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# regression model

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1. Assume that the demand for bottled water is price inelastic. Are the following statements true or false? Explain.
a. When the price of bottled water decreases, the quantity sold increases.
b. The percentage change in the price of bottled water is less than the percentage change in quantity demanded.
c. Changes in the price of bottled water do not affect the number of bottled water sales.
d. Quantity demanded is non responsive to changes in price.
e. If more bottled water is sold, expenditures on bottled water will increase.
f. At this point the marginal revenue of bottled water is negative.
2. A manufacturer of computer workstations gathered average monthly sales figures from its 56 branch offices and dealerships across the country and estimated the following demand for its product:
Q = 24,750 - 4.6 P + 255A + 0.48Ppc + 0.56 Pm + 0.38 Pc
(8,688) (2.1) (296) (0.2) (0.29) (0.22)
The number in parenthesis indicates the standard errors of the parameters. The variables and their assumed values are:

Variable
Variable Name
Value
Q
Quantity
P
Price of basic model
11,550
A
86
Ppc
Average price of a personal computer
6,800
Pm
Average price of a microcomputer
26,000
Pc
Average price of a leading competitor's workstation
13,200
a. Compute the elasticities for each of the variables. On this basis, discuss the relative impact that each variable has on the demand. What implications do these results have for the firm's marketing and pricing policies
b. Conduct a t-test for the statistical significance of each variable; state whether a one- tail test or two-tail test is required. What difference, if any, does it make to use a one-tail versus a two-tail test on the results? Discuss the results of the t-tests in light of the policy implications mentioned.
c. Suppose a manager evaluating these results suggests that interest rates and the performance of the computer (typically measured in millions of instructions per second, or MIPS) are important determinants of the demand for workstations and must therefore be included in the study. How would you respond to this suggestion? Elaborate.

https://brainmass.com/economics/elasticity/regression-model-309668

#### Solution Summary

Compute the elasticities in this set.

\$2.19

## Regression Model with Advertising Expenditures and Price Index

Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following:

1) Multiple R = 0.738

2) R-square = 0.546
By using lagged values she came up with the following:

3) Multiple R = 0.755

4) R-square = 0.570

Explain the differences in using these different models. How could CoffeeTime further optimize this model and explain?

Tourism is one consideration for CoffeeTime's future. A survey of 1,233 visitors to Mumbai last year revealed that 110 visited a small cafe during their visit. Laura claims that 10% of tourists will include a visit to a cafe. Use a 0.05 significance level to test her claim. Would it be wise for her to use that claim in trying to convince management to increase their advertising spending to travel agents? Explain.

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