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Linear Regression

In this Linear Regression for Marketing Analytics video, we move from comparing groups with A/B testing to predicting outcomes with regression in Colab. Using the classic Advertising and Sales dataset, we explore the relationship between TV, radio, and newspaper ad budgets and product sales. We start with simple linear regression using TV only, then extend to multiple linear regression with all three channels, reading intercepts and slopes and interpreting R² to see how much variation in sales the model explains. The hands-on section walks through a complete, reusable workflow: loading and exploring the data, fitting models, plotting regression lines, checking residuals to see whether the model is “good enough,” and running what-if scenarios to predict sales for new campaign plans. By the end, you will be able to use linear regression as a practical tool for media mix decisions and be ready to move on to logistic regression for binary outcomes in the next video. Instructor: Dr. Hyunhwan “Aiden” Lee, CSULB College of Business