Topics in linear, generalized linear, and nonlinear models with fixed and random predictors, and balanced and unbalanced cases. Statistical topics integrated with the use of the computer packages SAS and R.
This course can be applied toward:
STAA 552 (Generalized Regression Models); STAA 553 (Experimental Design); concurrent registration or written consent of instructor. This is a partial-semester course.
Tuition includes access to lecture recordings which are available by streamed video. Lecture recordings may also be available by download or on DVD. To determine viewing options, contact the Department of Statistics degree program staff at firstname.lastname@example.org. Visit the Department of Statistics website to learn more about what to do after registration, including creating your eID (if necessary) and accessing your course.
Textbooks and Materials
Kirsten Eilertson is originally from Minnesota. She earned her PhD in Statistics from Cornell University. She is an applied statistician, and has previously worked at The Gladstone Institutes at UC San Francisco and Penn State University. Her recent research has focused on modeling the impact of vaccination programs on disease burden in low- and middle-income countries. In her free time you may find her planning her next travel itinerary or hiking with her dog and husband, while optimistically anticipating The Winds of Winter by George R.R. Martin.