BMI=(height.025)2(weight.45) 3. Using the method presented in class and applying the numerical portion of your UT number as a random number seed, take a random sample of 50 cases from the master data set. This will be your primary data set. inalysis 1. Show the results of the strO command for your primary data set. 2. Use R to conduct a simple linear regression on the data with weight as the independent variable and bmi as the dependent variable. As a part of this be sure to: a. Report the beta coefficients and associated p values and confidence intervals from your model. b. Give a written interpretation of your beta coefficients in terms of the actual case at hand. c. Assess your model's conformance with the LINE assumptions of regression. d. Give a prediction using your model for an individual weighing 185 pounds. Include 95% confidence and prediction intervals and written interpretations of both intervals. 3. A 12-year-old boy has been presented to you who weighs 110 pounds. Give two reasons.

1. BMI=(height.025)2(weight.45) 3. Using the method presented in class and applying the
numerical portion of your UT number as a random number seed, take a random sample of 50
cases from the master data set. This will be your primary data set. inalysis 1. Show the results of
the strO command for your primary data set. 2. Use R to conduct a simple linear regression on
the data with weight as the independent variable and bmi as the dependent variable. As a part of
this be sure to: a. Report the beta coefficients and associated p values and confidence intervals
from your model. b. Give a written interpretation of your beta coefficients in terms of the actual
case at hand. c. Assess your model's conformance with the LINE assumptions of regression. d.
Give a prediction using your model for an individual weighing 185 pounds. Include 95%
confidence and prediction intervals and written interpretations of both intervals. 3. A 12-year-old
boy has been presented to you who weighs 110 pounds. Give two reasons