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Lagged Values

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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:

1. Multiple R=0.755
2. R-square=0.570

Can you explain the differences between the normal and lagged values for this info? Also, I need to explain how we could further optimize this.

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Solution Summary

This solution discusses the type of model the data was based on, the differences between lagged and normal values and the overall impact on the coffee times price index.

Solution Preview

The first model is concurrent model. In this we assume that the advertisement expenditure in this period affects the coffee times price index for this period. However, this may not be true. The advertising has two type of effects..one is current ...

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