Online MBA Courses
Curriculum Details
34 total credits required
*Foundation courses may be waived based on previous coursework.
The University of New Haven’s online MBA features career-focused concentrations in business analytics, data analytics (STEM), and global supply chain management, along with a general MBA option. Each concentration is designed to provide the expertise you need to take the next step in your business career.
Our online MBA courses are taught by a variety of engaging professors including research-active, tenured professors and full-time practitioners who bring industry experience to the classroom. Flexible, accelerated program delivery allows you to earn your degree in a format that fits your life.
This program consists of 34 credit hours and combines a core of essential business skills with specialized training in sought-after concentration areas. Online MBA courses are seven weeks in duration. Most students complete their degree in just 18 to 24 months.
The Foundational Courses can be waived based on previous coursework. For the Business Analytics Concentration and the Global Supply Chain Management Concentration, you’ll choose 3 courses. For the Data Analytics (STEM) Concentration, you’ll take ECON 6635, MGMT 6625, QNAL 6625, and choose two more courses.
Foundation Courses
This course addresses how scarcity forces individuals, firms, and societies to choose among alternative uses of its limited resources. At the same time, the various choices made by different economic agents must be mutually consistent. Markets are a mechanism to achieve such reconciliation. The course seeks to make the students understand how economists model the choice process of individual consumers and firms, and how markets work to coordinate these choices. It also examines how well markets perform this function using the economist’s criterion of market efficiency.
An introduction to general purpose financial statements including the balance sheet, the statement of income and retained earnings, and the statement of cash flow with an emphasis on understanding financial statements rather than their preparation. Financial statement ratios, useful in analysis, will also be introduced in the course.
Prerequisite: ACCT 6619. Introduction to some basic concepts of finance, time value of money, cash flow and financial planning, valuation techniques for projects, and capital budgeting.
Core Courses
This course examines the impact of theories and research findings relevant to leadership and team building in organizations. The role of the leader and teams in organizations is discussed. The knowledge and skills required for successful leadership and team building are analyzed. An assessment of one’s own leadership and team building capabilities is completed.
Accounting analysis for the managerial functions of planning, controlling, and evaluating the performance of the business firm.
This course reviews statistical concepts and methods with emphasis on data analytics and visualizations. Topics to be covered include descriptive statistics, plots and graphs for discrete and continuous data, statistical inference, regression, and selected non-parametrics including chi-square. In addition, power pivot and other Excel analytical tools will be covered. Students will obtain a solid introduction to R as a functional programming language and will be able to use Excel and R to effectively compute statistical and graphical procedures.
This course provides the basic theoretical foundation of both macroeconomics and international economics. The course will help the students to make decisions in today’s global economy. Topics may include comparative advantage, gains from trade, measuring national output, inflation, unemployment, productivity, growth, the role of economic policy and institutions in the performance of firms and nations, currency exchange rates, capital markets, open economy, trade liberalization, and economic integration.
Examination of valuation, investment, and financing of the firm and their implications for strategic decision making; application of pricing models.
This course integrates marketing strategy with the enhancement of value in firms, products, services, and industry. The course focuses on competitive and customer metrics and analysis, development of marketing strategy, and implementation of strategic marketing plans in business organizations. The course incorporates current developments in marketing to acquaint students with the present-day challenges of marketing activities and serves as a vehicle for the application and integration of the concepts, analytical tools, and problem-solving approaches to developing marketing strategy.
Prerequisite: MGMT 6663. A macro-level course that examines the intersection between business strategy, organizational leadership, and organizational change. Drawing from the disciplines of strategy, human resources management, organizational development, and leadership, this upper-level course engages students in the observation and analysis of the corporate executives’ perspective. Topics may include formulating and communicating organizational intent, performance management and organizational outcomes, human resources performance management and its links to organizational outcomes, organizational dynamics, organizational culture, organizational structure, and crisis management.
