From the course: Complete Guide to Generative AI for Data Analysis and Data Science

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Evaluating linear regression models

Evaluating linear regression models

From the course: Complete Guide to Generative AI for Data Analysis and Data Science

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Evaluating linear regression models

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- [Presenter] Now we want to take a look at how we evaluate linear regression models. So when we talk about model evaluation, we're talking about doing tests or evaluations that help us understand how good are the predictions, how accurate, how close to the actual data that we test with does the model actually get? So there are different ways of testing a linear regression model. We can use the R-squared statistic, which is the proportion of the variance in Y. That's our dependent variable. How much of that is explained by the model? 'Cause there's always going to be, or oftentimes there is like a residual error that's not really caught by the model. We also have another statistic called the F-statistic, and that indicates if there's a statistically significant relationship between the dependent and independent variables. And if we're doing linear regression, we're assuming there is a relationship and the F-statistic will help us understand if there really is a significant…

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