Statistics (Ph.D.)
https://ceps.unh.edu/mathematics-statistics/program/phd/statistics
The Ph.D. in statistics is a flexible program of coursework and research that meshes the faculty's expertise with the students' interests. Current faculty expertise are in Design of Experiments, Nonparametric Function Estimation, Model Selection, Time Series Analysis, Spatial Statistics, Bayesian Statistics, Data Mining and Large Data. Doctoral dissertations range from theoretical to applied. Interdisciplinary research is encouraged. Ph.D. students frequently work as research assistants in interdisciplinary studies, and also engage in statistical consulting.
Admission Requirement
Applicants must have completed significant undergraduate coursework in mathematics and Statistics, including basic Statistics (for example, design of experiments), the standard Calculus sequence, and Linear Algebra.
Applying
Please visit the Graduate School website for detailed instructions about applying to the doctoral program.
Degree Requirements
Students are advanced to candidacy after meeting the following requirements:
| Code | Title | Credits |
|---|---|---|
| Required Courses | ||
| MATH 836 | Advanced Statistical Modeling | 3 |
| MATH 839 | Applied Regression Analysis | 3 |
| MATH 840 | Design of Experiments I | 3 |
| MATH 855 | Probability with Applications | 3 |
| MATH 856 | Principles of Statistical Inference | 3 |
| Advanced Coursework in Statistics | ||
| MATH 945 | Advanced Theory of Statistics I | 3 |
| MATH 946 | Advanced Theory of Statistics II | 3 |
| Select four courses from the following: | 12 | |
| Statistical Methods for Quality Improvement and Design | ||
| Data Mining and Predictive Analytics | ||
| Survival Analysis | ||
| Time Series Analysis | ||
| Design of Experiments II | ||
| Bayesian and Computational Statistics | ||
| Spatial Statistics | ||
| Research Topics in Statistics 1 | ||
| Minor Coursework | ||
| Select one of the following analysis courses: | 3 | |
| One-Dimensional Real Analysis | ||
| Analysis I | ||
| Select two courses in a focused minor area, selected in consultation with the program advisor. | 6 | |
| Total Credits | 42 | |
- 1
MATH 979 Research Topics in Statistics is a topics course and may be repeated barring duplication of topic.
Successful completion of written qualifying examinations in theory of statistics and in applied statistics.
Successful completion of a comprehensive exam in advanced theory of statistics.
Successful completion of a dissertation proposal defense in the major field of statistics.
Dissertation
Doctor of Philosophy in Statistics: A dissertation that includes original research in statistics.
- Demonstrate deep knowledge of the theoretical foundations of statistics at the advanced level.
- Conduct research that contributes to the development of statistical theory and methods.
- Demonstrate competency in a broad array of advanced statistical methodologies, including skill in statistical computing for analysis and simulation.
- Demonstrate familiarity with at least one scientific area of investigation that crucially depends on statistical methodology.