Data Science vs. Statistics: Curricula, Joint Degrees and Careers

Statistics is one of the foundations of data science, and some statistics departments now carry data science in their name; Carnegie Mellon's and Northwestern's are examples. That makes the line between the two degrees harder to see than the line between data science and business. The differences that remain are mostly about emphasis: how much probability theory and inference you study, and how much programming, computing and data management. This guide covers how the curricula compare, how joint "Statistics and Data Science" degrees work, and what the Bureau of Labor Statistics reports for both occupations.

How the fields are defined

The federal Classification of Instructional Programs (CIP), maintained by the National Center for Education Statistics, describes them this way:

• Statistics, General (27.0501) "focuses on the relationships between groups of measurements, and similarities and differences, using probability theory and techniques derived from it." Listed instruction includes probability theory, regression analysis, stochastic processes, the Monte Carlo method, Bayesian and non-parametric statistics, and sampling theory.
• Data Science, General (30.7001) focuses on the analysis of large-scale data from the perspectives of applied statistics, computer science, data storage, data representation, data modeling and mathematics, with instruction in algorithms, programming, data management, data mining and statistics.

Statistics is defined by its methods and theory. Data science includes statistics but adds computing and data handling as core subjects.

How the curricula compare

Course lists show the difference more clearly than definitions. When you compare a statistics program with a data science program, look at:

• Theory. Does the program require probability and mathematical statistics, or a lighter applied statistics sequence? Are calculus and linear algebra prerequisites?
• Computing. How many required courses are programming, databases or large-scale computing?
• Machine learning. Is it a required course, and is it taught alongside statistical theory or alongside software and systems topics?
• Study design. Sampling theory appears in the federal definition of statistics, and BLS describes statisticians designing surveys and experiments and choosing sample size. Check whether a data science program covers these topics or leaves them as electives.

The University of Washington's catalog shows the difference inside one major. Its Statistics BS has a shared core in statistical foundations, modeling and applied data analysis, and a Data Science option that the catalog says "emphasizes computation and data management."

Joint "Statistics and Data Science" degrees

Many universities award one degree that names both fields. These are joint degrees, not double majors.

• Carnegie Mellon University offers a BS in Statistics and Data Science through its Department of Statistics and Data Science. The catalog lists 175 to 193 units for the major within a 360-unit degree, including a statistical computing requirement and a 36-unit self-defined concentration area. It notes that R is used throughout the statistics curriculum and requires all majors to gain basic competency in Python.
• Northwestern University offers an MS in Statistics and Data Science. Its stated mission is to provide "comprehensive training in advanced theory and methodology in statistics and data science," and it says the program prepares students for careers as a statistician or data scientist and for doctoral study.
• Southern Methodist University offers an MS in Data Science and Applied Statistics that, according to the department, combines statistical theory and methods with statistical computing, database management and predictive methods.

Related titles exist as well. Texas A&M's Department of Statistics awards an MS in Statistical Data Science with a thesis option (at least 31 credit hours) and a non-thesis option (at least 32).

Statistics degrees with a data science option

Some statistics degrees keep the statistics name and add an official data science option. The University of Wisconsin-Madison describes its MS in Statistics with a Statistics and Data Science named option as "a named option (formally documented sub-major) professional program in the Statistics MS." The guide lists a minimum of 30 credits and says the GRE is not required. The University of Washington's Statistics BS with its Data Science option is an undergraduate example.

In these programs, the awarded degree is statistics. In our directory (October 2026), 50 of 217 programs are joint degrees and 23 are concentrations or options within related degrees, including statistics.

Careers: statisticians and data scientists

BLS publishes separate profiles for the two occupations.

BLS describes statisticians' work as including designing surveys, experiments and opinion polls, determining sample type and size, and analyzing data with statistical software. It also notes that mathematicians and statisticians may help data scientists develop statistical models. For data scientists, BLS lists duties such as creating, validating and testing algorithms and models and presenting findings with data visualization, and it names mathematics, statistics, computer science, business and engineering as common fields of degree.

These figures describe national occupations, not graduates of any program. Individual outcomes vary and are not program-specific.

Which degree fits

A statistics degree or a statistics-led joint degree may suit you if you want depth in probability, inference and study design, or you are considering doctoral study in statistics or biostatistics. A data science degree may suit you if you want more of your coursework in programming, data management and machine learning systems. Joint degrees aim to cover both, so compare their required courses with care.

If you are considering doctoral study, browse PhD programs. If computing is the other half of your decision, see Data Science vs. Computer Science.