2022-2023 Graduate Catalogue Archived Catalogue
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DSC 512 - Linear Methods for Data Science Course Description: Linear methods including: linear algebra, linear regression, multiple linear regression, regression diagnostics, logistic regression. All concepts coded in SAS and based on data from various sources; therefore, in addition to the statistical methods, programming concepts include reading and writing data from and to raw text files, spreadsheets and relational databases. Six lecture hours and two laboratory hours per week for each week of the half-semester session.
Credit Hours: 3
Corequisite Courses: DSC 502 Prerequisite Courses: None Additional Restrictions/ Requirements: None Course Repeatability: Course may not be repeated
ADDITIONAL COURSE INFORMATION
Equivalent Courses: None Undergraduate Crosslisting: None Additional Course Fees: None Course Attribute: None
Click here for the Spring 2025 Class Schedule.
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