Examine the accompanying sample data for the variables y and x. Complete parts a throughd below. 1 3 4 y 9 8 8 7 5 a. Construct a scatter plot of these data. Describe the relationship between x and y. Choose the correct scatter plot below. O A. В. D. 11- 11- Describe the relationship between x and y. Choose the correct answer below. O A. There appears to be a negative linear relationship between x and y, because y increases as x increases. O B. There appears to be a negative linear relationship between x and y, because y decreases as x increases. O C. There appears to be a positive linear relationship between x and y, because y increasesas x increases. O D. There appears to be a positive linear relationship between x and y, because y decreasesas x increases. O E. There appears to be no relationship between x and y. b. Calculate the sum of squares error for the following equations: (1) y = 9.4 - 0.1x, (2) y = 10.1 – 0.9x, and (3) y = 10.7 –1.7x. The sum of squares error for the equation y= 9.4 - 0.1x is. The sum of squares error for the equation y= 10.1 - 0.9x is The sum of squares error for the equation y = 10.7 - 1.7x is (Round to two decimal places as needed.) c. Which of these equations provides the "best" fit of these data? Describe the criterion used to determine "best" fit. O A. The equation y= 10.1 - 0.9x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. O B. The equation y = 10.7 – 1.7x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. O C. The equation y= 10.1- 0.9x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares. O D. The equation y= 9.4 - 0.1x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares. O E. The equation y = 10.7 – 1.7x provides the best fit because it has the highest sum of squares error. This criterion is called the method of most squares. O F. The equation y= 9.4 - 0.1x provides the best fit because it has the lowest sum of squares error. This criterion is called the method of least squares. d. Determine the regression line that minimizes the sum of squares error. (Round to one decimal place as needed.)