Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 35 years. Is the result within 5 years of the actual Best Actor winner, whose age was 46 years? Best Actress 28 32 28 61 34 35 47 30 Best Actor 42 39 38 47 50 46 63 49 Find the equation of the regression line. 62 23 43 51 38 53 45 32 CO (Round the y-intercept to one decimal place as needed. Round the slope to three decimal places as needed.) The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 35 years is (Round to the nearest whole number as needed.) Is the result within 5 years of the actual Best Actor winner, whose age was 46 years? the predicted age is the actual winner's age. years old.

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**Regression Analysis of Best Actor and Actress Ages**

This dataset includes the ages of Best Actress and Best Actor award winners over various years. The goal is to use regression analysis to predict the age of the Best Actor winner based on the age of the Best Actress winner for a particular year.

**Data:**

- **Best Actress Ages:** 28, 32, 28, 61, 34, 35, 47, 30, 62, 23, 43, 51
- **Best Actor Ages:** 42, 39, 38, 47, 50, 46, 63, 49, 38, 53, 45, 32

**Analysis Task:**

1. **Find the Regression Equation:**
   - Let the Best Actress age be the predictor variable (x).
   - The regression equation is of the form: \(\hat{y} = b_0 + b_1x\)
   - Round the y-intercept (\(b_0\)) to one decimal place.
   - Round the slope (\(b_1\)) to three decimal places.

2. **Predicted Age Calculation:**
   - Predict the age of the Best Actor winner when the Best Actress age is 35 years.
   - Round the prediction to the nearest whole number.

3. **Verification:**
   - Check if the predicted age is within 5 years of the actual Best Actor winner's age (46 years).

This exercise aims to enhance understanding of linear regression and its application in analyzing patterns between related datasets.
Transcribed Image Text:**Regression Analysis of Best Actor and Actress Ages** This dataset includes the ages of Best Actress and Best Actor award winners over various years. The goal is to use regression analysis to predict the age of the Best Actor winner based on the age of the Best Actress winner for a particular year. **Data:** - **Best Actress Ages:** 28, 32, 28, 61, 34, 35, 47, 30, 62, 23, 43, 51 - **Best Actor Ages:** 42, 39, 38, 47, 50, 46, 63, 49, 38, 53, 45, 32 **Analysis Task:** 1. **Find the Regression Equation:** - Let the Best Actress age be the predictor variable (x). - The regression equation is of the form: \(\hat{y} = b_0 + b_1x\) - Round the y-intercept (\(b_0\)) to one decimal place. - Round the slope (\(b_1\)) to three decimal places. 2. **Predicted Age Calculation:** - Predict the age of the Best Actor winner when the Best Actress age is 35 years. - Round the prediction to the nearest whole number. 3. **Verification:** - Check if the predicted age is within 5 years of the actual Best Actor winner's age (46 years). This exercise aims to enhance understanding of linear regression and its application in analyzing patterns between related datasets.
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