Compute the linear correlation coefficient between the two variables and determine whether a linear relation exists. Round to three decimal places. The table shows the number of days off last year and the earnings for the year (in thousands of dollars) for nine randomly selected insurance salesmen. Number of days off, x 3 6 9 7 12 5 18 11 8 Earnings for the year, y (thousands of dollars) 89 77 71 Click the icon to view the critical values table. O A. r= -0.991; a linear relation exists O B. r= -0.899; no linear relation exists O C. r= -0.991; no linear relation exists O D. r= -0.899; a linear relation exists 73 62 83 46 67 73

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The scatter plot shows the number of hours worked and money spent on entertainment by each of 24 students. Also shown is the line of best fit for the data. Fill in the blanks below. 70 65 60 55. Amount of 50 × 45 money spent on entertainment 40+ (in dollars) 35. × × 30 25 20 15. × 10+ 5-x 0 6 8 10 12 14 16 18 20 22 Number of hours worked (a) For these 24 students, as the number of hours increases, the amount of money spent tends to (Choose one) (b) For these 24 students, there is (Choose one) money spent. correlation between the number of hours worked and the amount of (c) Using the line of best fit, we would predict that a student working 8 hours would spend approximately (Choose one) ▼ ك ?

The scatter plot shows the relationship between the number of minutes studying for a test (x) and the Score earned (y). Make a scatterplot for the data. Time Studying (x) 40 50 60 70 80 90 100 110 Score (y) 2 3 6 7 9. +H+ 10 6. -7- 4 3 1- 10, 10 20 30 40 50 60 70 80 90 100 110 12 7:04 PM Desktop 12/8/2026