1) Is there a relationship between product (level of treadmill) and gender? Test at the 5% level of significance, and show all 6 steps of the hypothesis testing procedure. In step 6, be sure to indicate why the company would want to know if there is such a relationship! HINT: first make a pivot table with product in the rows and gender in the columns. Those are your observed frequencies. Then find the expected frequencies and your chi-square. NOTE: do you understand why this is chapter 12 material and not chapter 13 material?
2) Is there a relationship between a person’s age and the number of miles they intend to walk/run on the treadmill each week? And can you predict the number of miles a 27-year-old would walk/run? Here’s what I’d like you to do.
· First form a scatter diagram. Does there seem to be a linear relationship between age and miles?
· Now run the regression procedure that can use age as a predictor of miles. Remember, all of this is to be done using Excel…no hand calculations are necessary!
· Interpret the correlation coefficient and the coefficient of determination in practical form.
· Predict the number of miles a 27-year-old would walk/run
· Interpret the slope
2) Is there a relationship between a person’s age and the number of miles they intend to walk/run on the treadmill each week? And can you predict the number of miles a 27-year-old would walk/run? Here’s what I’d like you to do.
· First form a scatter diagram. Does there seem to be a linear relationship between age and miles?
· Now run the regression procedure that can use age as a predictor of miles. Remember, all of this is to be done using Excel…no hand calculations are necessary!
· Interpret the correlation coefficient and the coefficient of determination in practical form.
· Predict the number of miles a 27-year-old would walk/run
· Interpret the slope
