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STAT 874. Generalized Linear Models. 3 Credits.

This course introduces the statistical theory and inference of generalized linear models (GLMs) which deals the cases that the normality of response data is in absence. The course starts from a review of linear regression with matrix approach. The topic includes exponential distribution family, link functions, contingency tables, GLMs, quasi-GLMs, deviance, residuals, model selection and diagnostics. Students are expected to be able to apply GLMs technique to deal with real world problems in diverse areas. Prereq: STAT 768.

Statistics Doctorate

https://catalog.ndsu.edu/curriculum/graduate/statistics-doctorate/
Complete a set of core courses with a grade of B or better including  STAT 661, 662, 767, 768, and 764 or 874 .  Most of these courses will be completed during your M.S. degree.  Without permission, a maximum of two of the courses can be used to count on your plan of study.  Complete an additional 30 semester credits of statistics courses at the 600- to 800-level (does not include  STAT 711, 712, 713, 714 , 725 or 726 ).  At least 15 credits must be at the 700- to 800- level. Upon approval by the adviser and supervisory committee, up to 9 hours may be taken in Mathematics or Computer Science. It is recommended that a student have knowledge of real analysis at some level such as  MATH 650  Real Analysis I  and  MATH 750  Analysis . Pass a written comprehensive exam. This exam consists of two sections. Exam 1 covers STAT 767 and STAT 768. Exam 2 covers STAT 661, STAT 662 and STAT 764 or STAT 774. Exam 1 is two hours and Exam 2 is three hours. These exams are offered during approximately the fifth week of each semester (fall and spring). A maximum of two attempts is allowed. STAT 899 research credits can not be taken during the first two semester in the graduate program at NDSU. Summer does not count as a semester.