BUSINESS ANALYTICS (BANA)
BANA 348 - BUSINESS ANALYTICS I
Prerequisite: MATH 108 or MATH 318
This course teaches the basic skills, applications, and practices necessary for continual exploration and investigation of organizational data. Based on statistical methods, business analytics searches for new insights and understandings of organizational performance. The course presents the logical process of conducting a statistical analytics project. Topic coverage includes descriptive and inferential statistics. Emphasis will be given to written descriptions of analytical results. Students are encouraged to analyze data related to their major.
Credit: 3
BANA 350 - MACHINE LEARNING FOR BUSINESS
Prerequisite: BANA 348
Applications of machine learning methods to the business setting. The course covers prediction and classification methods, social network analysis & text mining, and other topics in an emerging field of AI within a variety of business disciplines.
Credit: 3
BANA 448 - BUSINESS ANALYTICS II
Prerequisite: BANA 348
How can data be used to inform business decisions? Students in this class learn how to use computer software to analyze data to build models of consumer and firm behavior. Students begin by extending their practical and theoretical understanding of multiple linear regression, and progress to extensions including logistic regression. Students also learn critical “big data” skills such as data reduction, missing data imputation, model training, and model selection. The course concludes with a project analyzing student-gathered data. Emphasis throughout the course is on using data to inform decision-making.
Credit: 3
BANA 449 - RESEARCH IN BUSINESS ANALYTICS
Prerequisite: BANA 448 or MIS 272 or MGT 340
This course is designed to allow students to apply their knowledge of business analytics to an empirical research question. Students will define an empirical research question; collect, organize and clean data using an industry standard statistical program; perform data description; apply appropriate tools of inference to answering their question; and write either a technical report or a scientific paper.
Credit: 3
BANA 505 - APPLIED STATISTICS FOR BUSINESS
Prerequisite: None
Survey of statistical methods applied to business problems. Reviews college-level introductory statistics and extends to classical parametric prediction methods including linear and logistic regression. Uses major statistical software.
Credit: 3
BANA 510 - DATA MANAGEMENT
Prerequisite: None
Introduction to data management in the context of modern business problems. Students will learn foundations of structured query language (SQL) and its applications to data manipulation.
Credit: 3
BANA 515 - DATA VISUALIZATION
Prerequisite: None
This course focuses on creating visual aids appropriate for various business tasks and goals. Students will learn how to choose appropriate graphic tools and packages, as well as interpret the graphs and analyze visual patterns in data.
Credit: 3
BANA 520 - ADVANCED BUSINESS SPREADSHEETS
Prerequisite: None
Study and implementation of intermediate and advanced spreadsheet application features as applied within business environments. Focus on data analysis tools, collaboration, statistical functions, data imports/exports, auditing tools, business intelligence tools and macros.
Credit: 3
BANA 525 - PREDICTIVE ANALYTICS
Prerequisites: BANA 505
Applications of concepts from probability and statistics to draw inferences from data. Covers advanced regression analysis including non-parametric approaches. Introduction to time series and panel techniques for predicting future data. Additional topics may include Bayesian modeling, causal inference, A/B testing, and experimental design. Considers which of competing approaches will generate the most useful estimates for business decision-making. Uses major statistical software.
Credit: 3
BANA 530 - MACHINE LEARNING FOR BUSINESS
Prerequisite: BANA 505
Graduate-level class that introduces basics of machine learning in the context of modern business problems. Students will learn foundations of classification modeling, segmentation, clustering, computer vision, text analysis and sequences.
Credit: 3
BANA 535 - OPTIMIZATION METHODS FOR BUSINESS
Prerequisite: BANA 520
Graduate-level class that introduces basics of optimization methods. Students will learn applications of optimization tools in the context of business problems. No prerequisite is required for this course, however, prior knowledge of calculus and linear algebra is strongly recommended.
Credit: 3
BANA 540 - CASE STUDIES IN BUSINESS ANALYTICS
Prerequisite: BANA 505, BANA 510, BANA 515, BANA 520
A series of case studies on the use of analytics in various business settings. Topics include a variety of areas of data management and analysis in various settings, such as marketing, finance, education, health care, and sport management. Cases may address any or all stages of business analytics: design, data collection, cleaning, warehousing, analysis, and/or communication.
Credit: 3
BANA 545 - GRADUATE INTERNSHIP IN BUSINESS ANALYTICS
Prerequisite: None
This course helps the MSBA student meet the internship/work-experience graduation requirement for the MSBA degree. The student is required to work a minimum of 225 hours and fulfill other requirements as stated in the Learning Contract. Prior approval of the academic internship advisor and completion of the appropriate paperwork, including the learning contract, are required. The student will earn three credit hours per field experience (or at least 400 hours to get 6 credits).
Credit: 3-6
BANA 550 - RESEARCH IN BUSINESS ANALYTICS
Prerequisite: None
An original project in business analytics at the graduate level. May include theoretical and/or applied elements.
Credit: 3-6