Undergraduate Statistics General Info

Harvard Undergraduate Statistics Courses Family Tree

Announcement: a new track in Data Science now exists.  More details are forthcoming...

Statistics provides quantitative methods for analyzing data, making rational decisions under uncertainty, designing experiments, and modeling randomness and variability in the world. Statistics has a theoretical core surrounded by a vast number of domains of application in fields such as anthropology, astronomy, biology, business, chemistry, computer science, economics, education, engineering, environmental sciences, epidemiology, finance, government, history, law, linguistics, medicine, physics, psychology, sociology, and many others. A recent New York Times article pointed out the increasing demand for statisticians in an article with the headline: "For Today's Graduate, Just One Word: Statistics."

A basic goal of the Statistics concentration is to help students acquire the conceptual, computational, and mathematical tools for quantifying uncertainty and making sense of complex data arising from many applications. Recent alumni are applying their knowledge in a very wide variety of companies and graduate programs, including tech companies such as Google and IBM, investment banks such as Goldman Sachs and Credit Suisse, hedge funds such as D.E. Shaw and AlphaSimplex, medical schools, and Statistics PhD programs.

Statistics can be applied almost anywhere; to reflect this, the concentration allows many opportunities to learn about how statistics is used in other fields; by definition, statistics should not be studied in isolation. The concentration requirements can be fulfilled via any of four tracks: a General track in core statistical principles and methods, a track in Data Science, a track in Quantitative Finance, and a track in Bioinformatics and Computational Biology (BCB). These tracks all lead to a degree in Statistics.

The general track is the most flexible track, providing a foundation in principles and techniques for statistical theory, methods, and applications. This foundation can be applied to a myriad of fields. As John Tukey said, "The best thing about being a statistician is that you get to play in everybody else's backyard."

The data science track explores the interface of statistics and computer science. Courses involve a mixture of these fields, with applications to areas such as prediction, recommendation systems, and analysis of massive data sets.

The finance track gives strong preparation for many careers in finance and actuarial work. Specific topics addressed include statistical inference for stochastic models that arise in financial/insurance modeling as well as computational techniques that have become standard in pricing, hedging and risk assessment of complex financial/insurance instruments.

The BCB track mixes together biology, statistics, and computation, giving models and tools for studying biological data such as gene and protein sequences. This is motivated in part by the recent explosion of size and complexity of data in the biological sciences, which has required the development of new statistical methods and models, such as models for gene and protein motifs search, phylogenetic reconstruction, and gene expression analysis.

The Statistics Department also offers a secondary field, and welcomes joint concentrations with departments that allow this (for students who wish to write a senior thesis interweaving statistics and another field).

For further information about the concentration, you can explore this website (see tabs at left).  If you have questions, please consult with the Student Programs Administrator, Kathleen Cloutier, Science Center 400E (617-496-1402, cloutier@fas.harvard.edu) and the Co-Directors of Undergraduate Studies, Professor Joseph Blitzstein, Science Center 714 (617-496-2985, blitzstein@stat.harvard.edu) and Professor Michael Parzen, Science Center 300B (617-495-8711, mparzen@stat.harvard.edu) or the Assistant Director of Undergraduate Studies, Professor Kevin Rader, Science Center 614 (617-495-5204, krader@fas.harvard.edu).