Regression analysis. Problems in interpreting regression coefficients. Estimation, including two-stage least squares. Guided regression: building linear models, selecting carriers. Regression residuals. Analysis of variance. Nonparametric regression. Factorial designs, response surface methods. Prerequisite: either STAT 342, STAT 421, or STAT 481/ECON 481; recommended: MATH 308. Offered: W.
The course is a basic introduction to regression, at an undergraduate level. If you want a higher level introduction, and have linear algebra, you might want to consider STAT 504.
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