Refer to the data set (-2, 2), (-1,5), (0, 3), (1,2), (2,4), (3, 3) Part a: Make a scatterplot and determine which type of model best fits the data. Part b: Find the regression equation, round to two decimal places if necessary. = -3.6. Part c: Use the equation from Part b to determine y when x =

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
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**Question 7**

Refer to the data set: \((−2, 2), (−1, \frac{5}{2}), (0, 3), (1, \frac{7}{2}), (2, 4), (3, \frac{9}{2})\).

**Part a:** Make a scatterplot and determine which type of model best fits the data.

**Part b:** Find the regression equation, round to two decimal places if necessary.

**Part c:** Use the equation from Part b to determine \( y \) when \( x = -3.6 \).

For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac).

---

### Instructions:

1. **Scatterplot Creation:**
   - Plot each data point on a graph with the x-values ranging from -2 to 3 and the corresponding y-values.
   - Identify the pattern or trend of the data points to determine if a linear, quadratic, or another type of model fits best.

2. **Regression Equation:**
   - Use statistical software or a calculator to find the best-fit equation for the data. 
   - Ensure to round off the coefficients to two decimal places for accuracy in reporting.

3. **Prediction Using Regression:**
   - Substitute \( x = -3.6 \) into the derived equation to find the value of \( y \).
   - This can help extend the model’s prediction capabilities beyond the provided data points.
Transcribed Image Text:**Question 7** Refer to the data set: \((−2, 2), (−1, \frac{5}{2}), (0, 3), (1, \frac{7}{2}), (2, 4), (3, \frac{9}{2})\). **Part a:** Make a scatterplot and determine which type of model best fits the data. **Part b:** Find the regression equation, round to two decimal places if necessary. **Part c:** Use the equation from Part b to determine \( y \) when \( x = -3.6 \). For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). --- ### Instructions: 1. **Scatterplot Creation:** - Plot each data point on a graph with the x-values ranging from -2 to 3 and the corresponding y-values. - Identify the pattern or trend of the data points to determine if a linear, quadratic, or another type of model fits best. 2. **Regression Equation:** - Use statistical software or a calculator to find the best-fit equation for the data. - Ensure to round off the coefficients to two decimal places for accuracy in reporting. 3. **Prediction Using Regression:** - Substitute \( x = -3.6 \) into the derived equation to find the value of \( y \). - This can help extend the model’s prediction capabilities beyond the provided data points.
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