(Offered as STAT 370 and MATH 370) This course examines the theory underlying common statistical procedures including visualization, exploratory analysis, estimation, hypothesis testing, modeling, and Bayesian inference. Topics include maximum likelihood estimators, sufficient statistics, confidence intervals, hypothesis testing and test selection, non-parametric procedures, and linear models.
Students will engage with the material through synchronous lectures, individual and team based learning activities, and office hours. In addition, some lecture videos and discussion boards will be made available on Moodle for asynchronous engagement.
Requisite: STAT 111 or STAT 135 and STAT 360, or consent of the instructor. Limited to 25 students. Spring semester. Professor Donges.
If Overenrolled: Priority for Statistics majors, then Mathematics majors.