2017-2018 Academic Catalog 
    
    Jun 17, 2024  
2017-2018 Academic Catalog [Archived Catalog]

Courses


Undergraduate Prerequisites Course Numbering
A “C-” or higher is required in all prerequisite courses 100-299 - Lower division undergraduate
  300-499 - Upper division undergraduate
  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.

 

 
  
  • MATH 371 - Mathematical Statistics II


    Credits: Three (3)
    Prerequisite: MATH/ACSC-370
    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.

     
    Note: Note: The course is calculus-based.
    Cross-listed: ACSC-371

  
  • MATH 372 - Mathematical Statistics III


    Credits: Three (3)
    Prerequisite: MATH/ACSC-371
    This is the third course of the mathematical statistics sequence. Topics include basic concepts of inference 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; simple linear regression and advance estimation methods including Moment, Maximum Likelihood, and Bayesian Estimation.
    Note: Note: The course is calculus-based.
    Cross-listed: ACSC-372
  
  • MATH 399 - Internship


    Credits: Three (3)
    Prerequisite: MATH-299
    This internship course is designed for math and data science students to integrate math and data science academic to the corresponding professional through internship experiences. Students will work on internship related projects, and have a midterm report and a final internship project under the guidance of supervisor on site and faculty.
  
  • MATH 405 - Statistical Modeling I


    Credits: Three (3)
    Prerequisite: ACSC/MATH 371
    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.
    Cross-listed: ACSC-405
  
  • MATH 406 - Statistical Modeling II


    Credits: Three (3)
    Prerequisite: MATH/ACSC-405
    This course covers the content of the actuarial exam C. 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.
    Cross-listed: ACSC-406
  
  • MATH 408 - Machine Learning


    Credits: Three (3)
    Prerequisite: MATH 302 or MATH 303
    This course covers hot topics in machine learning using R/Python. Topics include regression splines, generalized additive models, tree based models, support vector machines, principal components analysis and clustering methods. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.
  
  • MATH 412 - Predictive Modeling


    Credits: Three (3)
    Prerequisite: ACSC/MATH 372
    Statistical modeling will be a powerful (and critical) tool for the next generation of actuarial scientists, as well as professionals working in other fields that deal with large amounts of data (e.g. health care, bioinformatics, biotechnology and chemical engineering). Many disciplines have developed tools that allow the generation of massive amounts of data, and the ability to use statistical modeling to analyze this data is in high demand. This course will prepare students with the fundamental statistical techniques and real life examples. Generalized linear model will be the focus, but advanced models, such as CART and data clustering, will be discussed as well. Students will gain a thorough understanding of predictive modeling and its applications (in particular in the field of insurance), and will be well prepared for professional work.
    Cross-listed: ACSC 412
  
  • MATH 496 - Independent Study


    Credits: One (1) to Four (4)
  
  • MATH 497 - Special Studies


    Credits: One (1) to Four (4)
  
  • MATH 498 - Seminar


    Credits: Three (3)
    The course covers the historical development of mathematics involves some degree of understanding of the mathematics. Students will be expected to read more than traditional mathematics courses in order to gain insight into several areas of mathematics and relevant historical perspectives. Projects and presentations will be required for the courses.

     

  
  • MATH 499 - Internship


    Credits: Three (3)
    Prerequisite: MATH 399
    This Internship course is designed for math and data science students to integrate math and data science academic to the corresponding professional through internship experiences. Students will have an internship research presentation under the guidance of supervisor on site and faculty.
  
  • MATH 501 - Mathematical Modeling with Tech


    Credits: Three (3)
    Prerequisite: MATH 151
    The course focuses on business applications including finance, statistics, and mathematical modeling. It covers Microsoft Excel skills and Visual Basic Applications. A variety of real-life problems will provide the context for developing spreadsheet proficiency, including functions and formulas, statistical analysis, numerical solutions, optimization, and graphical output. This is a “hands-on” course that is supplemented by guest lecturers and various team projects.
    Note: This course is for graduate students only.
  
  • MATH 502 - Introduction to R


    Credits: Three (3)
    Prerequisite: MATH/ACSC 151
    This course covers practical issues in data analysis and graphics that includes programming in R, debugging R codes, Jupyter Notebook, cloud computing, data exploration and data visualization. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. A presentation of one project is required for the course.
    Note: This course is for graduate students only
  
  • MATH 503 - Introduction to Python


    Credits: Three (3)
    Prerequisite: MATH/ACSC 151
    This course covers practical issues in data analysis and graphics that includes programming in Python, debugging Python codes, Jupyter Notebook, cloud computing, data exploration and data visualization. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. A presentation of one project is required for the course.
    Note: This course is for graduate students only
  
