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11-1/435 Diabetes and obesity are serious health concerns in the United States and much of the developed world. Measuring the amount of body fat a person carries is one way to monitor weight control progress, but measuring it accurately involves either expensive X-ray equipment or a pool in which to dunk the subject. Instead body mass index (BMI) is often used as a proxy for body fat because it is easy to measure: BMI = mass (kg)/(height (m))2 = 703 mass(Ib)/(height (in))?. In a study of 250 men at Bingham Young University, both BMI and body fat were measured. Researchers found the following summary statistics: 11-1/435 Xị = 6322.28 x} = 162674.18 i=1 Yi = 4757.90 > yi = 107679.27 i=1 X¡yi = 125471.10 11-1/435 (a) Calculate the least squares estimates of the slope and intercept. Graph the regression line. (b) Use the equation of the fitted line to predict what body fat would be observed, on average, for a man

11-1/435 Diabetes and obesity are serious health concerns in the United States and much of the developed world. Measuring the amount of body fat a person carries is one way to monitor weight control progress, but measuring it accurately involves either expensive X-ray equipment or a pool in which to dunk the subject. Instead body mass index (BMI) is often used as a proxy for body fat because it is easy to measure: BMI = mass (kg)/(height (m))2 = 703 mass(Ib)/(height (in))?. In a study of 250 men at Bingham Young University, both BMI and body fat were measured. Researchers found the following summary statistics: 11-1/435 Xị = 6322.28 x} = 162674.18 i=1 Yi = 4757.90 > yi = 107679.27 i=1 X¡yi = 125471.10 11-1/435 (a) Calculate the least squares estimates of the slope and intercept. Graph the regression line. (b) Use the equation of the fitted line to predict what body fat would be observed, on average, for a man

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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11-1/435 Diabetes and obesity are serious health concerns in the United States and much of the developed world. Measuring the amount of body fat a person carries is one way to monitor weight control progress, but measuring it accurately involves either expensive X-ray equipment or a pool in which to dunk the subject. Instead body mass index (BMI) is often used as a proxy for body fat because it is easy to measure: BMI = mass (kg)/(height (m)? = 703 mass(Ib)/(height (in))2. In a study of 250 men at Bingham Young University, both BMI and body fat were measured. Researchers found the following summary statistics: 11-1/435 x = 6322.28 x} = 162674.18 i=1 Yi = 4757.90 > y? = 107679.27 i=1 i=1 = 125471.10 11-1/435 (a) Calculate the least squares estimates of the slope and intercept. Graph the regression line. (b) Use the equation of the fitted line to predict what body fat would be observed, on average, for a man with a BMI of 30. (c) Suppose that the observed body fat of a man with a BMI of 25 is 25%. Find the residual for that observation. (d) Was the prediction for the BMI of 25 in part (c) an overestimate or underestimate? Explain briefly.
Transcribed Image Text:11-1/435 Diabetes and obesity are serious health concerns in the United States and much of the developed world. Measuring the amount of body fat a person carries is one way to monitor weight control progress, but measuring it accurately involves either expensive X-ray equipment or a pool in which to dunk the subject. Instead body mass index (BMI) is often used as a proxy for body fat because it is easy to measure: BMI = mass (kg)/(height (m)? = 703 mass(Ib)/(height (in))2. In a study of 250 men at Bingham Young University, both BMI and body fat were measured. Researchers found the following summary statistics: 11-1/435 x = 6322.28 x} = 162674.18 i=1 Yi = 4757.90 > y? = 107679.27 i=1 i=1 = 125471.10 11-1/435 (a) Calculate the least squares estimates of the slope and intercept. Graph the regression line. (b) Use the equation of the fitted line to predict what body fat would be observed, on average, for a man with a BMI of 30. (c) Suppose that the observed body fat of a man with a BMI of 25 is 25%. Find the residual for that observation. (d) Was the prediction for the BMI of 25 in part (c) an overestimate or underestimate? Explain briefly.
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