Investigation 4: Heart Disease A public health researcher is interested in some factors that influence heart disease. In

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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.”
g) Copy and paste the fitted line plot for “Biking” and
“Heart.Disease” into your solutions document. This StatCrunch graph
appears on page 2 of your StatCrunch output (i.e., click the right
arrow at the bottom of your regression output to find the
image).
h) Type the regression equation for “Biking” and “Heart.Disease”
in context into your solutions document. You may copy and paste it
from your output in part (f).
i) Interpret the slope of the regression line (in context of
this data set) for “Biking” and “Heart.Disease”.
j) Is it meaningful to interpret the y-intercept for “Biking”
and “Heart.Disease”? Why or why not?
Given data from Stat crunch: