Mark Price, the new productions manager for Speakers and Company, needs to find

Question

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 ollected by an extensive marketing project that lasted over the past 10 years and was reduced to the data that follow ADVERTISING 1998 1999 2000 2001 2002 2003 2004 398 700 898 1,290 1,153 1,188 898 1,116 988 1,332 924 818 SANDS) PRICE S/UNIT($000) 585 827 1,116 1,411 1,213 1,290 905 1,116 706 905 706 680 208 216 218 207 216 2006 2007 2008 218 208 221 238 a. Perform a regression analysis based on these data using Excel. (Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.) Price + Advertising c. Predict average yearly speaker sales for Speakers and Company based on the regression results if the price was $298 per unit and the amount spent on advertising (in thousands) was $898. (Enter your answer in thousands. Do not round intermediate calculations. Round your answer to the nearest whole number.) Forecasted sales units

Explanation / Answer

Running a regression analysis on the above data we have

Therefore

Y=1980.49+ (-6.187)*price+ 0.385*advertising

b.

substituting the value of price =298

advertising = 898

in the above equation we have

Y= 1980.49+ (-6.187)*298+ 0.385*898

=1980.49-1843.726+345.73

=482.494

SUMMARY OUTPUT Regression Statistics Multiple R 0.836168745 R Square 0.69917817 Adjusted R Square 0.632328875 Standard Error 160.5772455 Observations 12 ANOVA df SS MS F Significance F Regression 2 539372.7839 269686.392 10.45902076 0.004491507 Residual 9 232065.4661 25785.05178 Total 11 771438.25 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1980.493479 722.1706082 2.742417728 0.022757369 346.8300647 3614.156893 346.8300647 3614.156893 Price   (X1) -6.187715037 2.585590694 -2.393153353 0.040348266 -12.03672755 -0.33870253 -12.03672755 -0.33870253 Advertising (in $000)   (X2) 0.38470992 0.223319695 1.722686933 0.119042997 -0.120474327 0.889894167 -0.120474327 0.889894167

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