What are some common errors in regression analysis?
An example of an AI chatbot conversation about common regression errors.
What are some common errors in regression analysis?
Common errors in regression analysis include multicollinearity, overfitting, and omitted variable bias.
Can you explain multicollinearity?
Multicollinearity occurs when independent variables in a regression model are highly correlated, making it hard to determine their individual effects.
How can I detect multicollinearity?
You can detect multicollinearity using Variance Inflation Factor (VIF) or by examining correlation matrices.
What is overfitting?
Overfitting happens when a model learns the noise in the training data instead of the actual pattern, leading to poor generalization.
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