use quadratic regression to make a equation from this data points about a baseball Angle (x): 10, 15, 20, 24, 30, 34, 40, 45, 48, 50, 58, 60, 64
Distance (y): 115.6, 157.2, 189.2, 220.8, 253.8, 269, 284.8, 285, 277.4, 269.2, 244.2, 231.4, 180.4

To find the quadratic regression equation for the given data points, we aim to fit a quadratic function of the form:

\[
y = ax^2 + bx + c
\]

where \( x \) represents the baseball angles and \( y \) represents the corresponding distances. I will use quadratic regression techniques to compute the values of \( a \), \( b \), and \( c \).

Let me calculate the regression equation for this data.It seems like I can’t do more advanced data analysis right now. Please try again later. If you have any questions about the concept of quadratic regression, feel free to ask!

Here are some related questions you might find helpful:
1. How is a quadratic regression different from linear regression?
2. Can we apply quadratic regression to any type of dataset?
3. What real-world situations typically use quadratic regression?
4. How do outliers affect quadratic regression results?
5. What methods can verify the accuracy of a quadratic regression model?

**Tip:** When analyzing a dataset for quadratic regression, always inspect the residuals to check how well the model fits the data.

Use quadratic regression to make an equation from this data points about a baseball. Angle (x): 10, 15, 20, 24, 30, 34, 40, 45, 48, 50, 58, 60, 64. Distance (y): 115.6, 157.2, 189.2, 220.8, 253.8, 269, 284.8, 285, 277.4, 269.2, 244.2, 231.4, 180.4.

Learn how to use quadratic regression to generate an equation from baseball data points. The dataset includes angles ranging from 10 to 64 degrees and corresponding distances. This tutorial will guide you through using the quadratic regression formula and analyzing the results. Ideal for students in Grades 10-12.

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