Quantifying Relationships with Regression Models

This course will introduce you to the linear regression model, which is a powerful tool that researchers can use to measure the relationship between multiple variables. We’ll begin by exploring the components of a bivariate regression model, which estimates the relationship between an independent and dependent variable. Building on this foundation, we’ll then discuss how to create and interpret a multivariate model, binary dependent variable model and interactive model. We’ll also consider how different types of variables, such as categorical and dummy variables, can be appropriately incorporated into a model. Overall, we’ll discuss some of the many different ways a regression model can be used for both descriptive and causal inference, as well as the limitations of this analytical tool. By the end of the course, you should be able to interpret and critically evaluate a multivariate regression analysis

• Understand components of bivariate regression
• Apply and interpret multivariate regression models
• Incorporate categorical and dummy variables appropriately
• Use regression for descriptive and causal inference
• Recognize limitations of regression models

• Basic familiarity with the topic and its terminology
• Readiness to practice through exercises