CMPSC 200 (GQ) Programming for Engineers with MATLAB
EDPSY 101 (GQ) Analysis & Interpretation of Statistical Data in Education
MANAGEMENT INFORMATION SYSTEMS
MIS 204 (GQ) Intro to Management Information Systems
MATH 21 (GQ) College Algebra I
MATH 22 (GQ) College Algebra II and Analytic Geometry
MATH 26 (GQ) Plane Trigonometry
MATH 34 (GQ) The Mathematics of Money
MATH 110 (GQ) Techniques of Calculus I
MATH 140 (GQ) Calculus With Analytic Geometry I
MATH 141 (GQ) Calculus with Analytic Geometry II
MATH 141B (GQ) Calculus and Biology II
MATH 141H (GQ) Honors Calculus with Analytic Geometry II
MATH 220 (GQ) Matrices 2
PSYCH 200 (GQ) Elementary Statistics in Psychology
STAT 100 (GQ) Statistical Concepts and Reasoning
STAT 200 (GQ) Elementary Statistics
SUPPLY CHAIN MANAGEMENT
SCM 200 (GQ) Introduction to Statistics for Business
Development and implementation of algorithms in a procedure-oriented language, with emphasis on numerical methods for engineering problems. A student may receive credit for only one of the following courses: CMPSC 101, 102, 200, 201, or 202. CMPSC 200 CMPSC 200 Programming for Engineers with MATLAB (3) CMPSC 200 is a service course offered to engineering and science majors. The course teaches basic programming concepts including: algorithm development, data types, number representation, control structures, functions, plotting and basic numerical analysis techniques. The course enables students to develop computer programs in MATLAB to solve simple engineering problems. The basic numerical analysis techniques covered in the course include matrix operations, systems of equations, solving equations, roots, curve fitting, interpolation, numerical integration and ordinary differential equations.Students analyze physics-based and engineering problems; develop algorithms to solve the problems; implement the algorithms in the MATLAB programming environment; and produce informative output in both numerical and graphical form. The general programming concepts learned in the course are commonly found in most programming language environments. The problem-solving skills learned in the course can be utilized in upper-level engineering and science courses. The lecture portion of the course gives students the conceptual and syntactical background needed for the successful completion of practical programming assignments during the laboratory portion of the course. The laboratory instruction involves hands-on programming by individual students or student teams assisted by a teaching assistant and/or instructor. Evaluation methods may include examinations, in-class labs, and programming projects. The course is generally held in a STEC room where each student has access to a computer. The course will be offered during the Spring semester.
An introduction to quantitative methods in educational research emphasizing the interpretation of frequently encountered statistical procedures.
MANAGEMENT INFORMATION SYSTEMS
Introduction to Management Information Systems provides an overview of the role of information systems in business process design, the current technologies used for obtaining, storing, securing, and communicating information in support of operations and decision-making within a business organization, as well as, the concepts and principles for developing and using popular spreadsheet and database tools. Applications focus on the development of quantitative problem-solving skills applied to specific examples of business problems and issues found in business disciplines, including accounting, finance, marketing, supply chain operations, and general management. Problem solving skills will be reinforced by assigning problem sets to students to do on their own.
Quadratic equations; equations in quadratic form; word problems; graphing; algebraic fractions; negative and rational exponents; radicals.
Relations, functions, graphs; polynomial, rational functions, graphs; word problems; nonlinear inequalities; inverse functions; exponential, logarithmic functions; conic sections; simultaneous equations.
Trigonometric functions; solutions of triangles; trigonometric equations; identities.
This course is a very practical, real-world class. For example, you will learn how to calculate the interest/fees on your deposit account, your car loan, your credit card, and what your car payment should be. You will learn how to calculate how much you need to save from your pay to buy that large ticket item you so desperately want. To achieve the skills to calculate the above and more, this course includes, but is not be limited to, a study of simple interest, simple discount, compound interest, annuities, investments, retirement plans, credit cards, and mortgages.
Business Calculus is a critical component in the education of any business, financial, or economics professional who uses quantitative analysis. This course introduces and develops the mathematical skills required for analyzing change, and the underlying mathematical behaviors that model real-life economics and financial applications. The primary goal of our business calculus courses is to develop the students' knowledge of calculus techniques, and to use a calculus framework to develop critical thinking and problem-solving skills. The concept of a limit of a function/model is central to differential calculus; MATH 110 begins with a study of this concept, its geometric and analytical interpretation, and its use in the definition of the derivative. Differential calculus topics include: derivatives and their applications to rates of change, related rates, optimization, and graphing techniques. Target applications focus mainly on business applications, e.g. supply/demand models, elasticity, logistical growth, and marginal analysis within Cost, Revenue, and Profit models. Integral Calculus begins with the Fundamental Theorem of Calculus, integrating the fields of differential and integral calculus. Antidifferentiation techniques are used in applications focused on finding areas enclosed by functions, consumer and producer surplus, present and future values of income streams, annuities, and perpetuities, and the resolution of initial value problems within a business context. Students may only take one course for credit from MATH 110, 140, 140A, 140B, and 140H.
ICalculus is an important building block in the education of any professional who uses quantitative analysis. This course introduces and develops the mathematical skills required for analyzing change and creating mathematical models that replicate real-life phenomena. The goals of our calculus courses include to develop the students' knowledge of calculus techniques and to use the calculus environment to develop critical thinking and problem-solving skills. The concept of limit is central to calculus; MATH 140 begins with a study of this concept. Differential calculus topics include derivatives and their applications to rates of change, related rates, linearization, optimization, and graphing techniques. The Fundamental Theorem of Calculus, relating differential and integral calculus begins the study of Integral Calculus. Antidifferentiation and the technique of substitution is used in integration applications of finding areas of plane figures and volumes of solids of revolution. Trigonometric functions are included in every topic. Students may only take one course for credit from MATH 110, 140, 140A, 140B, and 140H.
