What is linearity in regression?
An example of an AI chatbot conversation about linearity in regression analysis.
What is linearity in regression?
Linearity in regression refers to the relationship between the independent and dependent variables being a straight line.
Why is linearity important in regression analysis?
Linearity is crucial because it ensures that the model accurately represents the relationship, allowing for reliable predictions.
Can you give me an example of a linear regression model?
Sure! An example is predicting house prices based on square footage, where the relationship is typically linear.
What happens if the relationship is not linear?
If the relationship is not linear, the model may not fit well, leading to inaccurate predictions and poor performance.
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