# The number in parenthesis below each parameter estimate is the standard error of the estimate of that parameter. Assume that the number of observations used to generate these results was large (i.e., >30). The variables and their assumed values are: 5.      A manufacturer of computer workstations has estimated the following demand for its product:

R2 = 0.68
SEE = 786
F = 21.25
The number in parenthesis below each parameter estimate is the standard error of the estimate of that parameter. Assume that the number of observations used to generate these results was large (i.e., >30).
The variables and their assumed values are:
Q = quantity (units)
P = Price of basic model = \$7,000
A = Advertising expenditures (in thousands of dollars) = 52
PPC = Average price of a personal computer = \$4,000
PM = Average price of a minicomputer = \$15,000
PC = Average price of a leading competitor’s workstation = \$8,000

a.       Compute the elasticities for each of the variables. Discuss the relative importance that each variable has on demand. What implications can you draw for the firm’s marketing and pricing decisions?

b.      Conduct a significant test for each of the variables. Discuss the results of the t-tests in light of your suggestions in part a

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