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STAT 671 - Linear Models | ||
This course discusses the estimation of parameters in the multiple linear regression model by the least-squares method . Topics covered include the statistical properties of the least-squares estimators, the Gauss-Markov theorem, estimates of residual and regression sums of squares, distribution theory under normality of the observations, assessment of normality, variance stabilizing transformations, examination of multicollinearity, variable selection methods, logistic regression for a binary response, log-linear models for count data, and generalized linear models.
Credits: 3.000 Levels: Graduate Schedule Types: Lecture, Final Exam Precluded: MATH-471 MATH-499 MATH-671 STAT-471 Students cannot receive credit for the course being described and the course(s) listed as Precluded Restrictions: Must be enrolled in one of the following Levels: Graduate
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