Kim K. asks you to develop a demand forecast for her perfume line. Using the data provided, you find a regression model, y = 4 + 3.36x₁ + 5x₂, with the undernoted parameters.

Parameters: R²= 0.70

Sig of F: 0.04

p-value of x₁= 0.05

p-value of x₂= 0.08

x₁ denotes Consumer Income

x₂ denotes Advertising

y denotes Demand

Would you advise KIm that the above model can be (technically) used for forecasting (disregard your responses to any other related question) ?

	a.	No
	b.	Yes

Your boss is not happy with your computed EOQ for an expensive item. What should you typically do first to lower the EOQ figure?

		Work to reduce supplier price
		Work to reduce ordering cost
		Work to increase holding cost
		Work to reduce customer demand.

System A has an average arrival rate of 12/hr (std deviation is 3) and an average service rate of 14/hr (std dev.is 2).

System B has an average arrival rate of 24/hr (std dev. is 5) and an average service rate of 28/hr (std dev. is 4).

Based on the above data, which system has a greater probability of a line developing?

	a.	The probability of a line developing is the same for system A and system B
	b.	System B
	c.	System A

Your boss is not happy with your computed EOQ for an expensive item. What should you typically do first to lower the EOQ figure?

		Work to reduce supplier price
		Work to reduce ordering cost
		Work to increase holding cost
		Work to reduce customer demand.