https://file.aiquickdraw.com/mathbot/file/1728085743204cul55mw2.jpg

Based on the scatter plot visible in the image, the points seem to suggest a curved relationship rather than a straight-line trend. The most appropriate type of regression for such a dataset, where the data appears to follow a pattern with some curvature, is **quadratic regression**.

Quadratic regression fits a parabolic curve (second-degree polynomial), which is suitable for datasets that exhibit a U-shaped or inverted U-shaped pattern, as appears in the plot.

Would you like further clarification or details about regression types? Here are 5 related questions:

1. What is the difference between linear and quadratic regression?
2. How can you tell which type of regression to apply just by looking at data?
3. Can you explain how the quadratic regression formula is derived?
4. What are the common applications of quadratic regression in real-life scenarios?
5. How would you calculate the error or goodness-of-fit for a quadratic regression model?

**Tip:** Always visualize the data first before deciding on a regression model, as it helps you choose the most appropriate curve or line for the best fit.

What type of regression would you use for this data?

Understand how to apply quadratic regression to datasets that exhibit a curved pattern, using the formula y = ax² + bx + c. This problem explains the key concepts in regression analysis and the least squares method for high school students in Grades 10-12.

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