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Creating the linear regression model and model summary: Part 3

Creating the linear regression model and model summary: Part 3 - SQL教程

课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced

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Creating the linear regression model and model summary: Part 3

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- [Narrator] Okay, now let's take a look at some diagnostic statistics. Starting with omnibus, which is a test for balance. This test checks if your prediction errors behave like a well-balanced seesaw. A smaller omnibus value is better. An omnibus value of 30.699 indicates our seesaw is a bit wobbly, like having a few bumps on a smooth road, but it's generally okay for most cases. The Durbin Watson. Durbin Watson acts like a detective, checking if there's a hidden pattern in your data. A score of 1.923 tells you there's no noticeable pattern in your data, which is good news. Like a detective saying, "I couldn't find any clues of foul play." Now, the probability omnibus, this is the probability linked to our omnibus test. A super tiny value like zero suggests that your data doesn't follow a perfect pattern, but that's perfectly normal for real world data. It's like saying your cake didn't turn out perfectly round,…

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