intended as a practical problem-solving course, to give students further exposure to the topics covered in 90.267 and to provide the tools needed for software development. The course emphasizes these aspects of the programming problem-solving process: problem specification and organization; algorithms, coding, debugging; the elements of good programming style; and the means of producing a high-quality finished product. Programming examples are chosen to span a wide range of both numeric and nonnumeric applications.
Notes:
This course qualifies for
free MSDNA software!
Requirements:
INFO.2120 or INFO.2670; requires Ansi C/C++ compiler software
MATH.1020 Freshman Seminar in Mathematics (1cr)
This course is designed to orient undergraduate math majors to the university and to their chosen field. Students will learn about the mathematics program, the mathematics faculty and their research interests, careers in math-related areas, internship opportunities, and university resources.
MATH.1310 Calculus I (4cr)
Serves as a first course in calculus. Functions, limits, continuity, derivatives, rules for differentiation of algebraic and transcendental function; chain rule, implicit differentiation, related rate problems, linearization, applied optimization, and curve sketching. Introduction to area and integration. Students are expected to have taken pre-calculus and trigonometry in order to be successful in this course.
Requirements:
Current ALEKS math placement 76-100, or MATH.1230 Precalculus II with a grade of 'C-' or higher.
MATH.1320 Calculus II (4cr)
Serves as a continuation of Calculus I. Integration and techniques of integration including the substitution method, integration by parts, trigonometric integrals, trigonometric substitution, integration of rational functions by partial fractions, numerical integration, and improper integrals. Volumes using cross-sections, the disk method, the washer method and the shell method. Arc length and surface area. Infinite series, power series, Maclaurin and Taylor series. Polar coordinates and areas and lengths in polar coordinates.
Requirements:
Pre-Req: MATH 1290 Calculus IB, MATH 1310 Calculus I, or a grade of CR in NONC CALC1.
MATH.2190 Discrete Structures I (3cr)
Presents propositional logic, combinatorics, methods of proof, mathematical systems, algebra of sets, matrix algebra, relations and functions, recursion and generating functions, applications to computer science, and graph theory.
Notes:
Formerly MATH.3210
MATH.2210 Introduction to Linear Algebra (3cr)
Elementary set theory and solution sets of systems of linear equations. An introduction to proofs and the axiomatic methods through a study of the vector space axioms. Linear analytic geometry. Linear dependence and independence, subspaces, basis. Inner products. Matrix algebra. Applications of the above will also be discussed.
Requirements:
MATH 1320 pre-req
MATH.2310 Calculus III (4cr)
Extends the concepts of Calculus I and II that deal with functions of a single variable to multi-variable functions, vector-valued functions and vector fields. Vectors and vector-valued functions, the dot and cross products, curves in space and the calculus of vector-valued functions. Multi-variable functions, limits, continuity, and differentiation. Partial derivatives, directional derivatives, the gradient, Lagrange multipliers and optimization. Double and triple integrals in Cartesian, polar and spherical coordinates. Vector fields and the fundamental theorems of vector calculus developed, line and surface integrals, Green's theorem, Stokes's theorem, and the divergence theorem.
Requirements:
MATH.1320 Calculus II, or MATH.2250 Calculus C.
MATH.2720 Introduction to Programming with MATLAB
This course will introduce basic programming concepts using MATLAB as the programming environment. Topics include an introduction to MATLAB, array manipulation, graphics, script files, data input and output, relational and logical operators, conditional statements, loops, and iterative procedures. Additional topics will be discussed as time permits. Additional topics will be chosen from the following: finding roots of nonlinear equations, random number generation, Markov processes, simple statistics, interpolation, and the basics of Fourier analysis.
MATH.3230 Introduction to Proofs (3cr)
This course will focus on reading and writing mathematics. Students will learn how to analyze and interpret mathematical statements and understand the reasoning behind these statements. They will also learn how to convey mathematical ideas and write proofs using precise language, correct logic, and other important elements.
Requirements:
MATH.2190 Discrete Structures I.
MATH.3750 Senior Seminar I (1cr)
Student works with an advisor to develop a proposal for a senior project that will be carried out as part of MATH.4750 Senior Seminar II. Generally taken during the spring of the junior year. Prerequisite: Permission of instructor.
MATH.3850 Applied Statistics (3cr)
Introduction to experimental design, data analysis and formal statistical procedures from an applied point of view.
Requirements:
MATH 1320 pre-req
MATH.4070 Probability and Mathematical Statistics I (3cr)
Addresses the topics of probability, random variables, discrete and continuous densities, expectation and variance, special distributions (binomial, Poisson, normal, etc.), moment generating functions, joint and conditional distributions, transformations of variables, sampling, and the central limit theorem.
Requirements:
MATH 2310, or MATH 2260, and 9
MATH.4190 Mathematica (3cr)
A project -based course starting with an introduction to the basic features of Mathematica. A project that allows the student to focus on certain features in more detail is required and occupies the second half of the course.
MATH.4660 Stat Program Using SAS (3cr)
An introduction to creation and manipulation of databases and statistical analysis using SAS software. SAS is widely used in the pharmaceutical industry, medical research and other areas. Cannot be used as a Math Elective.
Requirements:
MATH.3860 or equivalent
MATH.4750 Senior Seminar II (3cr)
Undergraduate seminar on advanced mathematical topics. Students are required to develop an understanding of an advanced subject beyond the scope of an existing course or synthesize two or more different areas form their curriculum. Students are required to participate in the seminar, present their results to the Department and write a substantial thesis in their topic area. Essential course elements include library research, original research, and both verbal and written exposition. The first semester is a graduation requirement for majors in mathematics.
Notes:
Senior Status Math majors
MATH.4860 Probability and Math Statistics II (3cr)
Point estimation, confidence intervals, hypothesis testing. Two-sample t-test. Correlation and linear regression. The bivariate normal distribution. Analysis of variance for one-and two-way designs. F tests. Nonparametric methods. Chi-squared tests for contingency tables. Generalized likelihood ratio. C.R. bound. Consistency.
Requirements:
MATH.4070 pre-req.
MATH.5750 Applied Statistics with R (3cr)
This is a methods course focusing on the applications of statistics using R programming language. Topics include: Study designs, review of inference and regression, categorical data, logistic regression, rates and proportions, and nonparametric methods. Additional topics may be considered if time permits. Only on of 92.575(R) and 92.576(SAS) may be applied toward a Masters degree in Mathematics.
Requirements:
MATH.5910 Linear Statistical Modeling & Regression.
MATH.5760 Statistical Programming using SAS (3cr)
An introduction to creation and manipulation of databases and statistical analysis using SAS software. SAS is widely used in the pharmaceutical industry, medical research and other areas.
MATH.5910 Linear Statistics Modeling and Regression (3cr)
Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience in linear model building on real data sets. Prerequisite: Probability, Biostatistics, or Statistics for Engineering and Science.
MATH.5930 Experimental Design (3cr)
How to design, carry out, and analyze experiments. Randomized block designs, randomization, blocking, matching, analysis of variance and covariance, control of extraneous variables.