For Exercises 23–37, follow these steps. You have already calculated the regression equation in Exercises 37–51 in Section 4.2. Do the following.

  1. Calculate the sum of squares error, SSE.
  2. Compute and interpret the standard error of the estimate, .
  3. Calculate the total sum of squares, SST.
  4. Find the sum of squares regression, SSR.
  5. Calculate and interpret the coefficient of determination, .
  6. Use to calculate and interpret the correlation coefficient, .

Question 4.224

23. Video Game Sales. See Exercise 37 in Section 4.2.

4.3.23

(a) 0.59123 (b) 0.443933. The typical difference between the predicted number of total sales in millions of units and the actual observed number of total sales in millions of units is 0.443933 million units. (c) 1.30800 (d) 0.71677 (e) 0.5480. Therefore, 54.80% of the variability in total sales in millions of units is accounted for by the linear relationship between total sales in millions of units and weeks on top 30 list. (f) 0.7403. This value of is close to the maximum value . We would therefore say that the total sales in millions of units and weeks in the top 30 are positively correlated. As the number of weeks in the top 30 increases, the total sales in millions of units also tends to increase.