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Daniel DeWees
Justin Widjaja
Samuel Djahanbani
April 5, 2012
Data Analysis
A. To determine the pricing policy of the firm, we:
1) Use the linear regression method to find the
marginal revenue
Price
Quantity
Data Analysis
2) Use the linear regression method to find the
marginal cost
Data Analysis
3) We derive a formula for marginal revenue and
marginal cost within this relevant range
 If MR>MC at our current price, our product is
overpriced, and vice versa
Demand Increase
B. With a 10% increase in demand at every price:
 The total cost curve remains unchanged and it results
in a marginal cost of 9.94 given our current capacity
 Our demand curve has changed and is now:
P=-0.0015Q+29.22
 Giving us a total revenue = P*Q= -0.00315Q2+29.22Q
 And a marginal revenue = -0.0063Q+29.22
Demand Increase
 At the current price of 20 our quantity sold is 2750
 Our resulting marginal revenue is then 11.9, which is
greater than our marginal cost of 9.44
 Since at our current price MR>MC, we learn that our
product is overpriced given our current fixed factors
of production
Sensitivity Analysis
C. Optimistic Marketing Numbers:
 There would be less of an impact on the sales from a
change in the price than she predicted
 Based on our analysis in part b, we determined that the
product was overpriced if the demand were to increase by
10%
 The magnitude of the excess in price would be lower (thus
the product would be less overpriced) if the marketing
manager was just a bit optimistic in her answers
Sensitivity Analysis
 If she was way too optimistic, it is possible our answer
would change to the point where the product would be
priced perfectly or even underpriced under the set
conditions
 If sales barely changed at all (or even decreased) from
a 10% or 20% increase in price, the product could
become underpriced
 With an increase in demand, the marginal cost is
constant, but the marginal revenue could be lower