Upon completion of the program, students should:

1. Demonstrate knowledge of probability and the standard statistical distributions.
2. Demonstrate knowledge of fixed-sample and large-sample statistical properties of point and interval estimators.
3. Demonstrate knowledge of the properties of parametric, semi-parametric and nonparametric testing procedures.
4. Demonstrate the ability to perform complex data management and analysis.
5. Demonstrate the ability to apply linear, nonlinear and generalized linear models.
6. Demonstrate understanding of how to design experiments and surveys for efficiency.
7. Demonstrate knowledge of classical and repeated measures multivariate methods and computational techniques.

At the end of the program, students will take a comprehensive final examination that reflects the curriculum covered in the program. The exam will be given orally via a video conference with the student’s Advisory Committee.