Jessi Cisewski

Jessi Cisewski's picture
Assistant Professor of Statistics and Data Science
24 Hillhouse Avenue, New Haven, CT 06511-6814, Room 208
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STAT 100b / STAT 500b Introductory Statistics

An introduction to statistical reasoning. Topics include numerical and graphical summaries of data, data acquisition and experimental design, probability, hypothesis testing, confidence intervals, correlation and regression. Application of statistical concepts to data; analysis of real-world problems.

Term: Spring
Day/Time: Monday, Wednesday, Friday 10:30am - 11:20am

STAT 361b / STAT 661b Data Analysis

Selected topics in statistics explored through analysis of data sets using the R statistical computing language. Topics include linear and nonlinear models, maximum likelihood, resampling methods, curve estimation, model selection, classification, and clustering. Weekly sessions in the Statistical Computing laboratory.

After STAT 242 and MATH 222 or 225, or equivalents.

Term: Spring
Day/Time: Monday & Wednesday,2:30pm - 3:45pm (tentative)

STAT 675 Topological Data Analysis

An introduction to a method of topological data analysis called persistent homology.  Persistent homology is a framework for extracting certain topological information (connected components, loops, voids, …) from data and can be used to estimate properties of the underlying structures.  Various theoretical, methodological, computational, and applied aspects of persistent homology will be discussed

Term: Fall
Day/Time: Monday 1:00pm - 3:45pm