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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What are the columns in the created dataset?
💡 Hint: Think about the type of data we are analyzing.
Question 2
Easy
How do we create a dataset in Python?
💡 Hint: Recall the pandas library and its DataFrame function.
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 is the dependent variable in the dataset?
- Experience
- Salary
- Both
💡 Hint: Look at what we want to predict.
Question 2
True or False: The dataset consists of two columns: Experience and Salary.
- True
- False
💡 Hint: Recap on the definitions we established for our dataset.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Consider the following additional data: (6, 65000). How would this new data point potentially affect the slope of the linear regression line you would create?
💡 Hint: Think about how adding higher data points may change our predictions.
Question 2
Propose a method to check for anomalies in this dataset before training a model. How would you design a simple test?
💡 Hint: Consider the first step before analyzing data visually.
Challenge and get performance evaluation