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The regression models that we introduced in Sections 14 2 and

The regression models that we introduced in Sections 14.2 and 14.6 are linear in the x’s, but, more important, they are also linear in the β’s. Indeed, they can be used in some problems where the relationship between the x’s and y is not linear. For instance, when the regression is parabolic and of the form

We simply use the regression equation µY|x = β0 + β1x1 + β2x2 with x1 = x and x2 = x2. Use this method to fit a parabola to the following data on the drying time of a varnish and the amount of a certain chemical that has been added:

Also, predict the drying time when 6.5 grams of the chemical is added.

We simply use the regression equation µY|x = β0 + β1x1 + β2x2 with x1 = x and x2 = x2. Use this method to fit a parabola to the following data on the drying time of a varnish and the amount of a certain chemical that has been added:

Also, predict the drying time when 6.5 grams of the chemical is added.

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