BUS 660 – lecture aid4

BUS 660 – lecture aid4 - BUS 660 lecture...

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BUS 660 – lecture aid Introduction Last week's lecture illustrated the concept of simple regression and how it can be meaningfully applied to business situations. Simple linear regression essentially attempts to explain the variation of a dependent variable (e.g., Charmsville furniture sales in Lecture 3) as a linear function of the variation in an independent (explanatory) variable (e.g., Charmsville population in Lecture 3). While simple linear regression does have many applications in business, it also has limitations. Not all business situations can be best modeled using a dependent variable and one other independent variable to which it is linearly related. Business modeling tends to be a bit more complex than that. This complexity can arise for several reasons, such as: 1) The dependence between the dependent variable and the independent variable(s) may not be linear. For example, we often use the term exponential growth for a phenomenon that catches on rapidly – internet adoption in the late 1990s, for example, or growth of a hot stock. In such situations, linear growth models just do not apply. 2) The dependent variable may actually depend on more than one variable. For example, home prices in a town may depend on home size, home location, quality of the town school system, crime rate, income of residents living in and near the town, etc. 3) There may be cyclical or seasonal factors that play a role in the model. For example, electricity usage
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BUS 660 – lecture aid4 - BUS 660 lecture...

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