This course examines management policies and strategies for the complex organization operating in a dynamic environment from the viewpoint of top-level executives of the organization. It also develops analytic and systematic frameworks for the management of the numerous elements involved in assuring the fulfillment of the goals of the total organization. The course integrates the student’s general business knowledge with knowledge acquired in the MBA curriculum. Emphasis on development of oral and written communication skills is assessed by examination and discussion of cases and by other appropriate instructional methods. Completion of a significant “SLiCE” project (Shared Live Client Experience) is required as a part of this course. Students will work in teams to assess, analyze, and make recommendations that address a real company’s issues or opportunities.
Business Analytics Concentration Courses
Prerequisite or co-requisite: BANL 6100. The focus of this course is on statistical and data analytical methods for the preparation of business forecasts. A variety of empirical techniques are covered: smoothing methods, moving averages, regression analysis, classical time-series decomposition methods, and ARIMA (Box-Jenkins) models. Emphasis is placed upon building forecasting models and evaluating their reliability. The focus is on time-series data. R is the preferred statistical package.
This course will familiarize you with some of the organizational and management issues surrounding the emergence of information and knowledge as key factors in developing and maintaining a competitive advantage for firms. The course is organized around two ideas: knowledge as a manageable asset and why people in organizations sometimes don’t use what they know. A basic assumption of the class is that organizations are complex adaptive systems operating in highly competitive, information- and knowledge-rich environments. This course will also use perspectives from Positive Organizational Scholarship as a possible framework for understanding how to get people in an organization to use what they know.
Prerequisite or co-requisite: BANL 6100. This course is designed to provide business students with the skills to conduct data mining and statistical analysis for dealing with common managerial-making tasks, such as prediction, classification, and clustering. Data mining is a rapidly growing field that is concerned with developing techniques to assist analysts to make intelligent use of large data sets. In this course, the emphasis is on understanding the application of a wide range of modern techniques to specific managerial situations, rather than on mastering the mathematical and computational foundations of the techniques. Upon successful completion of the course, students should possess valuable analytical skills that will give them a competitive edge in many industry sectors, in a wide range of managerial and analytical positions.
Prerequisite: FINC 6601 and FINC 6604 A review of econometric models with special focus on applications in finance.
Prerequisite: MKTG 6610. An examination of the principal comprehensive household and organizational buyer behavior models and the behavioral science theories on which such applied methods are based. Analysis of the buyer at the individual level, at the social level, and at the organizational level.
Prerequisites: MKTG 6610 , BANL 6100. An examination of methods useful for analyzing customer databases and developing data-driven marketing strategies. The exploration of insights from statistical analysis of customer life cycles, customer lifetime value, response experimentation, and predictive modeling. This course includes customer data analysis leading to performance metrics, marketing accountability, and dashboards.
Prerequisite: MKTG 6610. Key to a cutting edge marketing strategy today for all organizations is a relevant and meaningful social connection with customers and potential customers. Social media has become a cutting edge organizational tool to create, foster, and develop relationships with consumers, customers, clients, partners, funders, boards, volunteers – even competitors. We will focus on constituents’ social interactions, social media platforms, how to build social media strategies and market through those platforms, and finally, how to monitor and measure their effectiveness.
Prerequisite: MKTG 6610. This course will equip students with strategic abilities to help organizations adapt to the rapidly evolving digital markets of the future. It will cover a range of situations as brick and mortar businesses go partly or entirely digital and new business models emerge (such as Airbnb and Uber) that disrupt traditional business models. Using case studies and readings, students will learn the latest and upcoming changes in digital marketing strategy and practice. In addition, students will engage in an experiential learning project (e.g. search engine marketing) with a real business to appreciate the link between strategy and execution.
Statistical methods and theories used in solving business problems. Topics include data analysis, discrete and continuous probability distributions, statistical inference and estimation, regression and correlation analysis, the analysis of variance, decision theory, and nonparametric tests including chi-square. Students will use computers to conduct statistical tests using the information presented.
Prerequisite: BANL 6100. This course applies econometric methods to real-world economic questions in order to quantify economic relationships. By providing the basic tools to do empirical analysis, this course empowers the student to become a more sophisticated consumer of economic research done by others. A foundation is built first with estimation, hypothesis testing, and confidence intervals with simple and multiple regression. This core set of econometric skills is extended with the use of dummy variables, autocorrelation, heteroscedasticity and simultaneous equations. This course uses the statistical programming language R and the R-Studio programming tool.
