STAT 3301: Statistical Modeling for Discovery I
Statistical models for data analysis and discovery in big-data settings, with primary focus on linear regression models. The challenges of building meaningful models from vast data are explored, and emphasis is placed on model building and the use of numerical and graphical diagnostics for assessing model fit. Interpretation and communication of the results of analyses is emphasized.
Prereq: C- or better in 3202; or 4202 and 5730; or permission of instructor. Prereq or concur: Math 2568; or permission of instructor.
Prereq: C- or better in 3202; or 4202 and 5730; or permission of instructor. Prereq or concur: Math 2568; or permission of instructor.
Credit Hours
3
Typical semesters offered are indicated at the bottom of this page. For confirmation check the Schedule of Classes list on the Registrar's website.
Recent Syllabi
AU20 STAT 3301 Hans [pdf]
AU20 STAT 3301 Smillie [pdf]
AU18 STAT 3301 Hans [pdf]
AU17 STAT 3301 Hans [pdf]
AU16 STAT 3301 Hans [pdf]
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Semester(s) Offered:
Autumn