2020-2021 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 Fall 2024 Class Schedule.
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