Suppose Y is related to R and S in the following nonlinear way:

Y = aR^bS^c

a. How can this nonlinear equation be transformed into a linear form that can be analyzed by using multiple regression analysis?Sixty-three observations are used to obtain the following regression results:b. Test each estimated coefficient for statistical significance at the 5 percent level of significance. What are the exact significance levels for each of the estimated coefficients?c. Test the overall equation for statistical significance at the 5 percent level of significance. Interpret the p-value on the F-statistic.d. How well does this nonlinear model fit the data?e. Using the estimated value of the intercept, compute an estimate of a.f. If R 5 200 and S 5 1,500, compute the expected value of Y.g. What is the estimated elasticity of R? Of S?

Transcribed Image Text:

DEPENDENT VARIABLE: LNY R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 63 0.8151 132.22 0.0001 PARAMETER STANDARD VARIABLE ESTIMATE ERROR T-RATIO P-VALUE INTERCEPT -1.386 0.83 -1.67 0.1002 LNR 0.452 0.175 2.58 0.0123 LNS 0.30 0.098 3.06 0.0033