What are residuals in regression analysis?
An example of an AI chatbot conversation about understanding residuals in regression analysis.
What are residuals in regression analysis?
Residuals are the differences between observed and predicted values in a regression model.
Why are residuals important in regression?
Residuals help assess the fit of the model; they indicate how well the model predicts the data.
How can I visualize residuals?
You can visualize residuals using a residual plot, which shows residuals on the y-axis and predicted values on the x-axis.
What does it mean if residuals are not randomly distributed?
If residuals are not randomly distributed, it may indicate that the model is not capturing some patterns in the data.
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