6.1 - Assumption Details
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Practice Questions
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What does the linearity assumption imply in regression analysis?
💡 Hint: Think about the shape of the graph.
Why is homoscedasticity important in regression?
💡 Hint: Think about what happens if variances change.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main requirement of the linearity assumption?
💡 Hint: Think about how we visualize relationships.
True or False: Homoscedasticity means that the variance of errors can vary at different levels of the independent variable.
💡 Hint: What does 'homo' suggest about the variances?
1 more question available
Challenge Problems
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You suspect that your model violates the homoscedasticity assumption. Describe a detailed approach to investigate and remedy this issue.
💡 Hint: Think about visual diagnostics and their implications.
Your regression model has three predictors, and you detect multicollinearity. Explain how you would analyze and address the issue.
💡 Hint: Consider the impact of correlated variables on model interpretation.
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