  • MATH 504 - Introduction to SQL


    Credits: Three (3)
    Prerequisite: MATH/ACSC 151
    This course covers practical issues in relational database systems that includes creating database, updating data, retrieving data and saving data in database. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. A presentation of one project is required for the course.
    Note: This course is for graduate students only
  
  • MATH 505 - Statistical Modeling I


    Credits: Three (3)
    Prerequisite: ACSC/MATH 572
    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. A presentation of one project is required for the course.
    Note: This course is for graduate students only.
    Cross-listed: ACSC 505
  
  • MATH 506 - Statistical Modeling II


    Credits: Three (3)
    Prerequisite: MATH/ACSC 405
    This course covers the materials on the professional actuarial exam C. 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.  A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 506
  
  • MATH 508 - Machine Learning


    Credits: Three (3)
    Prerequisite: MATH 316
    Corequisite: MATH 316

    This course covers hot topics in machine learning using R/Python. Topics include regression splines, generalized additive models, tree based models, support vector machines, principal components analysis and clustering methods. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. A presentation of one project is required for the course.
    Note: This course is for graduate students only
  
  • MATH 510 - Risk Theory


    Credits: Three (3)
    Prerequisite: MATH/ACSC 371
    This course introduces the students to risk theory as it applies, under specified assumptions, to insurance. Topics include individual and collective risk models for single and extended periods, expense loaded premiums, liabilities and asset shares, Markov chains. A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 510
  
  • MATH 512 - Predictive Modeling


    Credits: Three (3)
    Prerequisite: ACSC/MATH 372 or 572
    Statistical modeling will be a powerful (and critical) tool for the next generation of actuarial scientists, as well as professionals working in other fields that deal with large amounts of data (e.g. health care, bioinformatics, biotechnology and chemical engineering). Many disciplines have developed tools that allow the generation of massive amounts of data, and the ability to use statistical modeling to analyze this data is in high demand. This course will prepare students with the fundamental statistical techniques and real life examples. Generalized linear model will be the main focus, but advanced models, such as CART and data clustering, will be discussed as well. Students will gain a thorough understanding of predictive modeling and its applications (in particular in the field of insurance), and will be well prepared for professional work. A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 512
  
  • MATH 514 - Theory of Interest


    Credits: Three (3)
    Prerequisite: MATH-151, Permission of Program Director
    This course covers the mathematical theory of compound interest with applications to investments. Topics include accumulation of interest in discrete and continuous time, nominal and effective interest, present and future values, and annuities. MATH 514 and MATH 515 cover all of the learning objectives contained in Examination FM (Financial Mathematics) of the Society of Actuaries. A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 514
  
  • MATH 515 - Financial Mathematics I


    Credits: Three (3)
    Prerequisite: MATH 514
    This course covers the mathematical theory of compound interest with applications to investments and corporate finance. Topics include amortization of loans sinking fund, price of bonds, amortization of premium, accumulation of discount, interest rate swaps and determinants of interest rates; the dollar weighted return, time-weighted rate of return, duration and convexity of cash flows; constructing an investment portfolio to fully immunize set of liability cash flows. MATH 514 and MATH 515 cover all of the learning objectives contained in Examination FM (Financial Mathematics) of the Society of Actuaries. A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 515
  
  • MATH 516 - Financial Mathematics II


    Credits: Three (3)
    Prerequisite: MATH 514
    This course covers financial theory, with emphasis on mathematical models, topics include the value of common stocks, risk and return, portfolio theory, capital budgeting issues, capital structure, strategic long-term financing decisions, financial statement ratio analysis and the valuation of options including the Black-Scholes formula. A project on portfolio design and analysis is required for the course. Students who get a grade of B- or better will receive credit for Corporate Finance from the Society of Actuaries. A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 516
  
  • MATH 521 - Actuarial Modeling I


    Credits: Three (3)
    Prerequisite: MATH 371 and MATH 415
    This course is the first of two courses in actuarial modeling, designed to develop students’ knowledge in the theoretical basis of actuarial models and the application of those models to insurance and other financial risks. Topics include survival models, life tables, mortality rates, life insurance, life annuities, benefit premiums, and benefit reserves.  A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 522
  
  • MATH 522 - Actuarial Modeling II


    Credits: Three (3)
    Prerequisite: MATH-521
    This course is the second part of the sequential courses in actuarial modeling to develop the student’s knowledge of the theoretical basis of actuarial models and the application of those models to insurance and other financial risks. Topics include analysis of benefits reserves, multiple life functions, multiple decrement models, frequency and severity models, compound distribution models, Poisson process models, insurance models including expenses and Markov chain models. A project on the above topics and presentation is required for the course. A presentation of one project is required for the course.
    Cross-listed: ACSC 522
  
