The University of Texas at Austin 3 credits Statistics and Data Sciences
Introduction to applied regression analysis. Explore estimation and inference in multiple regression models; logistic regression; regression for count data; time-to-event models; and case studies in regression modeling in published work, emphasizing both the use and limitations of regression modeling in advancing scientific knowledge. The equivalent of three lecture hours a week for one semester. Pre/Corequisites: Statistics and Data Sciences 431 with a grade of at least C-; Mathematics 340L or 341 or Statistics and Data Sciences 329C with a grade of at least C-; and Computer Science 303E or 312 with a grade of at least C-.
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