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Data-Driven Business Decisions by Chris J. Lloyd

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CHAPTER 16

The Reliability of Regression-Based Decisions

16.0. Introduction: What Is the Issue?

You have data on 108 apartments sold in Deepwater Bay in 1995. There is a clear positive association between sale price and area. The correlation is 0.828 and the least squares regression line is

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There are various reasons why this regression equation might be useful. In this particular example, it can answer at least three pertinent questions.

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What is the value of an extra 100ft2 of floor space? The branch office is having a sales review. Even though there was no apartment of exactly 1500ft2 in their database, what is the fair market price for such apartments? A client comes into the office with an apartment of a certain size and wants you to quote a range for likely sale price. What do you quote?

It is quite easy to give numerical answers to these questions. However, a proper statistical answer will not only give a best estimate, but will also evaluate the accuracy of this estimate. These accuracy estimates depend on the assumptions of the regression model. So a really thorough statistical answer would also verify the appropriateness of these assumptions.

16.1. Three Kinds of Questions That Regression Answers

Suppose that we have two business variables X and Y and are mainly interested ...

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