  • MATH 572 - Mathematical Statistics III


    Credits: Three (3)
    Prerequisite: Permission of Program Director, Graduate students only
    Topics include classical basic concepts of inference, inference for single samples, inference for two samples, inferences for proportion, simple linear regression and advance estimation methods including Moment, Maximum Likelihood, and Bayesian Estimation. This course is calculus-based. A presentation of one project is required for the course.
    Note: This course is for graduate students only.
    Cross-listed: MATH-372
  
  • MATH 597 - Capstone Project


    Credits: Three (3)
    The purpose of the Capstone Project is for the students to apply theoretical knowledge acquired during the Data Science program to a project involving actual data in a realistic setting. During the project, students engage in the entire process of solving a real-world data science project, from collecting and processing actual data to applying suitable and appropriate analytic methods to the problem. The capstone project must have theoretical, creative, and applied components.
  
  • MATH 599 - Internship


    Credits: Three (3)
    This Internship course is designed for math and data science students to integrate math and data science academic to the corresponding professional through internship experiences. Students will work on internship related project, and have a midterm report and a final internship project under the guidance of supervisor on site and faculty.
  
  • MATH 607 - Credibility and Simulation


    Credits: Three (3)
    Prerequisite: ACSC-506 or MATH-506 (previous or concurrent enrollment allowed)
    The student is expected to identify steps in the modeling process. Specifically, the candidate is expected to be able to perform the tasks such as; apply limited fluctuation (classical)credibility including criteria for both full and partial credibility, perform Bayesian analysis using both discrete and continuous models, apply B, hlmann and B, hlmann-Straub models and understand the relationship of these to the Bayesian model, apply conjugate priors in Bayesian analysis and in particular the Poisson-gamma Model, apply empirical Bayesian methods in the nonparametric and semi-parametric Cases, simulate both discrete and continuous random variables using the inversion Method, estimate the number of simulations needed to obtain an estimate with a given error and a given degree of confidence, use simulation to determine the p-value for a hypothesis test, use the bootstrap method to estimate the mean squared error of an estimator, and apply simulation methods within the context of actuarial models. A presentation of one project is required for the course.

     
    Note: This course combined with ACSC 506 will cover the materials for Actuarial Professional exam C. One presentation will be needed for this course.
    Cross-listed: ACSC 607

  
  • MATH 607 - Simulation and Credibility


    Credits: Three (3)
    Prerequisite: MATH/ACSC 506
    This course provides the knowledge on construction and evaluation of actuarial models. Topics include an introduction to modeling and covers important actuarial methods that are useful in modeling, the modeling process and how to carry out these steps in solving business problems, estimation and goodness-of-fit to loss distribution models, and credibility theory.  A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 607
  
  • MATH 610 - Enterprise Risk Management


    Credits: Three (3)
    Prerequisite: Permission of Program Director
    The course defines and categorizes different types of risks an entity faces, and defines an ERM framework. Ways to measure and quantify the risk, such as (principle based) Economic Capital, Value at Risk (VaR), and stress scenarios are analyzed and compared. The course concludes with applications of these methods in a case study of an insurance company and recent regulatory developments such as ORSA (Own risk solvency assessment). A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 610
  
  • MATH 611 - Derivative Markets


    Credits: Three (3)
    Prerequisite: MATH/ACSC 415/515
    This course will cover the topic of capital market, investment vehicles, derivatives, principles and tools of risk management. After successfully completing the course, students are expected to identify and evaluate the risk and return characteristics of various types of investments, how markets operate and explain the fundamental principles of modem portfolio theory, to determine the value of cash flow streams with embedded options. A presentation of one project is required for the course.
    Note: This course is for graduate students only
    Cross-listed: ACSC 611
  
  • MATH 612 - Experimental Design


    Credits: Three (3)
    Prerequisite: MATH 316 and MATH 371
    This course covers principles of experiments and basic statistics using R/SAS. Topics include analysis of variance, different designs, analysis of covariance, mixed model, categorical data analysis , survey data analysis, sample size and power analysis and model comparison. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. A presentation of one project is required for the course.
    Note: This course is for graduate students only
  
  • MATH 613 - NoSQL Database


    Credits: Three (3)
    Prerequisite: MATH 501 or MATH 502 or MATH 503
    This course covers no-relational database on a large scale. Topics include MongoDB, Cassandra, Redis, HBase and Neo4j. Project based learnings is used to help students develop effective problem solving skills and effective collaboration skills. A presentation of one project is required for the course.
    Note: This course is for graduate students only
  
  • MATH 614 - Data Mining


    Credits: Three (3)
    Prerequisite: MATH 501 or MATH 502 or MATH 503
    This course covers text analytics extracting the useful information hidden in the unstructured text such as social media, emails and web pages using R/Python. Topics include corpus, transformations, metadata management, term document matrix, world cloud and topic models. Project based learnings is used to help students develop effective problem solving skills and effective collaboration skills. A presentation of one project is required for the course.
    Note: This course is for graduate students only
  
  • MATH 699 - Internship


    Credits: Three (3)
    This Internship course is designed for math and data science students to integrate math and data science academic to the corresponding professional through internship experiences. Students will have an internship research presentation under the guidance of supervisor on site and faculty.
  