Prerequisite: BANL 6100. This course focuses on the process of creating goods and services. Concepts, functions and basic techniques of operations management are reviewed. Topics include decision-making, forecasting, scheduling, project management, production planning, inventory management, strategy, and quality control. Emphasis will be on quantitative methods, hands-on problem solving, and case studies. The course includes a team analysis of a real-world operations problem.
Prerequisite: BANL 6100. The course covers a variety of standard statistical methods used to analyze multivariate data. It emphasizes the implementation and interpretation of these methods across business domains. Topics covered include computation of summary statistics, analysis of categorical data, loglinear models for two- and higher-dimensional contingency tables, the multivariate normal distribution, MANOVA, principal components analysis, factor analysis, and other topics such as canonical correlation and cluster analysis. The R statistical computing package is used throughout.
Business analytics refer to the use of data, statistical, and quantitative analysis to derive decisions and actions, and is applied in many business functions including but not limited to operations, marketing, finance, and strategic management. This course is designed to provide insights into sport business analytics. Students are introduced to the skills, technologies, analyses, and practices essential to understand and evaluate business performance in sport industry, convert data into actionable information, and assist managerial decision making.
Data Analytics (STEM) Concentration Courses
Prerequisite or co-requisite: BANL 6100. The focus of this course is on statistical and data analytical methods for the preparation of business forecasts. A variety of empirical techniques are covered: smoothing methods, moving averages, regression analysis, classical time-series decomposition methods, and ARIMA (Box-Jenkins) models. Emphasis is placed upon building forecasting models and evaluating their reliability. The focus is on time-series data. R is the preferred statistical package.
This course will familiarize you with some of the organizational and management issues surrounding the emergence of information and knowledge as key factors in developing and maintaining a competitive advantage for firms. The course is organized around two ideas: knowledge as a manageable asset and why people in organizations sometimes don’t use what they know. A basic assumption of the class is that organizations are complex adaptive systems operating in highly competitive, information- and knowledge-rich environments. This course will also use perspectives from Positive Organizational Scholarship as a possible framework for understanding how to get people in an organization to use what they know.
Prerequisite or co-requisite: BANL 6100. This course is designed to provide business students with the skills to conduct data mining and statistical analysis for dealing with common managerial-making tasks, such as prediction, classification, and clustering. Data mining is a rapidly growing field that is concerned with developing techniques to assist analysts to make intelligent use of large data sets. In this course, the emphasis is on understanding the application of a wide range of modern techniques to specific managerial situations, rather than on mastering the mathematical and computational foundations of the techniques. Upon successful completion of the course, students should possess valuable analytical skills that will give them a competitive edge in many industry sectors, in a wide range of managerial and analytical positions.
Prerequisite: BANL 6100. This course focuses on the art of communicating ideas imbedded in data through visual means to include spatial representations. Students are introduced to industry-standard graphic and data design techniques used to create understandable visualizations in order to communicate effectively with a particular audience. Techniques in organizing and articulating data are developed using real world examples. The course materials, assignments and project will all be prepared using the R programming language.
Prerequisite: BANL 6100. The course consists of applied training in foundational topics for supervised learning such as Linear Regression, Nearest Neighbors, and Neural Networks. It first builds a sound understanding of data preparation, exploration, and reduction methods. It covers both prediction as well as classification processes. The emphasis is on understanding the application of a wide range of modern machine learning techniques to specific decision-making situations across business domains, rather than on mastering the mathematical and computational foundations of the techniques. The R programming language will be used for instruction.
Prerequisite: BANL 6100. The course consists of applied training in foundational topics for unsupervised learning such as Association Rules, Cluster Analysis, and Text Mining. It first builds a sound understanding of data preparation, exploration, and reduction methods. It covers both prediction as well as classification processes. The emphasis is on understanding the application of a wide range of modern machine learning techniques to specific decision-making situations across business domains. The R programming language will be used for instruction.
Prerequisite: BANL 6100. This course will introduce students to foundations of relational database design and management with a focus on business domains and business analytics applications. Topics include database design principles (to include connecting and updating), entity-relationship diagrams, constructing queries in SQL, and analyzing databases – critical skills for data analysts. The course materials, assignments, and project will all be prepared using the R programming language.
