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After the first exam in a statistics course, the professor surveyed 14 randomly-selected students to determine the relation between the amount of time they spent studying for the exam and exam score. She found that a linear relation exists between the two variables. The least-squares regression line that describes this relation is: y​=6.3333x+53.0298.

Required:
a. Predict the exam score of a student who studies 2 hours.
b. Interpret the slope.
c. What is the mean score of students who did not study?
d. A student who studies 5 hours for the exam scored 81 on the exam. Is this student's exam score above or below average among all students who studies 5 hours?

Respuesta :

Solution :

Given :

Equation :

y = 6.3333 x + 53.0298

Here, x = number of hours studied

         y = the exam score

a). To predict the exam score, we have to replace x in the least square regression line by 2 :

   y = 6.3333 x + 53.0298

   y = 6.3333 (2) + 53.0298

      = 65.6964

Thus he predicted exam score is 65.6964

b). The slope is the co-efficient of x in the least squares regression line :

  Slope = 6.3333

 The slope represents the average increase in y as x increases by 1.

  The exam score increases on average by 6.3333 points per hour studied.

c). The mean score of the [tex]\text{ students who did not study}[/tex] (studied 0 hours) is obtained by replacing x in the least squares regression line by 0 :

  y = 6.3333 x + 53.0298        

 y = 6.3333 (0) + 53.0298

    = 53.0298

d). To predict the exam score of a student who studied 5 hours, we replace x in the least squares regression line by 2 :

   y = 6.3333 x + 53.0298

   y = 6.3333 (5) + 53.0298

   y = 84.6963

Thus the average exam score of a student who studied 5 hours is 84.6963

Since the actual exam score 81 is less than the average exam score of 84.6963 the student's exam score is below the average.

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