  • MGMT 321 - Principles of Management


    Credits: Three (3)
    This course studies the basic theories and concepts of management including the evolution of management, ethics, decision making, organizational structure, motivation, communication, group dynamics and team building, planning, job design, leadership and organizational change.
  
  • MGMT 330 - Human Resource Management


    Credits: Three (3)
    Prerequisite: MGMT-321; Minimum grade C-
    This course provides an overview of the policies and procedures on personnel administration including the role of human resource professionals in organizations. It focuses on such topics as equal employment, job design, recruitment, selection, training, performance management, retention, termination and compensation.
  
  • MGMT 386 - Negotiations


    Credits: Three (3)
    Prerequisite: MGMT-321
    Course studies negotiation as a basic, generic human activity; a process used in labor-management relations, in business mergers and sales, in international affairs and in everyday activities.
  
  • MGMT 388 - Training and Development


    Credits: Three (3)
    Prerequisite: MGMT-330
    This course is designed to help managers and trainers to develop a systematic approach to training and development in organizations. It will address training needs, instructional objectives, learning styles, adult learners, training design and delivery, and evaluation of workshops. The process of active training or learning by doing is emphasized.
  
  • MGMT 470 - Interpersonal Management Skills


    Credits: Three (3)
    Prerequisite: MGMT-321
    This course will focus on further preparing the student to enter the workforce by concentrating on a greater understanding of human relations principles and practices. The ability to understand and cope effectively with today’s work and/or life issues and problems is a an important skill to master. Trends such as globalization, increasing workforce diversity, teamwork, and flat organizational structures require a greater understanding of human relations.
  
  • MGMT 472 - Business Organizational Behavior


    Credits: Three (3)
    Prerequisite: MGMT-321
    This course studies the behavior of people in work situations; includes major theories and concepts pertaining to organizational behavior, and applying these theories and concepts to organizational problems.
  
  • MGMT 473 - Global Human Resources Management


    Credits: Three (3)
    Prerequisite: MGMT-321
    The focus of this course is to develop students’ global mindset to prepare them to effectively manage human capital and to lead global teams in an increasingly interconnected business environment. The course also examines differences between countries to equip students with global cultural competency critical for successful international business relationships.
  
  • MGMT 487 - Leadership


    Credits: Three (3)
    Prerequisite: MGMT-321 and Minimum of 75 credits
    This course studies the relationship of strategic leadership and decision making to organizational effectiveness.
  
  • MGMT 493 - Cooperative Education


    Credits: One (1) to Three (3)
  
  • MGMT 496 - Independent Study


    Credits: One (1) to Four (4)
  
  • MGMT 497 - Special Topics


    Credits: One (1) to Three (3)
  
  • MGMT 499 - Internship


    Credits: One (1) to Three (3)
  
  • MGMT 597 - Special Studies


    Credits: One (1) to Four (4)
  
  • MGMT 631 - Entrepreneurship


    Credits: Three (3)
    Prerequisite: MGMT-647
    This course examines the challenges of bringing a new business and/or product to the marketplace and the strategies involved in obtaining financing. The focus is on the design of a business plan; obtaining financing from outside sources, and creating the appropriate marketing mix for success.
  
  • MGMT 640 - Human Resource Management


    Credits: Three (3)
    Prerequisite: MGMT-647
    This course is the study of human resource management (HRM) related to managing equal opportunity and diversity, personnel planning, recruiting and talent management, testing and selecting employees, training and development, performance management, compensation, ethics, retention, labor relations, collective bargaining, and safety.
  
  • MGMT 647 - Organizational Behavior and Development


    Credits: Three (3)
    Course topics include the history of management, perception and communication, motivation theory, leadership and power, group dynamics, conflict management and work design theory.
  
  • MGMT 650 - Workforce Management


    Credits: Three (3)
    Prerequisite: MGMT-647
    This course develops students’ understanding of recruitment and selection strategies, hiring aligned with organization-specific competencies, and training and recruitment methods. Students will learn to measure the costs of hiring and training, and turnover rate, all of which are central for an organization’s strategic plan.


