Regression models are an essential tool for data scientists and statisticians to understand the relationship between variables and make predictions about future outcomes. However, evaluating the performance of these models is a crucial step in ensuring their accuracy and reliability. Two commonly used metrics for evaluating regression models are Mean Squared Error (MSE) and R-squared. Understanding when to use each metric and how they differ can greatly improve the quality of your analyses. Check out my related blog on this topic – Mean Squared Error vs R-Squared? Which one to use?

To help you test your knowledge on MSE and R-squared (also known as coefficient of determination), we have created a quiz. This quiz consists of 10+ questions, including multiple-choice questions, to test your understanding of these two important metrics. By taking this quiz, you will gain a better understanding of when to use MSE or R-squared, and which metric is most appropriate for different evaluation scenarios.

Whether you are just starting out with regression analysis or are a seasoned data scientist, taking this quiz can help solidify your knowledge of MSE and R-squared, and improve your ability to evaluate regression models accurately. So, put your knowledge to the test and take this quiz today to enhance your understanding of these essential metrics.

## Results

- Agentic Reasoning Design Patterns in AI: Examples - October 18, 2024
- LLMs for Adaptive Learning & Personalized Education - October 8, 2024
- Sparse Mixture of Experts (MoE) Models: Examples - October 6, 2024

- Agentic Reasoning Design Patterns in AI: Examples - October 18, 2024
- LLMs for Adaptive Learning & Personalized Education - October 8, 2024
- Sparse Mixture of Experts (MoE) Models: Examples - October 6, 2024

### #1. Which metric is commonly used to evaluate regression models?

### #2. What is the range of the Mean Squared Error (MSE)?

### #3. Which of the following is true about the Mean Squared Error (MSE)?

### #4. What is R-Squared?

### #5. What is the range of R-Squared?

### #6. Which of the following is true about R-Squared?

### #7. Which metric should be used if the goal is to compare different models?

### #8. Which metric should be used if the goal is to interpret the impact of independent variables on the dependent variable?

### #9. What is Adjusted R-squared?

### #10. Which of the following is true about Adjusted R-squared?

### #11. Which of the following is true about Adjusted R-squared compared to R-squared?

### #12. Which metrics to use if the data consists of outliers?

- Agentic Reasoning Design Patterns in AI: Examples - October 18, 2024
- LLMs for Adaptive Learning & Personalized Education - October 8, 2024
- Sparse Mixture of Experts (MoE) Models: Examples - October 6, 2024

Hi Sir, for Q-6, 1st option should be the correct one, isn’t it? Correct me if I’m wrong.

Thank you for pointing that out. You were correct. I just rectified it.