2 credits
Fall 2026 Lecture Upper Division
This course introduces modern statistical methods for marketing using big data. Firms are increasingly facing vast amounts of data on their customers and the marketplace, thanks to the rapid development of information technology in the last couple of decades. The challenge is becoming more about how to turn the big data into information and insights to improve firms' marketing decisions and profitability. This course discusses marketing applications for which we may use econometric, statistical, and machine-learning methods to improve and optimize decisions. Students will use RStudio to analyze real-world data and gain hands-on experience on data manipulation, visualization, and analysis. Intro-level Statistics/econometrics (at the level of STAT 35000 or ECON 47200) and R coding experience (comfortable with manipulating data, plotting, defining functions, using for loops, and running linear and logistic regressions in R) are required prerequisites.
Learning Outcomes1Enable students to articulate analytical process and logic for selecting a particular marketing strategy/plan
2Enable students to do (and also evaluate/critique) good marketing research in their respective careers
3Marketing knowledge and critical thinking
Prerequisites
Restrictions
made by Purdue students.