Consider a linear regression analysis of Weight at Birth (Birth Weight) in grams and Gestational Age in Weeks. The analysis gave the following output Model Beta Coefficient p-value 95% Confidence Interval Gestational Age 96.56 0.02 14.41 -178.72 Constant -230.34 0.39 -3 340.0-3 180.30 2.1 Give the linear regression equation (use the variable names and not X and Y) 2.2 Calculate the predicted Weight at Birth of a baby born at 40 weeks Gestational Age 2.3 Do the data present sufficient evidence to indicate that the slope differs from zero, at the 1% level of significance? Interpret your results. (Ensure you use all the steps for your hypothesis test)
Consider a linear regression analysis of Weight at Birth (Birth Weight) in grams and Gestational Age in Weeks. The analysis gave the following output Model Beta Coefficient p-value 95% Confidence Interval Gestational Age 96.56 0.02 14.41 -178.72 Constant -230.34 0.39 -3 340.0-3 180.30 2.1 Give the linear regression equation (use the variable names and not X and Y) 2.2 Calculate the predicted Weight at Birth of a baby born at 40 weeks Gestational Age 2.3 Do the data present sufficient evidence to indicate that the slope differs from zero, at the 1% level of significance? Interpret your results. (Ensure you use all the steps for your hypothesis test)
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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