  
  • MGMT 655 - Employment Law and Compliance


    Credits: Three (3)
    Prerequisite: MGMT-647
    This course focuses on the study of employment law regulations and how to plan and reduce legal exposure in the area of human resources.  Employment laws are extensive and vary based on many factors, including the size of an organization, its location and the type of industry in which the business operates.  The laws that apply to the majority of employers are discussed.

     

  
  • MGMT 660 - Compensation and Benefits


    Credits: Three (3)
    Prerequisite: MGMT-647
    This course examines the total compensation package with a special emphasis on employee benefits - both legally required such as workers’ compensation insurance and optional benefits such as retirement plans. The course provides students the guidelines for establishing job and pay structures while taking into account legal requirements. Other topics include compensable and economic factors influencing pay decisions, incentive pay plans, executive compensation, and compa-ratio calculation.


  
  • MGMT 670 - Interpersonal Management Skills


    Credits: Three (3)
    Prerequisite: MGMT-647
    This course will focus on further preparing the student to enter the workforce by concentrating on a greater understanding of human relations principles and practices. (Career success is a function of many facets.) The ability to understand and cope effectively with todays work and/or life issues and problems is a skill that is valued by most employers. Many trends, such as workforce diversity, flatter organizations, globalization, teamwork, workplace violence, require a greater understanding of human relations.
  
  • MGMT 687 - Leadership


    Credits: Three (3)
    Prerequisite: MGMT-647
    This course examines the current leadership literature and traces the development of leadership theory. It stresses the strategic nature of leadership and its role in contemporary organizations. Students conduct self assessments of their personal leadership skills and participate in many activities designed to develop leadership and skills in team building.
  
  • MGMT 691 - Management Policies (Capstone)


    Credits: Three (3)
    Prerequisite: BUS-643, MGMT-647, MGMT-670, ISYS-650, BUS-640, MGMT-687, MGMT-640, and ACCT-610
    This capstone course summarizes prior required curriculum in ethics, information technology, accounting and management. Using primarily a case study approach, the course integrates the components into a strategic decision-making model.
  
  • MGMT 697 - Special Studies


    Credits: Three (3)
  
  • MHA 502 - Statistics


    Credits: Zero (0)
    This course is designed to offer students the skills necessary to interpret and critically evaluate statistics commonly used to describe, predict, and evaluate data in an information driven environment. The focus is on the conceptual understanding of how statistics can be used and how to evaluate statistical data.
  
  • MHA 610 - Healthcare Industry and its Impact on Healthcare Management


    Credits: Three (3)
    The course provides an extensive overview of leadership in the U.S. health services system. The focus of the course will be on the role health services leadership plays in the delivery of healthcare services, including financial management, services utilization, regulatory compliance issues, etc. The student will explore the key theoretical and practical elements of leadership as well as current issues clarifying how the U.S. health services system is organized, managed, and financed.
  
  • MHA 615 - Healthcare Operations


    Credits: Three (3)
    Prerequisite: MHA 610
    In this course, students examine operational concepts related to delivering quality, consistent and cost-effective patient care across the healthcare system.   Students gain an understanding of the major functions of operations management, governance and organizational structures.  The course will address specific concepts related to understanding how to perform an operational assessment; taking a systems perspective on the organization and delivery of services; identifying problems and improvement opportunities using analytical techniques; and monitoring performance data to identify trends and variation based on current operations and those resulting from changes and improvements.
  
  • MHA 630 - Healthcare Human Resources & Organizational Behavior


    Credits: Three (3)
    This course provides a systematic application of the principles of organizational behavior to understanding professional roles in health services organizations.  Students will explore governance theory and structures in a healthcare setting, medical staff structures and its relationship to facility operation (credentialing, priviledging, and discinplinary processes).  Students will also examine topics in human resources including recruiting, hiring, compensation, incentives, and performance-based evaluations.
  
  • MHA 631 - Healthcare Quality and Performance Improvement


    Credits: Three (3)
    Prerequisite: MHA 615
    Quality and performance improvement is critical to the success of every healthcare organization.  Students will explore quality improvement techniques with an emphasis on the roles of patient and health professional in improving healthcare delivery, outcomes tracking, analysis, and impact on practice performance and patient care. Specific topics include clinical care, patient safety, waste and cost reduction and delivery of the most cost-effective care possible.
  
  • MHA 651 - Healthcare Law, Ethics and Risk Management


    Credits: Three (3)
    Prerequisite: MHA 615
    Students will examine legal and regulatory compliance strategies from the business perspective of health administration.  Course concepts include: licensing, certification, and accreditation requirements of health care professionals; healthcare-related criminal law and torts, consent, legal reporting, and professional liability, as well as federal and state statutes and regulations and specific mandates.  Business considerations related to privacy and security standards related to HIPAA, requirements and implementing management software, will be discussed . Students will also examine basic ethical frameworks and understand how these constructs can assist health management professionals dealing with current medical ethics and related business ethics issues.
  
