Q1) In one randomly selected location, the researcher found the biking rate was 70%. Use this information to predict the corresponding rate of heart disease in that location. Use the regression equation in part (h) to predict the rate of heart disease. Show the typed calculation in your solutions.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter9: Quadratic Functions And Equations
Section9.8: Analyzing Functions With Successive Differences
Problem 2AGP
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a) A public health researcher is interested in some factors that influence heart disease. In a survey of 68 randomly selected localities, he gathered data on the percentage of people in each locality who bike to work “Biking”, the percentage of people in each locality who smoke “Smoking”, and the percentage of people in each locality who have heart disease “Heart.Disease”. The researcher wants to find which explanatory variable will be a better predictor of the response variable, “Heart.Disease”. Investigate the relationship between the explanatory variables and response variable to help the researcher find the better predictor. The dataset is called “Heart Disease.”

b) The regression equation for “Biking” and “Heart. Disease is
= 18.115809 - 0.20845321 Biking.

Q1) In one randomly selected location, the researcher found the biking rate was 70%. Use this information to predict the corresponding rate of heart disease in that location. Use the regression equation in part (h) to predict the rate of heart disease. Show the typed calculation in your solutions.

Q2) Was the prediction you made for the researcher in part (1) an example of extrapolation? Why or why not? Write your response in one to two complete sentences with an explanation.

 

 

State r (i.e., the coefficient of determination) for "Biking" and "Heart.Disease" and
explain what this value means in context of the data set.
Transcribed Image Text:State r (i.e., the coefficient of determination) for "Biking" and "Heart.Disease" and explain what this value means in context of the data set.
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