MAS105. Quantitative Methods in Business I. 3 Credit Hours.
This course provides a background in algebra, linear equations, matrices, quadratic, exponential, and logarithmic functions appropriate for the successful understanding, interpretation, and use of these concepts and their application to business and economics within the Business School curriculum and in career endeavors. The course also provides an introduction to the mathematics of finance, interest rates, discounting of future returns, and linear programming.
Components: LEC.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS110. Quantitative Applications in Business. 3 Credit Hours.
Review of algebra emphasizing its application to supply and demand functions, market equilibrium, compound interest, and amortization. Differential calculus emphasizing its applications to marginal cost and revenue functions, maximization, taxation in competitive markets, and elasticity of demand are discussed. The application of integral calculus to total cost and profit of demand, to total cost and profit functions, consumer's and producer's surplus, computation of present value, and constrained optimization using partial differentiation are also included.
Requisite:Mia Herbt Bus Schl And Prerequisite: ALEKS score>=76 Or SAT MTH score >=700 Or SAT Mth Section Score>=730 Or ACT Mth score>=31 Or score of 4 AP Calculus (AB) Or score of 3 in AP Calculus (BC) Or MTH108 or MTH107 with a grade of C- or higher.
Components: LEC.
Grading: GRD.
Typically Offered: Fall, Spring, & Summer.
MAS201. Introduction to Business Statistics. 3 Credit Hours.
Data analysis and presentation, cross tabulations, descriptive statistical measures, probability, sampling, statistical inference, hypothesis testing for one and two populations, covariance and correlation analysis. Utilization of microcomputer statistical packages is also included.
Prerequisites: MAS110 or MTH130 or MTH141 or MTH151 or MTH161 or MTH171.
Components: LEC.
Grading: GRD.
Typically Offered: Fall, Spring, & Summer.
MAS202. Intermediate Business Statistics. 3 Credit Hours.
Chi-squared goodness of fit tests, and contingency tables, analysis of variance, simple linear regression, multiple regression, time series, forecasting, statistical methods of quality. Utilization of microcomputer statistical packages, case analyses, and presentations are also included.
Prerequisite: MAS201 or MAS311 or MTH224 or ISE311 or PSY291 or PSY292 and Requisite: Miami Herbert Business School.
Components: LEC.
Grading: GRD.
Typically Offered: Fall, Spring, & Summer.
MAS311. Applied Probability and Statistics. 3 Credit Hours.
Descriptive statistics, basic probability, probability distributions, distribution theory, point and interval estimation, and single sample hypothesis testing.
Prerequisite: MTH162 or MTH172. Or Corequisites: MTH162 or MTH172 including equivalents.
Components: LEC.
Grading: GRD.
Typically Offered: Fall & Spring.
MAS312. Statistical Methods and Quality Control. 3 Credit Hours.
Two sample hypothesis testing, simple and multiple regression, analysis of variance, design of experiments, and statistical quality control.
Prerequisite: MAS311 or ISE311 or Equivalent and Requisite: Miami Herbert Business School.
Components: LEC.
Grading: GRD.
Typically Offered: Fall & Spring.
MAS332. Data Acquisition, Preparation and Visualization. 3 Credit Hours.
This course provides an in depth view of working with data to extract and present valuable information. Students will learn to collect, clean, manipulate, analyze, and visualize data from various sources correctly and efficiently. Through hands-on application, students will gain an understanding of what problems can occur when dealing with a variety of data and what solutions exist. Computing is a major component of this course, and students will learn a number of in-demand technical skills.
Prerequisite: MAS202 or MAS312.
Components: LEC.
Grading: GRD.
Typically Offered: Fall.
MAS342. Introduction to Optimization and Decision Making. 3 Credit Hours.
This course introduces the principles and techniques of applied mathematical programming and computational methods for managerial decision-making. Computer software will be used extensively to solve both small-scale and large-scale optimization problems. The course covers theory and applications of Linear Programming, Mixed Integer Programming, Binary Programming, Non-linear Programming, Network Optimization.
Prerequisite: MAS201 or MAS311.
Components: LEC.
Grading: GRD.
Typically Offered: Fall.
MAS352. Sports Analytics. 3 Credit Hours.
In this course students investigate questions that sports organizations face in business operations (ticketing, pricing, sales, and finance), and in team operations (scouting, coaching, and player personnel). Students will learn statistical and machine learning techniques such as mixed-effects regression models, random forests, neural networks, clustering, and support vector machines. Focus of the course will be on data management, data visualization, predictive modeling, forecasting, as well as written and verbal communication of the results of analysis. The programming language R will be used extensively in this course.
