Final answer:
The correlation coefficient measures the strength and direction of the linear relationship between two variables. In this case, the correlation coefficient is approximately 0.413.
Step-by-step explanation:
The correlation coefficient measures the strength and direction of the linear relationship between two variables. To find the correlation coefficient, we can use the formula:
r = [(nΣxy) - (Σx)(Σy)] / sqrt([(nΣx^2) - (Σx)^2][(nΣy^2) - (Σy)^2])
Using the provided data:
Average of the X values (Age): (14 + 25 + 19 + 35 + 20 + 12 + 5) / 7 = 19.71
Average of the Y values (Score): (360 + 293 + 315 + 212 + 315 + 331 + 404) / 7 = 317.57
Σxy: (14 * 360) + (25 * 293) + (19 * 315) + (35 * 212) + (20 * 315) + (12 * 331) + (5 * 404) = 769211
(Σx)(Σy): (14 + 25 + 19 + 35 + 20 + 12 + 5)(360 + 293 + 315 + 212 + 315 + 331 + 404) = 2021818
(nΣx^2) - (Σx)^2: (7 * [(14^2) + (25^2) + (19^2) + (35^2) + (20^2) + (12^2) + (5^2)]) - ([(14 + 25 + 19 + 35 + 20 + 12 + 5)^2]) = 3514
(nΣy^2) - (Σy)^2: (7 * [(360^2) + (293^2) + (315^2) + (212^2) + (315^2) + (331^2) + (404^2)]) - ([(360 + 293 + 315 + 212 + 315 + 331 + 404)^2]) = 2384668
Using these values, we can calculate the correlation coefficient:
r = [(7 * 769211) - (2021818)] / sqrt([(7 * 3514) - (2021818)][(7 * 2384668) - (2021818)]) = 0.413
Therefore, the correlation coefficient between the variables is approximately 0.413.