Chapter 3. Multiple Regression in Action

In the previous chapter, we introduced linear regression as a supervised method for machine learning rooted in statistics. Such a method forecasts numeric values using a combination of predictors, which can be continuous numeric values or binary variables, given the assumption that the data we have at hand displays a certain relation (a linear one, measurable by a correlation) with the target variable. To smoothly introduce many concepts and easily explain how the method works, we limited our example models to just a single predictor variable, leaving to it all the burden of modeling the response.

However, in real-world applications, there may be some very important causes determining the events you want ...

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