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This is " Intro to Linear Regression " from our Understanding Data course. What happens to course evaluations when a professor is really, really good looking? Are

This is "Intro to Linear Regression" from our Understanding Data course.

What happens to course evaluations when a professor is really, really good looking?

Are the evaluations more favorable? And if so, how big is the difference when compared to a not-so-attractive professor?

Linear regression is a neat little tool that can help us figure this out. (Don’t worry – it’s not nearly as complicated as it sounds.) And, given that student evaluations can help determine a professor’s pay, this exercise has important real-world implications.

How do we go about testing whether looks have an impact on course evaluations? If we take two professors – one who’s unattractive and one who’s gorgeous – we can start our test. We’ll need two variables for each professor: an average “beauty score” and average evaluation score.

Using a scatterplot, we can draw a straight line through the data points (our linear regression) to visualize the relationship between our two variables.

In this video, we use data from a real study to examine this relationship. So how closely correlated are these two variables? You’ll have to watch to find out!

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