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STAT 346
Regression Theory and Applications Fall 2020 (also offered Spring 2021)
Division III Quantative/Formal Reasoning

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, logistic 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: 15
Expected: 15
Class#: 2664
Grading: no pass/fail option, no fifth course option
Requirements/Evaluation: exams, homework, and a project
Prerequisites: MATH 250 and at least one of STAT 201, 202 or 302. Or permission of instructor
Enrollment Preferences: Statistics Majors
Distributions: Division III Quantative/Formal Reasoning
QFR Notes: This course prepares students in the use of quantitative methods for the modeling, prediction and understanding of scientific phenomena.
Attributes: EVST Methods Courses

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