Mark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for their line of company 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 its particular market. Pertinent information was collected by an extensive marketing project that lasted over the past 12 years and was reduced to the data that follow: UNIT SALES PRICE $ PER ADVERTISING YEAR (THOUSANDS) UNIT $000) 1 96 282 600 696 219 829 896 206 1, 118 1, 285 210 1, 413 1, 155 219 1, 214 1, 186 209 1, 285 896 218 907 1, 118 206 1, 118 9 985 220 708 10 1, 334 206 907 11 926 226 708 12 820 236 682 a. Perform a regression analysis based on these data using Excel. Note: Negative values should be indicated by a minus sign. Round your answers to 4 decimal places. y bar = + Price + advertising c. Predict average yearly speaker sales for Speakers and Company based on the regression results if the price was $296 per unit and the amount spent on advertising (in thousands) was $895. Note: Enter your answer in thousands. Round your intermediate calculations and final answer to 2 decimal places. Forecasted sales thousand units