Statistics 4+1 (B.S. + M.S.)

About our program

Our 4+1 program allows students to complete both their Bachelors and Masters in Statistics at UD in only five years.

Statistics is a high-demand field that provides skills for students in data analysis, statistical computing and quantitative reasoning. Statisticians are employed everywhere from finance and pharmaceuticals to gaming and agriculture. According to U.S. News & World Report, statistician is a Top Ten Best Business Job. The 4+1 gives students a jumpstart on the job market with advanced skills and expertise. 

Why our 4+1?

The 4+1 statistics program is an opportunity to earn two degrees, have the possibility to gain valuable internship experience, and be ahead of the competition on the job market. Every industry has increasing amounts of data and needs people who know how to meaningfully analyze that data to help make better decisions. You will gain a set of tools across an array of statistical approaches including regression analysis, time series analysis, survival analysis, in addition to experience with Python, SAS, R and other statistical software packages. With these skills, UD prepares graduates for job market success in nearly any field.


Throughout your time in the UD 4+1 Statistics program, we provide opportunities to apply your newly acquired skills to real-world problems and applications. Assist researchers across campus in our StatLab. Analyze sports analytics through our partnership with UD Athletics.  Take advantage of our department’s close relationships with local companies, including Barclays Bank, J.P. Morgan Chase, FMC and Sallie Mae, where we place students to gain meaningful internship experience. Given UD’s friendly faculty-to-student ratio, build a close relationship with your faculty mentor, who will prepare you for your desired career. 

Course highlights

This course provides you with an introduction to both R and SAS, two statistical computing packages you are likely to use in industry upon graduation. Our faculty do not simply teach the basics of these languages, but specifically how to use them for the statistical analysis you’ve studied throughout the program.
This course teaches a range of regression techniques from simple linear regression to principal component analysis and ridge regression. Our faculty cover the basics of experimental design and design models. This material is critical to much statistical analysis of large and small datasets.
Students learn the fundamental principles of experimental design, including randomized designs, sources of error, factorial designs, response surfaces and other related topics. When analysts have the opportunity to purposefully design data collection rather than just analyze data that is brought to them, experimental design is a critical skillset. As more organizations can control their data inputs, that data will bring higher value.

Related student organizations

Statistics 4+1 (B.S. + M.S.) | Undergraduate Programs | University of Delaware
Statistics 4+1 (B.S. + M.S.) | Undergraduate Programs | University of Delaware
Statistics 4+1 (B.S. + M.S.) | Undergraduate Programs | University of Delaware
Contact us

Noël Hart Wolhar
Associate Director, CANR Undergraduate Recruitment