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Skip to 0 minutes and 4 secondsHi, welcome, we're now going to talk about regression. Now regression is a very important part of the analytics tool kit. And it is an important predictive analytics method, because it allows you to understand how two variables are related. And in the marketing context, it really allows you to then understand how marketing levers like advertising is related to sales. We will discuss how to interpret regression output, the outputs that you get after doing regression analysis, how do you connect that to your marketing process? Explore the consequences of including some variables and not including some, commonly called as missing variables that are not in the regression model.

Skip to 0 minutes and 51 secondsAnd what it does in terms of confounding effects and biases that it introduces in your interpretation of the regression coefficients and the market in general. And then distinguish between economic and statistical significance. So the statistical significance is what the regression output gives you, but really does it translate into some kind of economic and business sense, and that's what you're going to able to distinguish. By the end, you will be able to describe what regressions are, what do they really do, and how they are used in marketing. And interpret integration outputs, you'll be smart consumers of all the outputs that somebody might give you about a regression analysis they conducted. And make inferences about customer behavior, really important thing, right?

Skip to 1 minute and 42 secondsWhen you're in marketing, you want to understand customer behavior. And regression allows you to understand customer behavior and connect them to business and marketing decisions.

Welcome to Week 5!

This week, you will learn about regressions–what they are and how to interpret them. Consider this week’s objectives and reflect on your familiarity with the concepts covered in this module.

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Marketing Analytics

Darden School of Business, University of Virginia