  • MHA 655 - Healthcare Financial Management


    Credits: Three (3)
    Prerequisite: MHA 615
    This course applies financial principles to management within various organizations in the healthcare industry.  Topics include resource allocation, cost analysis, budgeting and funding sources.  Students will learn how financial decisions are made, reported, and implemented in health care organizations.
  
  • MHA 656 - Population Health Management


    Credits: Three (3)
    Prerequisite: MHA 615
    In this course, students will be exposed to management principles of healthcare quality and the origin, distribution and control of disease.  Theories of health behavior relevant to individual and community health promotion program planning will also be explored. Students will examine formal and informal programs and strategies used to enhance the healthcare provider’s performance, quality outcomes, and patient satisfaction.
  
  • MHA 660 - Healthcare Technology & Information Systems


    Credits: Three (3)
    Prerequisite: MHA 615
    This course provides explores the fundamentals of information technology in the healthcare industry. It includes an exploration of how information technology supports clinical services, quality improvement, and administrative functions in health services organizations.
  
  • MHA 670 - Healthcare Marketing


    Credits: Three (3)
    Prerequisite: MHA 656
    This course examines the theory, concepts, skills, and principles of marketing applied to health related organizations and networks.  Students will analyze marketing theories and methodologies applied to health care marketing, consumer decision making about health, and marketing research techniques.  Emphasis is placed on the effective use of social media and digital marketing techinques in healthcare.  The course will culminate with the development of a strategic marketing plan for a healthcare product or service.
  
  • MHA 671 - Health Policy And Economics


    Credits: Three (3)
    Prerequisite: MHA 656
    This course provides a holistic review of the application of economics and policy-making process to the roles of markets and government in health care.  Students will explore the concepts used by economists to analyze health outcomes, health behaviors, health care markets, health insurance markets, and the role of government.
  
  • MHA 675 - Healthcare Analytics


    Credits: Three (3)
    Prerequisite: MHA 660 & 656
    Big data is driving changes in healthcare industry.  In this course, students will look at the types of available healthcare data, as well as different types of analytic tools to help make meaningful decisions regarding operations and management, quality, performance improvement, outcomes assessment and marketing.  It builds upon previous knowledge of basic statistics and analytics, concepts, and tools by applying them specifically to the health care system.
  
  • MHA 676 - Healthcare Informatics


    Credits: Three (3)
    Prerequisite: MHA 660
    This course provides an indepth multi-disciplinary analysis of the strategic management of information technology in healthcare organizations. Specific topics include: electronic health records, health information exchange, the impact of information technology on quality of care and patient safety.  Students will focus on information system acquisition and the implementation process including assessing the need for information technology, cost analysis and justification, Request for Proposal (RFP) process and implementation.
  
  • MHA 680 - Introduction To Gerontology


    Credits: Three (3)
    Prerequisite: MHA 615 & 656
    This course provides a multidisciplinary perspective of the biological, psychological and sociocultural aspects of aging. An overview of the issues that significantly impact the older adult, their family and society is presented. The demographics profile of America’s older adult serves as a basis for explaining issues related to physical and mental health changes, role transitions, care and living arrangements, and the role of the older adult in our society.
  
  • MHA 681 - Assisted Living / Senior Services Management


    Credits: Three (3)
    Prerequisite: MHA 615
    This course provides an overview of the senior services industry and the different forms of senior health care and living services. Students will learn about the day-to-day management of assisted-living communities, including resident care, operations, finance and budgeting, human resources and staffing, and successful marketing and community relations. Students will also examine the future of the industry and approaches to creating next generation of assisted-living services.
  
  • MHA 685 - Managerial Epidemiology


    Credits: Three (3)
    Prerequisite: MHA 656
    This course focuses on core epidemiological concepts including measures of occurrence of health events and methods of data collection. Students will explore practical applications of epidemiology to health services planning, quality monitoring, planning, policy development, system development, finance, and underwriting.
  
  • MHA 686 - Community Health


    Credits: Three (3)
    Prerequisite: MHA 656
    This course provides an overview of the organization and structure of community health agencies and their role in population health management.   It explores political, social, environmental, economic and biological factors that determine health outcomes across populations. Students will examine various strategies to promote health, prevent disease and prolong life among populations and communities, including policy change, mass media approaches, and community-based interventions. Students will also examine the role of national and global governance in public health.
  
  • MHA 690 - Leadership And Professionalism In Healthcare


    Credits: Three (3)
    Prerequisite: This class must be taken following completion of 30 Credit Hours
    This class will prepare students to practice ethical leadership in a healthcare setting.  Students will examine identifying, monitoring and maintaining codes of professional conduct and procedures to ensure needs of staff are met.   Students will also focus on understanding the implications of ethical decisions, providing procedures to monitor the standards of behavior and accountability procedures. 
  
