AIM 5004

Predictive Models

Yeshiva University · UGRD · Fall 2026

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Predictive modeling answers the question, 'What will happen next?' Linear regression and logistic regression are foundational predictive modeling methods, used to predict continuous and categorical output respectively. The main topics covered in this course include simple and multiple linear regression, variable selection and shrinkage methods, binary logistic regression, count regression, weighted least squares, robust regression, generalized least squares, multinomial logistic regression, generalized linear models, panel regression, and nonparametric regression. Prerequisite(s): Data Acquisition and Management; Computational Statistics and Probability.

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Class #yeshiva-AIM5004Fall 2026UGRD3 credits
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