DVD Express is a large manufacturer of affordable DVD players. Management recently became aware of rising costs resulting from returns of malfunctioning products. As a starting point for further analysis, Bridget Forrester, the controller, wants to test different forecasting methods and then use the best one to forecast quarterly expenses for 2010. The relevant data for the previous three years follows:

2007	Return	2008	Return	2009	Return
Quarter	Expenses	Quarter	Expenses	Quarter	Expenses
1	$15,000	1	$16,200	1	$16,600
2	$17,500	2	$17,800	2	$18,100
3	$18,500	3	$18,800	3	$19,000
4	$18,600	4	$17,700	4	$19,200
The result of a simple regression analysis using all 12 data points yielded the following:
	Intercept term		$16,559
	Coefficient estimate		$183.22
	R-squared		0.27
	t-statistic		1.94
	SE		1,128

The result of a simple regression analysis using all 12 data points yielded an intercept of $16,559.09 and a coefficient for the independent variable of $183.22. (R-squared = .27, t = 1.94, SE = 1128).

Required
1. Calculate the quarterly forecast for 2010 using the high-low method and regression analyses. Recommend which method Bridget should use and explain why.
2. How does your analysis in requirement 1 change if DVD Express manufactures its products in multiple global production facilities to serve the globalmarket?

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Since there is noticeable seasonality in the data (lower for periods 1, 5 and9, the first quarters of the year) it is possible to improve orn he regression model by adding a dummy variable with Os in all periods and 1s in the periods 1, 5 and 9. The result is below, which shows a much higher R squared, improved SE, and a significant t-value for the dummy variable.