  • MHA 691 - Strategic Healthcare Management Capstone


    Credits: Three (3)
    Prerequisite: MHA 690
    As the culminating course in the MHA program, students will review the business and leadership fundamentals of healthcare administration plus further examination of the compelling issues defining the industry today and in the future.  Through integration and application of prior course work, students will to develop a strategic plan for a health services organization.
  
  • MIL 101 - Intro to Leadership I


    Credits: One (1) to Six (6)
    Military Science credits earned in partnership with Washington University’s ROTC Program.

    Examine the challenges and competencies that are critical for effective leadership. You will learn how the personal development of life skills such as cultural understanding, goal setting, time management, mental/physical resiliency, and stress management relate to leadership, officership, and the Army profession. MSL 101 is open to all students and enrollment does not require a commitment to join the US Army.

  
  • MIL 102 - Intro to Leadership II


    Credits: Two (2)
    Military Science credits earned in partnership with Washington University’s ROTC Program.

    Investigate leadership fundamentals such as problem-solving, listening, presenting briefs, providing feedback, and using effective writing skills. You will explore dimensions of leadership attributes and core leader competencies in the context of practical, hands-on, and interactive exercises. Learn fundamental military concepts and explore the Army’s leadership philosophy. MSL 102 is open to all students and enrollment does not require a commitment to join the US Army.

  
  • MIL 201 - Innovative Team Leadership


    Credits: Three (3)
    Military Science credits earned in partnership with Washington University’s ROTC Program.

    Explore the dimensions of creative and innovative tactical leadership strategies and styles by examining team dynamics and leadership theories. The course continues to build on developing knowledge of leadership attributes and core leader competencies through the understanding of Army rank, structure, and duties as well as broadening knowledge of land navigation and squad tactics. Enrollment in MSL 201 does not require a commitment to join the US Army.

  
  • MIL 202 - Foundations of Tactical Leadership


    Credits: Three (3)
    Military Science credits earned in partnership with Washington University’s ROTC Program.

    Develop greater self-awareness as you assess your own leadership styles and practice communication and team building skills. Examine and practice the challenges of leading teams in the complex operational environment. Study dimensions of terrain analysis, patrolling, and operation orders. Explores the dynamics of adaptive leadership in the context of military operations. Enrollment in MSL 202 does not require a commitment to join the US Army.

  
  • MIL 301 - Adaptive Team Leadership


    Credits: Three (3)
    Prerequisite: MIL-101 through MIL-202; OR attendance at the Leader’s Training Course (LTC)

    Military Science credits earned in partnership with Washington University’s ROTC Program.

    This is an academically challenging course where you will study, practice, and apply the fundamentals of Army leadership, officership, Army values and ethics, and small unit tactics. At the conclusion of this course you will be capable of planning, coordinating, navigating, motivating and leading a team or squad in the execution of a tactical mission during a classroom practical exercise (PE), a leadership lab, or during a military situational training exercise (STX) in a field environment.

  
  • MIL 302 - Applied Team Leadership


    Credits: Three (3)
    Prerequisite: MIL-301
    Military Science credits earned in partnership with Washington University’s ROTC Program.

    Continue to learn and apply the fundamentals of Army leadership, officership, Army values and ethics as you hone your leadership abilities in a variety of tactical environments and the classroom. Successful completion of this course will help prepare you for success at the ROTC Leader Development and Assessment Course (LDAC) which you will attend the summer following this course at Fort Lewis, WA. You will receive systematic and specific feedback on your leadership attributes, values and core leader competencies from your instructors, other ROTC cadre, and senior cadets.

  
  • MIL 401 - Adaptive Leadership


    Credits: Three (3)
    Prerequisite: Successful completion of the ROTC Leadership Development and Assessment Course (LDAC) or permission of the instructor

    Military Science credits earned in partnership with Washington University’s ROTC Program.

    This course focuses on practical application of adaptive leadership. Throughout the semester, students will apply the fundamentals of principles of training, the Army writing style and military decision making. Students will study the special trust reposed to Army Officers by the US Constitution and the President of the United States–a special trust given to no other civilian professions. Students will also study the Army officer’s role in the Uniform Code of Military Justice, and the counseling and development of subordinates.

  
  • MKT 360 - Principles of Marketing


    Credits: Three (3)
    Prerequisite: ENGL-104, ISYS-100, or ADGD-265
    An introduction to the concepts of marketing and their application to those engaged in marketing consumer and industrial goods and services; pricing, product planning, distribution and promotion.
  
