Forecasting New Production Demand

Mark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for their line of stereo speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are the main drivers in sales and wants to use regression analysis to figure out which factor drives more demand for their particular market. Pertinent information was collected by an extensive marketing project that lasted over the past 10 years and was reduced to the data that follow:

Year Sales/Unit Price/Unit Advertising
(Thousands) ($000)

1996 400 280 600
1997 700 215 835
1998 900 211 1,100
1999 1,300 210 1,400
2000 1,150 215 1,200
2001 1,200 200 1,300
2002 900 225 900
2003 1,100 207 1,100
2004 980 220 700
2005 1,234 211 900
2006 925 227 700
2007 800 245 690

Perform a regression analysis based on these data using Excel®. Answer the following questions based on your results.

1. Which variable, price or advertising, has a larger effect on sales and how do you know?
2. Predict average yearly speaker sales for Speakers and Company based on the regression results if the price was $300 per unit and the amount spent on advertising (in thousands) was $900.