Prerequisite: BANL 6100. This course will introduce some commonly-used survey methods for conducting research, evaluating programs and outcomes. Analysis of survey data, explanation of survey outcomes, and implications of differences in sampling techniques will be also emphasized. The R programming language will be used for survey data analysis.
This course introduces concepts and principles of business process improvement, and quality assurance in organizations. It examines the primary tools and methods used to monitor, measure, improve, and control business processes, and quality from a holistic supply chain perspective. Topics include statistical process control, Lean Six Sigma principles, and continuous improvement.
This course introduces key concepts, skills, and methods in Business Analytics for data-driven decision making in organizations. Using Microsoft Power BI, the course trains the student in dashboarding, and Power BI’s quantitative, and computational capabilities across various business domains. The mix of topics includes data access, data wrangling, visualization, and machine learning via R programming language in Power BI.
Prerequisite: FINC 6601 and FINC 6604 A review of econometric models with special focus on applications in finance.
A course on real estate financial and market analysis ,and the impact it has on the real estate decision process. Concepts covered will include the application of cash flow analysis, risk, discount rates, capitalization rates, financing, leverage, investment value vs. market value, and taxation. The student will be exposed to economic base analysis, shift-share analysis, highest and best use, and the impact that market and cash flow analyses have on real property for commercial and residential real estate.
Prerequisites: MKTG 6610 , BANL 6100. An examination of methods useful for analyzing customer databases and developing data-driven marketing strategies. The exploration of insights from statistical analysis of customer life cycles, customer lifetime value, response experimentation, and predictive modeling. This course includes customer data analysis leading to performance metrics, marketing accountability, and dashboards.
Prerequisite: MKTG 6610. This course will equip students with strategic abilities to help organizations adapt to the rapidly evolving digital markets of the future. It will cover a range of situations as brick and mortar businesses go partly or entirely digital and new business models emerge (such as Airbnb and Uber) that disrupt traditional business models. Using case studies and readings, students will learn the latest and upcoming changes in digital marketing strategy and practice. In addition, students will engage in an experiential learning project (e.g. search engine marketing) with a real business to appreciate the link between strategy and execution.
Prerequisites: BANL 6100, MKTG 6610. This course prepares students for a career in marketing analytics. This involves analyzing data using a set of statistical tools to facilitate informed decision making. Topics include methods used in online marketing, grocery stores, and financial markets. The course also explores customer big-data techniques and their theoretical foundations to help students acquire practical skills through hands-on experiences. Students are provided with the tools and the confidence necessary to analyze real-world questions and present their findings.
Prerequisite: BANL 6100. This course applies econometric methods to real-world economic questions in order to quantify economic relationships. By providing the basic tools to do empirical analysis, this course empowers the student to become a more sophisticated consumer of economic research done by others. A foundation is built first with estimation, hypothesis testing, and confidence intervals with simple and multiple regression. This core set of econometric skills is extended with the use of dummy variables, autocorrelation, heteroscedasticity and simultaneous equations. This course uses the statistical programming language R and the R-Studio programming tool.
Prerequisite: BANL 6100. This course focuses on the process of creating goods and services. Concepts, functions and basic techniques of operations management are reviewed. Topics include decision-making, forecasting, scheduling, project management, production planning, inventory management, strategy, and quality control. Emphasis will be on quantitative methods, hands-on problem solving, and case studies. The course includes a team analysis of a real-world operations problem.
Prerequisite: BANL 6100. The course covers a variety of standard statistical methods used to analyze multivariate data. It emphasizes the implementation and interpretation of these methods across business domains. Topics covered include computation of summary statistics, analysis of categorical data, loglinear models for two- and higher-dimensional contingency tables, the multivariate normal distribution, MANOVA, principal components analysis, factor analysis, and other topics such as canonical correlation and cluster analysis. The R statistical computing package is used throughout.
