From the course: Complete Guide to AI and Data Science for SQL Developers: From Beginner to Advanced

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Dropping insignificant variables and re-creating the model

Dropping insignificant variables and re-creating the model - SQL Tutorial

From the course: Complete Guide to AI and Data Science for SQL Developers: From Beginner to Advanced

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Dropping insignificant variables and re-creating the model

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- [Instructor] Welcome back! In this step, step 16, you'll drop insignificant variables, then recreate your model. But before we jump into the details, let's recall why you're here. In step 15, you created your linear regression model and thoroughly examined its performance. You used the ordinary lease squared, OLS method to build the model, analyze metrics like R-squared and F-statistic, and even broke down the coefficients and diagnostic statistics. Now in step 16, you're taking a closer look at your model's coefficients to ensure that it's accurate and reliable as possible. But why are you doing this? When you build a model to predict something like home prices, you want to be sure that each piece of information you put into the model actually matters. So you check if each piece of information like crime rate or air quality is really important in predicting home prices. If something doesn't make a big…

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