Question

Attem 1 Hou ences The manufacturer of a light fixture believes that the dollars spent on advertising, the price of the fixture and the number of retail stores selling the fixture in a particular month influence the light fixture sales. The manufacturer randomly selects 10 months and performs a regression analysis - part of the output appears below. The sales are in thousands of units per month, the advertising is given in hundreds of dollars per month, the price is the unit retail price in a given month. Predictor Constant Advertising Price Stores Coet 30.992 0.8202 -0.32502 1.841 St Dev 7.728 0.5023 0.08935 3.855 T 4.01 1.63 -3.64 0.48 Р 0.007 0.154 0.011 0.650 S = 5.465 R-S9 = 96.74 R-Sq(adj) - 95.0+ Analysis of Variance Source DF Regression 3 Residual Error 6 SS 5179.2 179.2 MS 1726.4 29.9 T 57.81 6.000 What is the best interpretation of the coefficient of price? All of the above As price increases by $100 we expect sales to decrease by 32.502 thousand units, everyhing else being constant As price increases by $10 we expect sales to decrease by 32502 thousand units, everything else being constant As price increases by $1 we expect sales to decrease by 0,32502 thousand units, everything else being constant « Previous Next

Answer 1

#the regressin equation is

y^=30.992+0.6202*advertising-0.32502*price+1.041*store

#the best interpretation of the coeffficent of price

As price increase by $1 we expect sales to decrease by 0.32502 thousand units every thing else being constant

increase by $10 decrease by 3.2502

increase by $100 decrease by 32.502

All of the obove are the correct option

Option A is correct