The Ph.D. in Statistics at UNH provides you with a deep understanding of theoretical and computational foundations in statistical methodology to prepare you for a career in academia, research, or industry. You'll engage in innovative research alongside faculty at a top-tier research university in areas like Bayesian statistics, machine learning, and environmental statistics. Our flexible, interdisciplinary program offers numerous collaboration opportunities across campus, making it ideal for students looking to become leaders in data-driven science and analytics.
Why pursue a Ph.D. in statistics at UNH?
In our statistics Ph.D. program, you’ll develop deep knowledge of the theoretical and computational foundations of statistical methodology that drives data analysis and predictive analytics. You’ll work closely with faculty to conduct original research in a chosen area of interest. Our departmental specializations include Bayesian statistics, causal inference, data mining and large data, epigenomic statistics, design of experiments for innovation, environmental statistics, high-dimensional data, machine learning, network analysis, nonparametric function estimation, spatial statistics, and time series analysis. We offer a flexible program of coursework and research that encourages interdisciplinary study and is designed to align your interests with the expertise of our faculty.
Program Highlights
Being a major research university, UNH is a hotbed of data-driven science exploration. There are numerous opportunities for our statistics Ph.D. students in interdisciplinary and data-driven research and collaborations on campus. Combined with the foundational training of the program, our graduates are positioned to become leaders in statistical development, especially in industry. Our graduates work in academia as researchers, or in interdisciplinary studies in research centers and in the private and public sectors,and also engage in statistical consulting, outreach and leadership.
Potential career areas
- Actuarial science
- Artificial Intelligence
- Data analysis
- Government and economic statistics
- Information technology
- Service industries
- Startup companies
- Teaching and research
Curriculum & Requirements
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 | |
MATH 837 | Statistical Methods for Quality Improvement and Design | |
MATH 838 | Data Mining and Predictive Analytics | |
MATH #841 | Survival Analysis | |
MATH 843 | Time Series Analysis | |
MATH 844 | Design of Experiments II | |
MATH #941 | Bayesian and Computational Statistics | |
MATH #944 | Spatial Statistics | |
MATH 979 | Research Topics in Statistics 1 | |
| Minor Coursework | ||
| Select one of the following analysis courses: | 3 | |
MATH 867 | One-Dimensional Real Analysis | |
MATH 953 | 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.
Deadlines
Applications must be completed by the following deadlines in order to be reviewed for admission:
- Fall: Feb. 15 (for funding); April 1 (recommended US; final international); July 1 (final)
- Spring: Dec. 1, Nov. 1 for international students
- Summer: N/A
- Special: N/A
Application fee: $65
Campus: Durham
New England Regional: No
Accelerated Masters Eligible: No
New Hampshire Residents
Students claiming in-state residency must also submit a Proof of Residence Form. This form is not required to complete your application, but you will need to submit it after you are offered admission, or you will not be able to register for classes.
Transcripts
If you attended UNH or Granite State College (GSC) after September 1, 1991, and have indicated so on your online application, we will retrieve your transcript internally; this includes UNH-Durham, UNH-Manchester, UNH Non-Degree work and GSC.
If you did not attend UNH, or attended prior to September 1, 1991, then you must upload a copy (PDF) of your transcript in the application form. International transcripts must be translated into English.
If admitted, you must then request an official transcript be sent directly to our office from the Registrar's Office of each college/university attended. We accept transcripts both electronically and in hard copy:
- Electronic Transcripts: Please have your institution send the transcript directly to grad.school@unh.edu. Please note that we can only accept copies sent directly from the institution.
- Paper Transcripts: Please send hard copies of transcripts to: UNH Graduate School, Thompson Hall- 105 Main Street, Durham, NH 03824. You may request transcripts be sent to us directly from the institution or you may send them yourself as long as they remain sealed in the original university envelope.
Transcripts from all previous post-secondary institutions must be submitted and applicants must disclose any previous academic or disciplinary sanctions that resulted in their temporary or permanent separation from a previous post-secondary institution. If it is found that previous academic or disciplinary separations were not disclosed, applicants may face denial and admitted students may face dismissal from their academic program.
Letters of recommendation: 3 required
Recommendation letters submitted by relatives or friends, as well as letters older than one year, will not be accepted.
Personal Statement/Essay Questions
Prepare a brief but careful statement regarding:
- Reasons you wish to do graduate work in this field, including your immediate and long-range objectives.
- Your specific research or professional interest and experiences in this field.
Important Notes
All applicants are encouraged to contact programs directly to discuss program-specific application questions.
International Applicants
Prospective international students are required to submit TOEFL, IELTS, or equivalent examination scores. English Language Exams may be waived if English is your first language. If you wish to request a waiver, then please visit our Test Scores webpage for more information.
