Quality Control A manufacturer recorded the number of defective items (y) produced on a given day by each of 10 machine operators and also recorded the average output per hour (x 1 ) for each operator...

Quality Control
A manufacturer recorded the number of defective items (y) produced on a given day by each of 10 machine operators and also recorded the average output per hour (x₁) for each operator and the time in weeks from the last machine service (x₂).

The printout that follows resulted when these data were analyzed using the MINITAB package using the model:

E(y) = β₀
+ β₁x₁
= β₂x₂

Regression Analysis: y versus x1, x2

a. Interpret R²
and comment on the fit of the model.

b. Is there evidence to indicate that the model contributes significantly to the prediction of y at the a = .01 level of significance?

c. What is the prediction equation relating
 and x₁
when x₂
= 4?

d. Use the fitted prediction equation to predict the number of defective items produced for an operator whose average output per hour is 25 and whose machine was serviced three weeks ago.

e. What do the residual plots tell you about the validity of the regression assumptions?