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The task requires finding the linear regression equation for the provided dataset with **age** as the explanatory variable (independent) and **weight** as the dependent variable. Let’s walk through the steps of how you can solve this in Excel to get the **slope and intercept**, rounded to two decimal places.

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### **Steps to Calculate Linear Regression in Excel:**

1. **Enter Data into Excel**:
   - Input the **age values (1 to 20)** in one column (e.g., Column A).
   - Input the corresponding **weights** in the next column (e.g., Column B).

2. **Use the SLOPE and INTERCEPT Functions**:
   - In a new cell, type:
     ```
     =SLOPE(B1:B20, A1:A20)
     ```
     This will calculate the **slope** of the regression line.

   - In another cell, type:
     ```
     =INTERCEPT(B1:B20, A1:A20)
     ```
     This will give the **y-intercept** of the line.

3. **Linear Regression Equation**:
   - The equation for a linear regression line is:
     \[
     y = mx + b
     \]
     Where:
     - \(m\) is the slope (from the SLOPE function).
     - \(b\) is the intercept (from the INTERCEPT function).

4. **Round the Slope and Intercept**:
   - You can use the **ROUND function** in Excel if needed. For example:
     ```
     =ROUND(SLOPE(B1:B20, A1:A20), 2)
     ```
     Similarly, do the same for the intercept.

5. **Optional: Plot the Regression Line**:
   - Highlight both columns (A and B).
   - Go to **Insert** → **Scatter Plot** → Choose **Scatter with Straight Lines**.
   - Right-click on the data points and select **Add Trendline**.
   - In the Trendline options, choose **Display Equation on Chart** to see the line equation directly.

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Would you like me to assist further with these calculations, or do you need specific help using Excel?

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### **Related Questions:**
1. How do you interpret the slope and intercept in this context?
2. What does the linear regression tell you about the relationship between age and weight?
3. How can you calculate R² in Excel to determine how well the regression fits the data?
4. What would happen if we added more data points to this model?
5. How do you determine if the regression model is appropriate for the data?

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### **Tip:**
A high **R² value** (close to 1) indicates that the model explains a large portion of the variability in the dependent variable. Use `=RSQ(B1:B20, A1:A20)` to calculate R² directly in Excel.

The table gives the average weight (in kilograms) of certain people ages 1–20. Use Excel to find the best-fit linear regression equation, where age is the explanatory variable. Round the slope and intercept to two decimal places.

Learn how to calculate the linear regression equation for age and weight data in Excel for people aged 1–20. This tutorial covers key statistical concepts, including slope and intercept calculation, and is suitable for students in Grades 10-12.

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