MATH 141 is the second course in a two- or three-course calculus sequence for students in science, engineering and related fields. Calculus is an important building block in the education of any professional who uses quantitative analysis. This course further introduces and develops the mathematical skills required for analyzing growth and change and creating mathematical models that replicate real-life phenomena. The goals of our calculus courses include to develop the students' knowledge of calculus techniques and to use the calculus environment to develop critical thinking and problem solving skills. This course covers the following topics: logarithms, exponentials, and inverse trigonometric functions; applications of the definite integral and techniques of integration; sequences and series; power series and Taylor polynomials; parametric equations and polar functions. Students may take only one course for credit from MATH 141, 141B, and 141H.
Techniques of integration and applications to biology; elementary matrix theory, limits of matrices, Markov chains, applications to biology and the natural sciences; elementary and separable differential equations, linear rst-order differential equations, linear systems of differential equations, the Lotka-Volterra equations. Students may take only one course for credit from MATH 141, 141B, and 141H.
MATH 141 is the second course in a two- or three-course calculus sequence for students in science, engineering and related fields. Calculus is an important building block in the education of any professional who uses quantitative analysis. This course further introduces and develops the mathematical skills required for analyzing growth and change and creating mathematical models that replicate reallife phenomena. The goals of our calculus courses include to develop the students' knowledge of calculus techniques and to use the calculus environment to develop critical thinking and problem solving skills. This course covers the following topics: logarithms, exponentials, and inverse trigonometric functions; applications of the definite integral and techniques of integration; sequences and series; power series and Taylor polynomials; parametric equations and polar functions. Students may take only one course for credit from MATH 141, 141B, and 141H.
Systems of linear equations; matrix algebra; eigenvalues and eigenvectors; linear systems of differential equations. MATH 220 Matrices (2-3) (GQ) (BA) This course meets the Bachelor of Arts degree requirements.Systems of linear equations appear everywhere in mathematics and its applications. MATH 220 will give students the basic tools necessary to analyze and understand such systems. The initial portion of the course teaches the fundamentals of solving linear systems. This requires the language and notation of matrices and fundamental techniques for working with matrices such as row and column operations, echelon form, and invertibility. The determinant of a matrix is also introduced; it gives a test for invertibility. In the second part of the course the key ideas of eigenvector and eigenvalue are developed. These allow one to analyze a complicated matrix problem into simpler components and appear in many disguises in physical problems. The course also introduces the concept of a vector space, a crucial element in future linear algebra courses. This course is completed by a wide variety of students across the university, including students majoring in engineering programs, the sciences, and mathematics. (In case of many of these students, MATH 220 is a required course in their degree program.)
This course provides an introduction to the descriptive and inferential statistics commonly used in psychology, and to hypothesis testing as a method of scientific investigation. It also explores the ways in which the assumptions of statistical tests place constraints on experimental design and, conversely, how the design of experiments can dictate the statistical test appropriate for data analysis. The ability to understand and perform statistical analyses, and to evaluate the match between statistical analysis and experimental procedures, is critical to reading and understanding the empirical research that psychology is based upon, and that will be covered in upper-level psychology courses such as PSYCH 301W, for which PSYCH 200 is a pre-requisite, most 400-level courses, and certain lower-level psychology courses. In addition to performing some statistical tests by hand, students may also conduct statistical tests via statistical software packages commonly used by psychologists, such as SPSS or R. Finally, this course will include material on the responsible and effective communication of statistical results to a scientific audience according to APA guidelines. Specific topics covered include probability theory, scales of measurement, measures of variability and central tendency, normal curves, graphical displays (e.g., histograms, bar charts), the relation between samples and populations, correlations, simple regression, basic mean differences tests (e.g., t-tests), effect sizes, and confidence intervals. Classes may also cover z-tests, simple and factorial ANOVA, non-parametric tests (e.g., Chi Square, Mann-Whitney U, Wilcoxon), statistical power, or other statistical techniques commonly used in psychology.
Statistics is the art and science of decision making in the presence of uncertainty. The purpose of Statistics 100 is to help students improve their ability to assess statistical information in both everyday life and other University courses. Topics covered include methods for collecting and summarizing data, analyzing the relationship between variables, and using basic probability concepts to draw conclusions about populations based on data. The course is less technical and more conceptual than Statistics 200. Statistical concepts and interpretations will dominate over techniques and calculations, but students should be comfortable working with fractions and square roots.
Descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation. STAT 200 Elementary Statistics (4) (GQ) (BA) This course meets the Bachelor of Arts degree requirements. STAT 200 is a standard first course in statistics. Students who have successfully completed this course will understand basic concepts of probability and statistical inference, including common graphical and numerical data summaries; notions of sampling from a population of interest, including the sampling distribution of a statistic; construction and interpretation of confidence intervals, test statistics, and p-values; and connections between probabilistic concepts like the normal distribution and statistical inference. They will recognize various types of data, appropriate statistical methods to analyze them, and assumptions that underlie these methods. They will also gain extensive experience in the use of statistical software to analyze data and the interpretation the output of this software.
SUPPLY CHAIN MANAGEMENT
SCM 200 introduces basic statistical concepts and models within the framework of business problems and applications. Students learn about the usefulness of business statistics to decision making, how to perform basic statistical and analytical procedures, and how to interpret, critically evaluate, and analyze data. Special emphasis is given to active learning methods.