Part III: Regression and Correlation
Based on what you have learned from your research on regression analysis and
correlation, answer the following questions about the Body Fat Versus Weight
data set:
When performing a regression analysis, it is important to first identify
your independent/predictor variable versus your dependent/response variable, or
simply put, your x versus y variables. How do you decide which
variable is your predictor variable and which is your response variable?
Based on the Body Fat Versus Weight data set, which variable is the
predictor variable? Which variable is the response variable? Explain.
Using Excel, construct a scatter plot of your data.
Using the graph and intuition, determine whether there is a positive
correlation, a negative correlation, or no correlation. How did you come to this
conclusion?
Calculate the correlation coefficient, r, and verify your
conclusion with your scatter plot. What does the correlation coefficient
determine?
Add a regression line to your scatter plot, and obtain the regression
equation.
Does the line appear to be a good fit for the data? Why or why not?
Regression equations help you make predictions. Using your regression
equation, discuss what the slope means, and determine the predicted value of
body fat (y) when weight (x) equals 0. Interpret the meaning
of this equation.
Part IV: Putting it Together
Your analysis is now complete, and you are ready to report your findings to
your boss. In one paragraph, summarize your results by explaining your findings
from the statistical measures, hypothesis test, and regression analysis of body
fat and weight for the 252 men attending Silver’s Gym.
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