Computational and Applied Mathematics and Statistics, Applied Statistics Track (BS in Computational and Applied Mathematics and Statistics)
CAMS Program
The CAMS (Computational and Applied Mathematics and Statistics) program is by nature inter-disciplinary. In CAMS, applications are the primary driver of the research agenda for scholarly activity. The CAMS program supports a collaborative, multi-disciplinary, and integrative approach to teaching and research in applied and computational mathematics, operations research, mathematical biology and statistics. Course work and research experiences in CAMS provide a strong base in both the knowledge and practical skills necessary to make important contributions to mathematics, industry and the sciences. There are two tracks within the CAMS program: Mathematical Biology and Applied Statistics.
Mathematical Biology aims at modeling natural, biological processes using mathematical techniques and tools. It has both practical and theoretical applications in biological research. Applying mathematics to biology has a long history, but only relatively recently has there been an explosion of interest in the field. Some reasons for this include: the explosion of data-rich information sets, due to the genomics revolution, which are difficult to understand without the use of analytical tools; recent development of mathematical tools such as chaos theory to help understand complex, nonlinear mechanisms in biology; an increase in computing power which enables calculations and simulations to be performed that were not previously possible; and an increasing interest in computer experimentation due to the complications involved in human and animal research.
The Applied Statistics Track provides a major option for undergraduates with an interest in statistics, “big data”, and actuarial science. As humans have developed cheaper and smaller sensors, web cameras and other data collection devices, the amount of data available to be analyzed and understood has exploded. Statistics is the mathematical science that pertains to the collection, analysis, interpretation, explanation, and presentation of data. Because of its empirical roots and its focus on applications, statistics is typically considered a distinct mathematical science rather than a branch of mathematics.
The Applied Statistics major gives students a rigorous training in the highly-interdisciplinary modern practice of statistics. The major draws upon a foundation of topics in mathematics and computer science to build a core specialization in applied and theoretical statistics and enriches this statistical knowledge with cross-disciplinary electives. Possible areas of focus within the major include: econometrics, data science, general applied statistics, and actuarial science.
Course Requirements
Major Writing Requirement
The upper-division writing requirement is satisfied by one of the following ways:
- Completion of ECON 308 Econometrics or ECON 380 Experimental Economics or MATH 352 Statistical Data Analysis or MATH 455 Statistical Learning or MATH 459 Topics in Statistics with a grade of C- or better, or
- Completion of CAMS 495 Honors and CAMS 496 Honors , which requires the writing of an Honors thesis.
Major Requirements
| Code | Title | Hours |
|---|---|---|
| MATH 111 | Calculus I | 4 |
| or MATH 131 | Calculus I for Life Sciences | |
| MATH 112 | Calculus II | 4 |
| or MATH 132 | Calculus II for Life Sciences | |
| MATH 214 | Foundations of Math | 3 |
| Major Computing Requirement | ||
| CSCI 141 | Modern Programming Fundamentals | 4 |
| CSCI 241 | Data Structures | 3 |
| or MATH 240 | Programming for the Mathematical Sciences | |
| Major Mathematics Requirement | ||
| MATH 109 | Linear Algebra | 3 |
| MATH 109L | Computational Linear Algebra Lab | 1 |
| and | ||
| MATH 212 | Introduction to Multivariable Calculus | 3-4 |
| or MATH 213 | Multivariable Calculus for Science and Mathematics | |
| Major Statistics Requirement | ||
| MATH 451 | Probability | 3 |
| MATH 452 | Mathematical Statistics | 3 |
| Select one of the following: 1 | 3 | |
| Fundamentals of Artificial Intelligence/Machine Learning | ||
| Topics in Computational Operations Research 2 | ||
| Time Series Econometrics | ||
| Statistical Data Analysis | ||
| Statistical Learning | ||
| Electives | ||
| Select 24 elective credits onsisting of: 9-15 credits of Statistics and Math electives; and 9-15 credits of cross-disciplinary electives from the following: | 24 | |
| Statistics and Mathematics Electives: | ||
Statistics Courses: | ||
| Probability and Statistics for Scientists 3 | ||
| Statistical Data Analysis | ||
| Advanced Statistical Data Analysis | ||
| Operations Research: Stochastic Models | ||
| Statistical Learning with Survival Data | ||
| Statistical Learning | ||
| Mathematics of Financial Economics | ||
Mathematics Courses: | ||
| Theory of Vector Spaces | ||
or MATH 408 | Matrix Analysis | |
| Elementary Analysis | ||
| Operations Research: Deterministic Models | ||
| Topics in Mathematics (Subject to approval of CAMS Applied Statistics Track Director) | ||
| Introduction to Numerical Analysis I | ||
| Cross-disciplinary Electives: | ||
Computer Science Courses: | ||
| Software Development | ||
| Algorithms | ||
| Fundamentals of Artificial Intelligence/Machine Learning | ||
| Special Topics in Computer Science (depending on material.) | ||
| Reliability | ||
| Analysis of Simulation Models 4 | ||
| Topics in Computational Operations Research (Linear Regression) 4 | ||
| Topics in Computational Operations Research (Design of Experiments) 4 | ||
| Topics in Computational Operations Research (Topics in Computational Operations Research) 4 | ||
Economics Courses: | ||
| Econometrics | ||
| Experimental Economics | ||
| Topics in Economics (subject to approval of CAMS Applied Statistics Track Director) | ||
| Cross Section Econometrics | ||
| Time Series Econometrics | ||
| Bayesian Econometrics | ||
| Total Hours | 58-59 | |
- 1
Permission to take CSCI 688 can be found here.
- 2
Note: MATH 351 Probability and Statistics for Scientists cannot not be taken concurrently with MATH 451 Probability, nor after receiving credit for MATH 451 Probability. CAMS majors are encouraged to proceed directly to MATH 451 Probability and consult with a CAMS director if they have any questions.
- 3
Graduate courses may be taken by completing this form
Note
Credit for CAMS 495 Honors-CAMS 496 Honors Honors, with faculty advisor approved by the Applied Statistics Track Director, may substitute for any two elective courses, as long as the two courses are not in the same category. In addition, with advisor approval, students may replace one elective course with one or more independent study or research credits, which must total at least 3 credits.