Investigation 4: Heart Disease A public health researcher is interested in some factors that influence heart disease. In
Posted: Wed May 11, 2022 5:31 pm
Investigation 4: Heart Disease 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.”
k) State r 2 (i.e., the coefficient of determination) for
“Biking” and “Heart.Disease” and explain what this value means in
context of the data set.
l) 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.
m) Was the prediction you made for the researcher in part (l) an
example of extrapolation? Why or why not? Write your response in
one to two complete sentences with an explanation.
n) Can we say that biking causes reduction in the heart disease
rate? Why or why not? If you cannot, provide an example of a
confounding variable. Answer these questions in one or two
sentences.
Given data from Stat crunch:
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.”
k) State r 2 (i.e., the coefficient of determination) for
“Biking” and “Heart.Disease” and explain what this value means in
context of the data set.
l) 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.
m) Was the prediction you made for the researcher in part (l) an
example of extrapolation? Why or why not? Write your response in
one to two complete sentences with an explanation.
n) Can we say that biking causes reduction in the heart disease
rate? Why or why not? If you cannot, provide an example of a
confounding variable. Answer these questions in one or two
sentences.
Given data from Stat crunch: