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STA X35 STA 235  Data Science for Business Applications  2 Hours

2 Lecture Hours  0 Lab Hours  
Examine data science for business applications at the intermediate level. Explore building and validating predictive models; advanced regression modeling, including an in-depth treatment of regression; models for binary outcomes; and causal inference. Statistics 235 and 235H may not both be counted. The equivalent of two lecture hours a week for one semester.
Pre/Corequisites: Statistics 301 or 301H, Mathematics 408Q or credit or registration for Mathematics 408D, 408L, or 408S.  
Restrictions: Restricted to students in the McCombs School of Business.  
Grading: Letter Grade  
Repeatable for credit: No  
Academic Level: Upper Division