DATASCI 451 - Bayesian Data Analysis
Fall 2022, Section 001
Instruction Mode: Section 001 is  In Person (see other Sections below)
Subject: Data Science (DATASCI)
Department: LSA Statistics
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Details

Credits:
3
Requirements & Distribution:
BS
Waitlist Capacity:
99
Enforced Prerequisites:
(STATS 412 or STATS 425) and (STATS 306 or EECS 280).
BS:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
Repeatability:
May not be repeated for credit.

Description

The course is an introduction to both the principles and practice of Bayesian inference for data analysis. At the end of this course students will be familiar with the Bayesian paradigm, and will be able to analyze different classes of statistical models. The course gives an introduction to the computational tools needed for Bayesian data analysis and develops statistical modeling skills through a hands-on data analysis approach. Topics include: prior/posterior distributions, Bayes rule, Markov Chain Monte Carlo computations, linear and generalized linear models, mixed effect models, hierarchical models, analysis of spatial data, model selection and comparison, model checking.

Schedule

DATASCI 451 - Bayesian Data Analysis
Schedule Listing
001 (LEC)
 In Person
33615
Open
1
 
79Enrollment Management
19
TuTh 11:30AM - 1:00PM
Note: The Department of Statistics must allow students who are declared in its programs the opportunity to register for Statistics classes needed to complete their programs. Any remaining seats reserved for Statistics students will be opened after registration is complete and waitlists have been evaluated.

Textbooks/Other Materials

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Syllabi

Syllabi are available to current LSA students. IMPORTANT: These syllabi are provided to give students a general idea about the courses, as offered by LSA departments and programs in prior academic terms. The syllabi do not necessarily reflect the assignments, sequence of course materials, and/or course expectations that the faculty and departments/programs have for these same courses in the current and/or future terms.

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CourseProfile (Atlas)

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