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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 42 years. Is the result within 5 years of the actual Best Actor winner, whose age was 42 years? Best Actress 29 29 30 59 33 33 43 30 65 23 42 54 Best Actor 41 58 52 41 53 42 32 35 36 47 48 50 Find the equation of the regression line. ŷ=+*x (Round the y-intercept to one decimal place as needed. Round the slope to three decimal places as needed.) years old. The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 42 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 42 years? Yes, the predicted age is more than 5 years greater than the actual winner's age.

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 42 years. Is the result within 5 years of the actual Best Actor winner, whose age was 42 years? Best Actress 29 29 30 59 33 33 43 30 65 23 42 54 Best Actor 41 58 52 41 53 42 32 35 36 47 48 50 Find the equation of the regression line. ŷ=+*x (Round the y-intercept to one decimal place as needed. Round the slope to three decimal places as needed.) years old. The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 42 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 42 years? Yes, the predicted age is more than 5 years greater than the actual winner's age.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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**Regression Analysis of Best Actress and Best Actor Ages** In this exercise, we explore the relationship between the ages of Best Actress winners and Best Actor winners using data from various years. We aim to predict the age of the Best Actor given that the age of the Best Actress in that year is 42 years. Furthermore, we will assess whether this prediction is within 5 years of the actual Best Actor winner's age when the Best Actress winner's age is 42 years. ### Provided Data The ages of Best Actress and Best Actor winners for different years are as follows: | Best Actress | 29 | 29 | 30 | 59 | 33 | 33 | 43 | 30 | 65 | 23 | 42 | 54 | |--------------|----|----|----|----|----|----|----|----|----|----|----|----| | Best Actor | 41 | 35 | 36 | 47 | 48 | 50 | 58 | 52 | 41 | 53 | 42 | 32 | ### Steps to Find the Regression Equation: 1. **Define the Predictor and Response Variables:** - Predictor (x): Age of Best Actress - Response (y): Age of Best Actor 2. **Calculate the Regression Line:** The regression equation is generally formulated as: \[ \hat{y} = a + bx \] Where \(\hat{y}\) is the predicted age of the Best Actor, \(a\) is the y-intercept, and \(b\) is the slope of the regression line. - Round the y-intercept to one decimal place. - Round the slope to three decimal places. 3. **Prediction for Best Actor Age:** Given that the age of the Best Actress winner is 42 years, insert \(x = 42\) into the regression equation to find the predicted age of the Best Actor winner. Round this predicted age to the nearest whole number. 4. **Validation:** Compare the predicted age with the actual age of the Best Actor winner when the Best Actress's age was 42 years. Check if the predicted age is within a 5-year range of the actual winner's age. ### Formulas and Calculations 1. **Regression Equation:** \[ \hat{y} = \text{[y
Transcribed Image Text:**Regression Analysis of Best Actress and Best Actor Ages** In this exercise, we explore the relationship between the ages of Best Actress winners and Best Actor winners using data from various years. We aim to predict the age of the Best Actor given that the age of the Best Actress in that year is 42 years. Furthermore, we will assess whether this prediction is within 5 years of the actual Best Actor winner's age when the Best Actress winner's age is 42 years. ### Provided Data The ages of Best Actress and Best Actor winners for different years are as follows: | Best Actress | 29 | 29 | 30 | 59 | 33 | 33 | 43 | 30 | 65 | 23 | 42 | 54 | |--------------|----|----|----|----|----|----|----|----|----|----|----|----| | Best Actor | 41 | 35 | 36 | 47 | 48 | 50 | 58 | 52 | 41 | 53 | 42 | 32 | ### Steps to Find the Regression Equation: 1. **Define the Predictor and Response Variables:** - Predictor (x): Age of Best Actress - Response (y): Age of Best Actor 2. **Calculate the Regression Line:** The regression equation is generally formulated as: \[ \hat{y} = a + bx \] Where \(\hat{y}\) is the predicted age of the Best Actor, \(a\) is the y-intercept, and \(b\) is the slope of the regression line. - Round the y-intercept to one decimal place. - Round the slope to three decimal places. 3. **Prediction for Best Actor Age:** Given that the age of the Best Actress winner is 42 years, insert \(x = 42\) into the regression equation to find the predicted age of the Best Actor winner. Round this predicted age to the nearest whole number. 4. **Validation:** Compare the predicted age with the actual age of the Best Actor winner when the Best Actress's age was 42 years. Check if the predicted age is within a 5-year range of the actual winner's age. ### Formulas and Calculations 1. **Regression Equation:** \[ \hat{y} = \text{[y
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