Courses

Students in DePauw's Business Analytics Program explore business decision-making and problem-solving individually and in groups, drawing on a rich, liberal arts foundation of data analysis, ethical inquiry, global awareness, and clear thinking and communication. Business analytics students develop and apply these abilities in coursework, case studies, independent research, and internships.

Opportunities for leadership, internships, alumni connections, and mentorship are magnified through the Business Analytics Program's connections with the McDermond Center for Management and Entrepreneurship and the Management Fellows honors program.

Course Catalog

Requirements for a major

Business Analytics

Requirements for a minor

Business Analytics

Entrepreneurship

Courses in Business Analytics

Gateway to Business Analytics

A first course in applied business analytics that assumes no prior experience in the field. Explores uses of business analytics and ways to successfully use analytics in business decisions, including ethical aspects of data analysis. Focuses on gathering, organizing, and describing information. May include introductory topics such as data visualization and interpretation through use of simulation, case studies, and guest speakers. The course will include content from each of the four specializations in the Business Analytics major at DePauw: mathematics, computer science, financial analytics, and business & economics. Prerequisites: None.

Off-campus Extended Studies

An off-campus Extended Studies course on business analytics.

On-campus Extended Studies

An on-campus Extended Studies course on business analytics.

Topics

An exploration of selected topics in business. May be repeated for credit with different topics.

First-Year Seminar

A seminar focused on a theme related to the study of business analytics. Open only to first-year students. Does not count toward the major or into the major GPA.

Business Analytics II

An intermediate course in business analytics for students who have completed a statistics course. Develops data management, programming, and analytical skills to guide business decision-making. May cover tools such as Python, R, Julia, and Tableau and topics such as LASSO, random forests, and spreadsheet models. Prerequisites: A statistics course (choose from: MATH 141 or PSY 214 or ECON 350 or BIO 375) and BUSA 110 or consent of the instructor.

Principles of Risk Management and Insurance

The course surveys fundamental principles of risk, the risk management process, and insurance as a systematic approach to transfer and finance risk. It examines how insurance offers protection against major risks that firms and individuals face, how the insurance market is structured, and how and why the industry is regulated. This course also delves into theories and philosophies that provide insights into how the risk management industry functions in the larger society. Emphasis is placed on understanding that insurance is just one of the techniques to be relied upon in planning a comprehensive risk management program.

Inequality via Analytics

This course uses microdata (from the Current Population Survey) to explore inequality in the distribution of income and wealth in the United States. It is grounded in numbers and data analysis, but we will also study philosophical arguments (e.g., Rawls and Nozick) and theories about inequality. We will focus mainly on differences between rich and poor, but also examine racial, gender, health and other gaps. Prerequisite: Elementary statistics (such as ECON 350, BIO 275, MATH 141, MATH 247 or PSY 214) or consent of the instructor.

Data Visualization in Tableau

An introductory course on creating graphical representations of data in Tableau. Emphasizes both static graphics and animations that clarify complex situations and support data-driven decision-making. Includes basics of data cleaning and preparation using spreadsheets. Applications in business will be included. Other applications may include analyzing voting patterns, financial data, demographic trends, climate data, and public health policy. Prerequisites: None.

Social Media Analytics

This course focuses on the critical role of social media analytics in driving business analytics. Students will learn about the principles and practices of social media analytics and how to leverage social media data to inform business strategy and decision-making. The course will cover various topics, including data collection and analysis, social media platforms, and tools and techniques for social media analytics. Throughout the course, students will develop the skills to effectively communicate their findings to others and make data-driven recommendations for business analysis. They will also be exposed to case studies of businesses that have successfully used social media analytics to drive strategic planning and decision-making. Finally, they will be encouraged to think critically about the ethical and social implications of social media analytics in business analysis. Prerequisites: None.

Business Analytics Topics

Topics are chosen from business analytics topics that extend explorations of content in existing courses or allow exploration of content not duplicated in regular course offerings. May be repeated for credit with different topics. Prerequisites: Open to students by permission of instructor or to those who satisfy prerequisites determined by the instructor.

Internship in Business Analytics

An experiential course for students who complete a business analytics internship at an organization outside the University. This course does not satisfy major core or specialization requirements.