Business analytics refer to the use of data, statistical, and quantitative analysis to derive decisions and actions, and is applied in many business functions including but not limited to operations, marketing, finance, and strategic management. This course is designed to provide insights into sport business analytics. Students are introduced to the skills, technologies, analyses, and practices essential to understand and evaluate business performance in sport industry, convert data into actionable information, and assist managerial decision making.
Global Supply Chain Management Concentration Courses
Prerequisite or co-requisite: BANL 6100. The focus of this course is on statistical and data analytical methods for the preparation of business forecasts. A variety of empirical techniques are covered: smoothing methods, moving averages, regression analysis, classical time-series decomposition methods, and ARIMA (Box-Jenkins) models. Emphasis is placed upon building forecasting models and evaluating their reliability. The focus is on time-series data. R is the preferred statistical package.
This course provides the student with an understanding of the effects of globalization on the economic environment and corporate operations. It examines the multinational’s operations and the many adaptations management must undertake to interact successfully with the various global business environments. Topics will be examined from both domestic and international perspectives and will include the operational and strategic adjustments necessary for the multinational to navigate among the diverse and rapidly evolving cultural, political, economic, financial, operational, and ethical environments of global markets.
A study of the traditional functions of management: planning, organizing, directing, controlling, and coordinating, along with an analysis of human behavior in organizations and the exploration of new paradigms in business and management systems.
Prerequisite: MKTG 6610. An examination of the service product in for-profit and not-for-profit organizations. Unique tools for analysis of service quality and the service encounter, including the roles of the customer and the service provider in service production, service expectations and scripts, and positioning. Communication and management strategies for service expectations, demand management, and organizational flexibility.
Prerequisite: MKTG 6610. A case-based review of the basic decision-making problems in marketing management, with an emphasis on information gathering and strategy. Topics include both U.S. and international problems in product, promotion, distribution channels, sales management, and pricing. Cases will consider both physical products and services in the consumer and business-to-business environments.
Prerequisite: MKTG 6610. The application of marketing principles and techniques in a global environment. A managerial approach to international marketing as it pertains to product policies, market channels, pricing, and advertising in a foreign market. Emphasis on marketing in different cultural settings.
Prerequisite: BANL 6100. This course focuses on the process of creating goods and services. Concepts, functions and basic techniques of operations management are reviewed. Topics include decision-making, forecasting, scheduling, project management, production planning, inventory management, strategy, and quality control. Emphasis will be on quantitative methods, hands-on problem solving, and case studies. The course includes a team analysis of a real-world operations problem.
Prerequisite or co-requisite: BANL 6100. This course is designed to provide business students with the skills to conduct data mining and statistical analysis for dealing with common managerial-making tasks, such as prediction, classification, and clustering. Data mining is a rapidly growing field that is concerned with developing techniques to assist analysts to make intelligent use of large data sets. In this course, the emphasis is on understanding the application of a wide range of modern techniques to specific managerial situations, rather than on mastering the mathematical and computational foundations of the techniques. Upon successful completion of the course, students should possess valuable analytical skills that will give them a competitive edge in many industry sectors, in a wide range of managerial and analytical positions.
An examination of how sports facilities such as coliseums, municipal and college stadiums, and multipurpose civic centers are managed. Course topics include facility ownership and management, business and financial management, event booking, marketing and sales, ticketing and access management, ancillary revenue sources, back-of-house operations, event management, and safety and security.
SMGT 6618 focused on the foundation for intercollegiate athletics. This course focuses on the applied process of managing collegiate fitness and athletic programs. Issues covered include arranging travel, scheduling events, purchasing insurance, hiring officials, handling sport media, town/gown relationships, laundry and equipment processing, and a host of other actions required to run a collegiate program.
Prerequisite: SMGT 6613. This course takes the students through the entire process of building a sport facility. From the planning process and site acquisition steps through hiring architects and builders, the course is detailed and focused primarily on larger sport facilities.
This course will review and examine the principles and practices associated with managing events and the nature of the broader event management industry ranging from sport events to major concerts. This course will help students develop the skills necessary to manage virtually any aspect of an event, including logistics, contingency planning, ticketing/admissions, access control, financing, sponsorship, seating designs/controls, sponsor and supplier agreements, risk management, marketing, managing event personnel, and working with local/government agencies.
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