Welcome to the Cornell University Department of Statistics and Data Science (DSDS) website. Statistics is the science of learning from data, and of measuring, controlling, and communicating uncertainty. Statisticians develop objective models and methods and apply these for data analysis in a wide variety of scientific, social, and business endeavors. Statistical inference and probabilistic modeling are central to all of the pure and applied sciences today. Statistical thinking and quantitative reasoning has become pervasive in culture, economy, law, government, and sciences, dramatically changing the way people view the world.
The Department of Statistics and Data Science’s academic and research programs take advantage of Cornell University's extensive resources, drawing from many colleges and research groups. Our department itself is a multi-college partnership among three Cornell colleges – Computing and Information Science, the College of Agriculture and Life Sciences and the Industrial and Labor Relations (ILR) School. Specializations in our department include statistical science, social statistics, and biometry and range from mathematical statistics, computational statistics, and machine learning to the development of statistical methods for astrophysics, ecology, economics, epidemiology, financial modeling, genomics, high dimensional data, neurobiology, legal studies, medicine, public health and risk management.
If you take a look around our website, you'll learn about the exceptional faculty and students in our department, and the enthusiasm we have about the field of statistics. You'll also find detailed information about faculty, staff and students (former and present), the curriculum, courses offered, and faculty research projects. DSDS hosts weekly seminars and colloquia - see our Events section for more details – and also includes a consulting unit, Cornell Statistical Consulting Unit.
Statistics and Data Science faculty members and staff are committed to excellent training and instruction at the undergraduate, MPS and PhD levels. We encourage potential students to obtain more information about statistics as a profession, and our department as a place to learn it. Prospective students will find explicit guidelines, program descriptions and forms to learn about and facilitate the application for admission to our undergraduate and graduate programs.
Please don’t hesitate to contact us if you are interested in our programs or research.
Martin T. Wells Chair, Department of Statistics and Data Science