Statistics Major (B.S.)
https://ceps.unh.edu/mathematics-statistics/program/bs/statistics
This program prepares students for employment and/or graduate study in a variety of fields and research specializations in which statistical analysis and its applications play a critical role. In addition to its degree programs, the department has an active interest in the actuarial profession. Those interested in actuarial science should seek the advice of departmental coordinator of the actuarial program, Professor Linyuan Li.
Graduation Requirements
In all courses used to satisfy the requirements for its major programs, the Department of Mathematics and Statistics requires that a student earn a grade of C- or better and have an overall grade-point average of at least 2.00 in these courses.
| Code | Title | Credits |
|---|---|---|
| Required MATH Courses | ||
| MATH 425 | Calculus I | 4 |
| MATH 426 | Calculus II | 4 |
| MATH 445 | Mathematics and Applications with MATLAB | 4 |
| or CS 410P | Introduction to Scientific Programming/Python | |
| or CS 410C | Introduction to Scientific Programming/C | |
| MATH 527 | Differential Equations with Linear Algebra 1 | 4 |
| MATH 528 | Multidimensional Calculus 1 | 4 |
| MATH 531 | Mathematical Proof | 4 |
| MATH 539 | Introduction to Statistical Analysis | 4 |
| MATH 645 | Linear Algebra for Applications 1 | 4 |
| MATH 739 | Applied Regression Analysis | 4 |
| MATH 755 | Probability with Applications | 4 |
| MATH 756 | Principles of Statistical Inference | 4 |
| TWO approved MATH electives, selected in consultation with the major advisor (at least one at the 700-level) | 8 | |
| Select THREE courses from the following: | 12 | |
| Statistical Computing | ||
| Advanced Statistical Modeling | ||
| Statistical Methods for Quality Improvement and Design | ||
| Design of Experiments I | ||
| Survival Analysis | ||
| Time Series Analysis | ||
| Design of Experiments II | ||
| Capstone - Select one course from the following: | 4 | |
| Senior Seminar | ||
| Senior Project | ||
| Senior Thesis | ||
| Total Credits | 68 | |
| First Year | ||
|---|---|---|
| Fall | Credits | |
| MATH 425 | Calculus I | 4 |
| Discovery Course | 4 | |
| Discovery Course | 4 | |
| Inquiry Course | 4 | |
| MATH 400 | Freshman Seminar | 1 |
| Credits | 17 | |
| Spring | ||
| MATH 426 | Calculus II | 4 |
| MATH 445 |
Mathematics and Applications with MATLAB or Introduction to Scientific Programming/C or Introduction to Scientific Programming/Python |
4 |
| ENGL 401 | First-Year Writing | 4 |
| Discovery Course | 4 | |
| Credits | 16 | |
| Second Year | ||
| Fall | ||
| MATH 528 | Multidimensional Calculus | 4 |
| MATH 531 | Mathematical Proof | 4 |
| Discovery Course | 4 | |
| Discovery Course | 4 | |
| Credits | 16 | |
| Spring | ||
| MATH 527 | Differential Equations with Linear Algebra | 4 |
| MATH 539 | Introduction to Statistical Analysis | 4 |
| Discovery Course | 4 | |
| Writing Intensive Course | 4 | |
| Credits | 16 | |
| Third Year | ||
| Fall | ||
| MATH 645 | Linear Algebra for Applications | 4 |
| MATH 739 | Applied Regression Analysis | 4 |
| 700-level MATH Elective Course | 4 | |
| Discovery Course | 4 | |
| Credits | 16 | |
| Spring | ||
| 700-level MATH Elective Course | 4 | |
| 700-level MATH Elective Course | 4 | |
| Elective Course | 4 | |
| Writing Intensive Course | 4 | |
| Credits | 16 | |
| Fourth Year | ||
| Fall | ||
| MATH 755 | Probability with Applications | 4 |
| MATH 797 |
Senior Seminar or Senior Project or Senior Thesis |
4 |
| 700-level MATH Elective Course | 4 | |
| Elective Course | 4 | |
| Credits | 16 | |
| Spring | ||
| MATH 756 | Principles of Statistical Inference | 4 |
| MATH Elective Course | 4 | |
| Elective Course | 4 | |
| Elective Course | 4 | |
| Credits | 16 | |
| Total Credits | 129 | |
- Communicate theoretical foundations and principles of intermediate-level statistics to diverse audiences.
- Design an appropriate method of data collection for a variety of practical applications.
- Perform analyses using the established tools of applied statistics, including production of appropriate software output and its interpretation.