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STAT 421. Applied Regression Methods

Credits: 3
Department: Statistics
Description: Advanced regression methods focused on complex real-world data. Model checking and diagnostics, model building, transformations, polynomial regression, logistic regression, general linear models, nonparametric regression methods.
Prerequisites: STAT 321
Semester Offered: Spring
Grading Method: ABCDF

Student Learning Outcomes

1. Determine meaning and perform computation of regression coefficients and diagnostics.
2. Select the best regression equation based on a given criterion.
3. Use computer software to perform a variety of regression analysis and ANOVA.
4. Apply inferential methods to test hypotheses in regression and a variety of ANOVA problems.
5. Use the logistic regression analysis for binary response data.

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