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To better understand complex processes, we study how variables are related to one another, and how they work in combination. Therefore, we want to make inferences about more than one variable at time? Elementary statistical methods might not apply. In this course, we study the tools and the intuition that are necessary to analyze and describe such data sets. Topics covered will include data visualization techniques for high dimensional data sets, parametric and non-parametric techniques to estimate joint distributions, techniques for combining variables, as well as classification and clustering algorithms.
Format: lecture; This will be a hybrid course for students who are both remote and in-person, with a mix of synchronous and asynchronous elements
Grading: yes pass/fail option,
no fifth course option
homework, project/presentations, possibly one or two exams.
MATH 250, and STAT 346 or permission of instructor
students interested in statistics which have solid background in math and stat
It is an advanced statistics class with prerequisites that are QFR courses