Answer:
a. y = 27.5 - 0.3X
b. 20
Explanation:
y = a + bX
usin the table in the attachment i added, we so for the regression equaion
n = 8
∑xy = 4460
∑x = 280
∑y = 136
∑x²= 10800

from here we solve for a

a. the estimated regression equation
y = 27.5 - 0.3X
b. at x = 25
y = 27.5 - 0.3(25)
y = 20 is the number of defective parts.