Economic
a. Q = A + B.P + C.Pᵪ + D.Ad + E.I Where, A = 807.91 B = -5.03 C = 4.86 D = 0.33 E = 0.01Q = 807.91 – 5.03P + 4.86Pᵪ + 0.33A + 0.01Ib. 1. Price variable (P) is all other things being equal – increase of $1.00 in product price will decreased demand by 5.03 cases. 2. Competitor’s price variable (Pᵪ), if all other things being equal – increase in competitor’s price by $1.00 will increase company’s demand by 4.86 cases. 3. Advertising variable (A), if all other things being equal – increase of expenditures by $1.00 in advertising will increase demand by 0.33 cases. 4. Income variable (I), if all other things being equal – increase in customer’s income by $1.00 will increase demand by 0.01 cases.c. . Evaluate the coefficient of determination for the regression model.The R2 = 90.4 per cent obtained by the model means that 90.4 per cent of demand variation is explained by the underlying variation in all four independent variables. This is a relatively high level of explained variation and implies an attractive level of an explanatory power.
d. T-testn=30 k=5Variablest-ratiot-criticalResultP(-11.022) ≥2.060Cannot reject H₀P is significantPᵪ4.833 ≥ 2.060Cannot reject H₀P is significantA3.141 ≥2.060Cannot reject H₀A is significantI7.994 ≥2.060Cannot reject H₀I is significantAll independent variables are significant.e. Forecast demand for 5 markets Regression model: Q=807.91 – 5.034P + 4.86Pᵪ + 0.33A + 0.01I Market A