  • MKT 361 - Consumer Behavior


    Credits: Three (3)
    Prerequisite: MKT-360
    An understanding of the psychological processes, individual differences, and environmental influences that shape consumers’ purchasing decisions is fundamental to the development of marketing strategy and tactics. This course covers the knowledge, concepts and applications of consumer behavior modeling for the purposes of developing effective communication, positioning, pricing, product development, social media, and location decisions needed for an effective marketing strategy in a competitive environment.
  
  • MKT 363 - Marketing Research


    Credits: Three (3)
    Prerequisite: MKT-360, and ISYS-241
    Marketers gather, analyze, and report information that can be used to make effective marketing decisions.Today data are captured from a variety of sources: purchasing transactions, online interactions and surveys, blogs, and a variety of marketing information systems. The information derived from the analysis of this data is used for internal reporting, marketing intelligence, marketing decision support systems, and to support competitive marketing research in general. This course will cover methods of data acquisition, statistical analysis techniques, results reporting, and decision making techniques.


  
  • MKT 364 - Professional Selling


    Credits: Three (3)
    Prerequisite: MKT-360
    This course introduces personal selling; includes the sales call techniques used, sales strategy, the psychology of selling, and the role of sales in the marketing and promotional mix.
  
  • MKT 370 - Marketing the St Louis Region


    Credits: Three (3)
    This course leaves the classroom to discover the great region of St. Louis by visiting civic leaders in their offices and learning from them first hand about marketing St. Louis to tourists, business and conventions.
  
  • MKT 373 - Interactive Marketing


    Credits: Three (3)
    Prerequisite: MKT-360
    Interactive marketing uses database marketing technology to manage customer acquisition and relationships on a one-to-one basis.The devising of integrated marketing plans that use sales calls, web-based technology, social media, telemarketing, and direct mail to find, recruit, and support customers. This course provides knowledge and skills in the use of database marketing, direct mail copy and graphics design, segmentation, mailing list construction and acquisition, and web-based marketing strategies.
  
  • MKT 375 - Services Marketing


    Credits: Three (3)
    Prerequisite: MKT-360
    Services dominate the world economy and technology evolves in dramatic ways. This course responds to the demand for new strategies and tactics. This course develops the all-important skills in marketing and managing services.


  
  • MKT 393 - Cooperative Education


    Credits: One (1) to Four (4)
  
  • MKT 461 - Social Media Marketing


    Credits: Three (3)
    Prerequisite: MKT-360
    Marketers use a wide range of proprietary social media - Facebook, YouTube, Twitter, LinkedIn, Pinterest, Digg, etc . - to communicate with customers and prospects. This courseexplores both paid and unpaid methods ofcommunication to identify prospects, build brand image, and find new customers.


  
  • MKT 470 - Sales Management


    Credits: Three (3)
    Prerequisite: MKT-360, and MGMT-321
    This course focuses on problem solving theory and techniques applied to managing a sales force.


  
  • MKT 471 - Marketing Communication


    Credits: Three (3)
    Prerequisite: MKT-360
    This course focuses on how communications tools such as advertising and promotion utilize the wide array of media including internet, broadcast and print to deliver the firm’s marketing strategy.


  
  • MKT 472 - Internet Marketing


    Credits: Three (3)
    Prerequisite: MKT-360
    This non-technical course focuses on finding profitable applications for marketing activity on the Internet. Today, most organizations depend on Internet-based marketing systems to automate sales processes, communicate with customers and prospects, manage social media relationships, advertize employment opportunities, and collect data for analytical purposes. An understanding of how to developcreative and profitable web sites, achieve operational efficiencies in service businesses, and add customer value in cyberspace are all essential to efficient marketing operations.
  
  • MKT 474 - Global Marketing


    Credits: Three (3)
    Prerequisite: MKT-360
    Many American businesses (e.g. Coca-Cola, McDonald’s, Boeing) now generate over half their revenues from markets outside the United States. Exploiting fast-growing markets in developing countries present profitable opportunities for businesses of all kinds. This course examines how economic, social, cultural, political, legal, and financial environments play an important role when formulating marketing plans for individual countries in the global marketplace. The pace and complexity of regional integration and interdependence, cultural diversity, electronic communications, and terrorism all create constant challenges and opportunities for marketers.
  
  • MKT 480 - Product Development (Senior Experience)


    Credits: Three (3)
    Prerequisite: MKT-361, MKT-471, and Six (6) additional Marketing credit hours
    This course focuses on the marketing and management of products, services and interactive experiences that define opportunities that exceed user value expectations.The course integrates all aspects of marketing strategy including product, pricing, communications and distribution.


  
  • MKT 493 - Cooperative Education


    Credits: One (1) to Three (3)
 

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