Prerequisite: MAS332.
Components: LEC.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS432. Data Analysis. 3 Credit Hours.
This course introduces students to the analysis of various data types, with an emphasis on interpreting and communicating result. The course begins with linear regression modeling of normally distributed outcomes, and extends the concepts to other important data types frequently encountered in practice. Students will gain a firm understanding of a wide range of statistical models, when each is appropriate, and how to implement, interpret, and communicate results.
Prerequisite: MAS202 or MAS312 or ISE312 or equivalent.
Components: LEC.
Grading: GRD.
Typically Offered: Spring.
MAS442. Stochastic Models in Operations Research. 3 Credit Hours.
Introduction to probabilistic models and their applications. Topics include inventory theory, stochastic processes (queuing systems, Markov chains), and computer simulation. Lecture, 3 hours.
Prerequisite: MAS311 or ISE311 or equivalent.
Components: LEC.
Grading: GRD.
Typically Offered: Spring.
MAS496. Directed Studies in Business Analytics. 1-3 Credit Hours.
Supervised readings, individual research project, or independent investigation of selected non-STEM related problems in the discipline. Offered only by special arrangement with supervising faculty member, who approves topic and evaluation process at time of registration.
Components: THI.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS497. Directed Studies in Business Analytics. 1-3 Credit Hours.
Supervised readings, individual research project or independent investigation of selected STEM-related problems in the discipline. Offered only by special arrangement with supervising faculty member, who approves topic and evaluation process at time of registration.
Components: THI.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS498. Special Topics in Business Analytics. 3 Credit Hours.
Special topics in selected non-STEM areas of Business Analytics.
Requisite: Sophom*ore Standing or Higher.
Components: LEC.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS499. Special Topics in Business Analytics. 3 Credit Hours.
Special topics in selected STEM areas of Business Analytics.
Requisite: Sophom*ore Standing or Higher.
Components: LEC.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS547. Computer Simulation Systems. 3 Credit Hours.
Introduction to discrete-event computer simulation and hands-on development of simulation models. Topics include introduction to queuing theory, input and out put analysis, random number generation, and variance reduction techniques. Students practice their modeling skills using commercial state-of-the-art simulation software. Assigned readings of real-life simulation projects complement the material learned in the classroom. Lecture, 3 hours.
Prerequisite: MAS311 or ISE311 or equivalent.
Components: LEC.
Grading: GRD.
Typically Offered: Fall.
MAS548. Machine Learning for Analytics. 3 Credit Hours.
An introduction to the principles and techniques of machine learning. Topics covered include the machine learning process, data preprocessing, common machine learning techniques and methods for evaluating model performance. The course will involve a combination of lectures, labs, projects and case studies.
Prerequisite: MAS432.
Components: LEC.
Grading: GRD.
Typically Offered: Spring.
MAS549. Big Data Analytics. 3 Credit Hours.
As firms have the ability to access and store large amounts of customer and business data, they are faced with the complexities associated with Big Data. This class will discuss the challenges and potential solutions in working with Big Data through use cases and applications. Hands-on tools and methodologies that are needed when handling, visualizing, and/or analyzing Big Data to solve business critical questions will be presented.
Prerequisite: MAS332 and MAS432.
Components: LEC.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS550. Management Science Internship. 1-3 Credit Hours.
Student is individually assigned to operating business firm or other organization to gain insight into management practice in area of career interest. Periodic reports and conferences are required. Permission of departme nt chair is required prior to registration.
Components: LEC.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS551. Business Analytics Capstone. 3 Credit Hours.
The goal of the Business Analytics Capstone course is to apply the skills learned throughout the undergraduate degree in Business Analytics to a single data analytics project. Students will work in groups on a project assigned to them by the instructor. Project topics will vary depending on availability, but reasonable efforts will be made to match projects with student interest. The project will expose students to the entire spectrum of Business Analytics; from initiating a project and defining the scope and goals, to data collection, cleaning, and exploration, to modeling and suggesting recommendations based on results. Along the way, students will practice effectively communicating with stakeholders who may or may not be familiar with the complex analytical methods implemented.
Prerequisite: MAS332 and MAS342 and MAS432.
Components: EXP.
Grading: GRD.
Typically Offered: Offered by Announcement Only.
MAS555. Management Science Departmental Honors Research Project.. 3 Credit Hours.
Research project to fulfill requirements for Departmental Honors in Management Science.
Components: THI.
Grading: SUS.
Typically Offered: Offered by Announcement Only.
