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Multiple regression:Interpret coefficients

See attachment.

7. The following equation was estimated as the demand function for gasoline (number of observations equals 1,682, and standard errors are in parentheses):
_lnQ = 3.95 - 0.525lnP - 0.263lnAge + 0.129lnY - 0.211lnPc + 0.796LnD - 0.103U + 0.182R_
(1.51) (0.105) (0.920) (0.65) (0.156) (0.063) (0.031) (0.036)
_with R-squared = 0.39, where Q-gallons of gas demanded per week by a household, P = price per gallon of gasoline, Age = age of the head of household, Y = income level, and Pc = an index of the price for automobiles, D = Number of drivers, U = urban (inner city) location, R = rural (not suburban) location.

a. Interpret the coefficients of the various variables in the preceding demand equation.
b. How much confidence do you have in each of these coefficient estimates?

NOTE: the standard error in parenthesis correspond with the coefficient above them. So, the following matches:

3.95 => 1.51
0.525 => 0.105
0.263 => 0.920
0.129 => 0.65
0.211 => 0.156
0.796 => 0.063
0.103 => 0.031
0.182 => 0.036

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Hi

Please find attached response to your questions. The answer to both questions are provided ...

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This posting contains interpretation of following multiple regression results.

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