For parts a and b, round all number values in your answer to the nearest hundredth. a) The linear regression equation is y = _________________________ b) The exponential regression equation is y = _________________________ c) Which regression model is the better choice, linear or exponential? _________________ d) To the nearest thousandth, what is the r-value for the better model? ________________

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For parts a and b, round all number values in your answer to the nearest hundredth. a) The linear regression equation is y = _________________________ b) The exponential regression equation is y = _________________________ c) Which regression model is the better choice, linear or exponential? _________________ d) To the nearest thousandth, what is the r-value for the better model? ________________
**Exercise 13: Analyzing Data with a Calculator**

Use your calculator to make two lists and a scatterplot for the data below. Find both the linear and exponential equations-of-best-fit (regression equations) and the corresponding \( r \) values for each equation. Then answer the questions that follow.

| \( x \) | \( y \)  |
|:------:|:------:|
| 0      | 28     |
| 1      | 24.5   |
| 2      | 20.4   |
| 3      | 17     |
| 4      | 15.5   |
| 5      | 13.9   |
| 6      | 12.7   |

**Instructions:**
1. Enter the data into two lists on your calculator.
2. Create a scatterplot based on the lists.
3. Calculate the linear regression equation and note the correlation coefficient (\( r \)).
4. Calculate the exponential regression equation and note the correlation coefficient (\( r \)).
5. Compare the \( r \) values to determine which model best fits the data.
Transcribed Image Text:**Exercise 13: Analyzing Data with a Calculator** Use your calculator to make two lists and a scatterplot for the data below. Find both the linear and exponential equations-of-best-fit (regression equations) and the corresponding \( r \) values for each equation. Then answer the questions that follow. | \( x \) | \( y \) | |:------:|:------:| | 0 | 28 | | 1 | 24.5 | | 2 | 20.4 | | 3 | 17 | | 4 | 15.5 | | 5 | 13.9 | | 6 | 12.7 | **Instructions:** 1. Enter the data into two lists on your calculator. 2. Create a scatterplot based on the lists. 3. Calculate the linear regression equation and note the correlation coefficient (\( r \)). 4. Calculate the exponential regression equation and note the correlation coefficient (\( r \)). 5. Compare the \( r \) values to determine which model best fits the data.
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