STAT 346
Regression Theory and Applications Spring 2024 (also offered Fall 2023)
Division III Quantitative/Formal Reasoning
This is not the current course catalog

Class Details

This course focuses on the building of empirical models through data in order to predict, explain, and interpret scientific phenomena. Regression modeling is the most widely used method for analyzing and predicting a response data and for understand the relationship with explanatory variables. This course provides both theoretical and practical training in statistical modeling with particular emphasis on simple linear and multiple regression, using R to develop and diagnose models. The course covers the theory of multiple regression and diagnostics from a linear algebra perspective with emphasis on the practical application of the methods to real data sets. The data sets will be taken from a wide variety of disciplines.
The Class: Format: lecture
Limit: 30
Expected: 20
Class#: 3524
Grading: yes pass/fail option, no fifth course option
Requirements/Evaluation: Weekly homework, theory and data analysis exams, final course project.
Prerequisites: MATH/STAT 341, MATH 250, and at least one of STAT 201 or 202. Or permission of the instructor.
Enrollment Preferences: Statistics Majors
Distributions: Division III Quantitative/Formal Reasoning
QFR Notes: This course prepares students in the use of quantitative methods for the modeling, prediction and understanding of scientific phenomena.

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