课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced
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Q-Q plot for checking the normality of error terms - SQL教程
课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced
Q-Q plot for checking the normality of error terms
- [Instructor] Welcome to step 18 of your journey to build a reliable model for predicting home values. So far, you've been examining various assumptions to ensure your model behaves as expected. In this step, you're going to explore a fascinating tool called the Q-Q Plot to see if the errors in your data follow a typical or expected pattern. But what does that mean and why is it important? Think of a Q-Q Plot as a special kind of graph, like an x-ray that helps you see hidden characteristics of your data. In this case, it's like taking an x-ray of your residuals, the differences between your predicted and actual values. You're going to use a Q-Q Plot to visualize your residuals. Imagine it as a way to unveil the true nature of your data. Here's how it works. You'll run this code to create the Q-Q Plot. Now, let's take a look at the observations from your plot. Starting with the trend, the points on the plot seem to follow a…
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Creating the linear regression model and model summary: Part 19 分钟 33 秒
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Creating the linear regression model and model summary: Part 27 分钟 16 秒
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Creating the linear regression model and model summary: Part 35 分钟 33 秒
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Dropping insignificant variables and re-creating the model7 分钟 57 秒
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Checking assumptions for linear regression3 分钟 18 秒
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Assumption 1: Checking for mean residuals2 分钟 47 秒
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Assumption 2: Checking homoscedasticity3 分钟 13 秒
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Assumption 3: Checking linearity2 分钟 12 秒
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Assumption 4: Checking normality of error terms3 分钟 24 秒
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Q-Q plot for checking the normality of error terms3 分钟 14 秒
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Model performance comparison on train and test data6 分钟 7 秒
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Applying cross-validation and evaluation4 分钟 40 秒
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Challenge: Model building48 秒
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Solution: Model building1 分钟 16 秒
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