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.