^{Data description, probability, inference on means, proportions, difference of means and proportions, categorical data, regression, analysis of variance, and multiple comparisons.}

^{This course covers important business data analytics concepts, including warehousing, OLAP, ETL, data mining, self-service business intelligence, and business reporting and visualization tools. It provides hands-on experience in the use of some popular data analytics software tools with a focus on aiding managerial decision-making across different business functional areas.}

^{Case-based discussion course examining how data analytics impact organizations today and issues related to the development of an overall business data analytics organizational strategy. Topics include business data analytics in organizations and the impact on business functional areas, strategic use of data and information, ethical issues related to data collection and usage, social and legal implications of pervasive digitization, and management of intellectual property.}

^{This managerially-oriented course covers the use of predictive analytic tools to generate predictive models such as logistic regression, decision trees, neural networks, and cluster analysis to generate deeper business insights in direct support of managerial decision making.}

^{This course takes a very hands-on approach with customer intelligence and equips students with the marketing science understanding and techniques they need to solve real-world marketing challenges. Thsi course uses a combination of lectures, cases, and exercises to teach the materials.}

^{This course focuses on understanding, managing, and analyzing an organization's digital marketing strategy. Topics related to online business models, search engine optimization, paid search and display advertising, web analytics, email marketing, social media marketing, and reputation management will be considered.}

^{This course provides a foundational understanding of the management, conceptualization, development, and implementation of databases. It covers normalization, structured query language (SQL), distributed databases, and conceptual modeling using entity-relationship (ER) diagrams. Case examples of modeling data in an organizational context will be utilized. Prereq: Open to MSBA students or with permission of the instructor.}

^{Provides advanced usage of quantitative analysis using spreadsheets, in-memory database, and development of effective dashboards. Emphasis is on the application of theoretical understanding of the human interaction with the user interface to facilitate communication and story-telling using data. Effectively communicating analysis results to a mangement and business audience using dashboards and reports to enhance decision-making is examined.}

^{This course develops an understanding of practical applicability of advanced analytics methods in a variety of business scenarios. The course is designed to provide hands-on opportunities for students to work with data and apply advanced business analytics techniques and machine learning, which include text mining, natural language processing, web analytics, social analytics, and simulation.}

^{Seminar course that examines current topics related to business analytics and how organizations can make use of data for decision-making.}

^{Project course where students apply their learning to a real-world problem domain resulting in solutions to solve organizational problems using data and advanced analytics methods. Emphasis is on real-world relevance and integration of multiple aspects of data analytics to meet users' needs. Three-course sequence must be taken in succession in final year of the MSBA program.}

• ^{MIS 795 I (1 credit)
  The introductory capstone project course focuses on the data architecture of the client and descriptive analytics that meet the organizational reporting needs.}

• ^{MIS 795 II (2 credits)
  This intermediate capstone project course focuses on teh organization's predictive and prescriptive analytics needs and a company-specific deliverable to solve a problem the organization currently faces.}

• ^{MIS 795 III (2 credits)
  This advanced capstone project course focuses on marketing analytics solutions for the organization, their potentail business anlytics strategy and plan for digital transformation, and a company-specific deliverable to solve a problem the organization currently faces}

^{In addition to the 26 required core credits listed above, MSBA students must complete a minimum of four (4) elective credits, as approved by the MSBA program advisor.}