Activity Regression

The video tutorial introduces linear regression, allowing users to select or create data sets to explore the correlation between variables. It uses a height vs shoe size example to demonstrate the concept of a best fit line, explaining how it predicts values and is represented by an equation. The tutorial also covers the correlation coefficient, which measures the relationship between variables, and discusses residuals, which indicate the error in predictions. Users are encouraged to experiment with custom data to see how the best fit line and residuals change.

What does a correlation coefficient of 0.85 indicate about the relationship between shoe size and height?

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Describe how residuals are related to the accuracy of a linear regression model.

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