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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does the linearity assumption imply?
💡 Hint: Think about what a scatter plot should look like.
Question 2
Easy
Define homoscedasticity in simple terms.
💡 Hint: Consider the consistency of error logs in your data.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does the linearity assumption in regression analysis refer to?
- No relationship
- Curvilinear relationship
- Straight-line relationship
💡 Hint: Think about how figures are represented in scatter plots.
Question 2
True or False: Homoscedasticity means that error variances are consistent across values of the independent variable.
- True
- False
💡 Hint: Recall what happens if residuals change over predicted values.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are given a dataset with multiple variables. Describe a step-by-step process for checking each of the four assumptions in linear regression.
💡 Hint: Remember to visualize your data at every stage to make your conclusions clearer.
Question 2
You discover a significant level of multicollinearity in your model. Propose strategies to address this issue.
💡 Hint: Think about how simplifying your model might help clarify results.
Challenge and get performance evaluation