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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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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 ...

Solution Summary

This solution helps CoffeeTime company by advising its advertising strategy and expenditures based on an analysis of a regression and then hypothesis testing.

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