Regression with Microdata

This course uses microdata from complex surveys (e.g., the Current Population Survey) and hypothetical data with Monte Carlo simulation to explain regression analysis, interpret results, and answer research questions with data. Special emphasis is placed on understanding sampling variability and the standard error. Excel is used at an advanced level and combined with other statistical software such as Stata or R. Prerequisite: Elementary statistics (such as ECON 350, BIO 275, MATH 141, MATH 247 or PSY 214) or consent of the instructor.

Business Analytics III

An advanced course in predictive and prescriptive business analytics for students who have completed a regression course. May include algorithms such as neural networks and support vector machines, and applications such as text mining. Prerequisite: A regression course (any regression course such as BUSA 305, MATH 341, ECON 450) and BUSA 210 or consent of the instructor.

Financial Mathematics

(Cross-listed with MATH 331) Dive into the world of financial mathematics and unlock the power of money over time. This course equips students with advanced mathematical skills to navigate complex financial landscapes. Master the art of calculating the time value of money, analyzing investment opportunities, and understanding the intricacies of loans and bonds. Explore yield curves, portfolio management, and asset-liability matching techniques used by financial professionals. Gain hands-on experience with real-world applications in investment analysis, capital budgeting, and risk management. Upon completing this course, students will be able to navigate financial decisions confidently and strategically in an ever-evolving economic landscape. Prerequisite: ECON 100 and MATH 136 or MATH 151 or ECON 375

Seminar in Financial Mathematics

(Cross-listed with MATH 332) This is a problem-solving seminar. The problems discussed in the seminar provide students with a better understanding of the actuarial field by exposing students to the professional application of actuarial science and by providing resources for students taking actuarial exams. Techniques and strategies for solving difficult problems are also introduced in the seminar. The seminar also includes an introduction of financial instruments, the determinants of interest rates, an alternative way to approximate the effect of change in interest rates, and interest rate swaps. This course is of great assistance for students who are preparing for the actuarial exam Financial Math. Prerequisite: MATH 331 or BUSA 331 which may be taken concurrently.

Quantitative Risk Analysis

(Cross-listed with MATH 336) This course in Quantitative Risk Analysis provides students with a comprehensive interdisciplinary foundation in quantitative techniques for financial risk assessment and management. The curriculum encompasses the principles of fixed-income securities, Modern Portfolio Theory (MPT) and advanced topics like the Black-Scholes formula and the Binomial Tree method for derivatives pricing. The course emphasizes practical skills in identifying, calculating, and mitigating risks associated with fixed-income securities, equities, options, and futures. Students will work on projects that simulate real-world scenarios, gaining experience in managing the interest rate risk of fixed-income securities by controlling durations, applying MPT to create efficient portfolios, using stock index futures to manage market exposure, and leveraging stock options to hedge individual stock risks. Prerequisite: MATH 136 or MATH 151 or ECON 375, ECON 100, and either MATH 141 or ECON 350.

Business Analytics Topics

Topics are chosen from business analytics topics that extend explorations of content in existing courses or allow exploration of content not duplicated in regular course offerings. May be repeated for credit with different topics. Prerequisites: Open to students by permission of instructor or to those who satisfy prerequisites determined by the instructor.

Business Analytics Seminar

The integrated capstone for the business analytics curriculum with emphasis on cases, research methodology, and writing. Group discussion and criticism of research methods, including ethical considerations. Prerequisite: a major in business analytics or permission of the instructor and BUSA 310. Not open for pass/fail credit. BUSA 480 or BUSA 485 is required of all senior Business Analytics majors.

Independent Capstone Project

Outstanding students in business analytics may complete an intensive independent project in their senior year. The project culminates in a written thesis and a public presentation of their research. The thesis is directed by a Business Analytics faculty member. Thesis proposals must be approved by the program before a student can register for BUSA 485. Prerequisite: Permission of the program. May be taken for 1 semester (1 credit) or in two consecutive semesters (1/2 credit each semester). Not open for pass/fail credit.

Business Analytics Topics

Topics are chosen from business analytics topics areas that extend explorations of content in existing courses or allow exploration of content not duplicated in regular course offerings. May be repeated for credit with different topics. Prerequisites: Open to students by permission of instructor or to those who satisfy prerequisites determined by the instructor.