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Part III: Regression 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 yvariables. 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? Discuss the strength of the correlation coefficient calculated, and if the correlation is positive or negative.
  • 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 weight when body fat is zero. Interpret the meaning of this result.

Part IV: Putting it Together

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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