From the course: 11 Useful Tips for Regression Analysis
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Polynomial variables
From the course: 11 Useful Tips for Regression Analysis
Polynomial variables
- [Instructor] Linear regression does not mean you need to model every relationship in a linear way. Many processes in real life have complex relationships that include curves and failure to model such relationships can result in biased regression estimates. So let's take a look at how we can use polynomials to fit quadratic and cubic relationships in a regression. A polynomial is a mathematical expression that uses the same variable, often, multiple times raised to various powers. The highest power or exponent, denotes the degree of the polynomial. Here's some examples of typical mathematical polynomials and expression with only a constant as a polynomial of degree zero and expression with one X is a polynomial of degree one, and then expression with one X squared and one X is a polynomial of degree two and so on. Unfortunately we cannot include a variable twice in a regression model, but we can include transformations of…
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Contents
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Weighted regression5m 36s
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(Locked)
Factor variables5m 40s
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(Locked)
Polynomial variables4m 36s
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(Locked)
Fractional variables5m 38s
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Model proportions5m 39s
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Centering5m 1s
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Missing data5m 55s
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Standardized estimates3m 22s
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Graph estimates4m 9s
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Contour plots3m 37s
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Animate results4m 18s
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