BNAD 276 Lecture Notes - Lecture 8: Simple Linear Regression, Polynomial Regression, Scatter Plot
18 Mar 2017
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Document Summary
Introductory case: the rental market in ann arbor, michigan. Marcela treisman is analyzing the rental market in ann arbor, the home of the university of michigan. She has data on monthly rent, along with several property characteristics. Marcela will evaluate models that predict rental income from home characteristics. She will select the most appropriate model and make predictions for rental income for specific property characteristics. A simple linear regression model, y = 0 + 1x + , is easy to interpret: if x increases by one unit, we expect y to change by 1. However, sometimes the relationship cannot be represented by a straight line and, rather, must be captured by an appropriate curve. 15 places the restriction of linearity on the parameters, not the x values, we can capture many interesting nonlinear relationships within this framework. For example, a firm"s average cost curve tends to be (cid:862)u-shaped(cid:863)
