# Mathematics or Statistics/Biology Interdisciplinary Major

### Mathematics and Statistics Courses required:

- MA 251, MA 252, MA 351: Calculus I-III
- ST 265 Biostatistics (or ST210 Introduction to Statistics)
- MA 301 Linear Algebra
- ST 365 SAS Laboratory (for the Statistics track) - this is a 1-credit computer course.
- MA 395 Discrete Methods or MA 304 Ordinary Differential Equations (depending on track selected)
- Four 400 level Mathematical Sciences courses depending on track selected (see below)

### Biology Courses required:

- BL 118, 119 Cellular and Molecular Biology and Lab
- BL 121, 126 Organismal Biology and Lab
- BL 201, 202 Ecology, Evolution, & Biodiversity and Lab
- Five upper level (200 level or higher) Biology courses.

*Note:*

BL122 may be substituted for BL 201, 202. BL 123 may be substituted for BL118, 119. (Please consult the Biology dept. chair.)

### Other Requirements:

- CS 151: Computer Science through Programming

*Notes:*

CS212: Object-Oriented Data Structures is strongly encouraged as an elective.

CH 101: General Chemistry I, is strongly encouraged as an elective.

### Suggested Tracks:

## Statistics Track

The discipline of biostatistics applies statistical theory and methodology to the biological sciences. Based in the mathematical sciences, biostatistics is concerned with developing an empirical basis for understanding biological mechanisms and for medical and health policy decisions that profoundly affect our lives. Examples include:

- Designing and analyzing studies to determine if new drugs and medical devices are safe and effective (at a pharmaceutical company, medical research center, or the Food and Drug Administration)
- Designing studies for and analyzing data from agricultural experiments to increase productivity and yield (at an agricultural college or agribusiness corporation)
- The search for improved medical treatments rests on careful experiments that compare promising new treatments with the current state of the art. Statisticians work with medical teams to design the experiments and to analyze the complex data they produce.
- Studies of the environment require data on the abundance and location of plants and animals, on the spread of pollution form its sources, and on the possible effects of changes in human activities. The data are often incomplete or uncertain, but statisticians can help uncover their meaning.
## Required Courses:

MA395 (Discrete Methods)

ST365 (SAS Laboratory)

ST461 (Elements of Statistical Theory: Distributions)

ST465 (Experimental Research Methods)## Additional 400-level MA courses from:

ST462 (Elements of Statistical Theory: Inference)

ST466 (Experimental Design)

MA445 (Advanced Linear Algebra)

MA/ST485 (Stochastic Processes)

ST472 Applied Multivariate Analysis

ST491 (Statistical Special Topics - when applicable)## Differential Equations/Modeling Track

Mathematical models are important tools in basic scientific research in many areas of biology, including physiology, ecology, evolution, toxicology, immunology, natural resource management, and conservation biology. The result obtained from analysis and simulation of system models are used to test and extend biological theory, and to suggest new hypotheses or experiments. Models are also widely used to synthesize available information and provide quantitative answers to practical questions. What measures can be used to reverse the decline in sea turtle populations, and how soon can we tell if they are working? How can laboratory experiments on chemical carcinogenicity be scaled up to set safe exposure limits on humans? For questions like these, where it is desirable to predict the outcome accurately before action is taken, quantitative modeling is essential. This track emphasizes the use of mathematical methods such as differential equations, dynamical systems, and other analytic techniques.

## Required Courses:

MA304 (Ordinary Differential Equations)

MA421 (Analysis I)## Additional 400-level MA courses from:

MA302 (MATLAB)

MA424 (Complex Analysis)

MA425 (Differential Equations)

MA427 (Numerical Analysis)

MA445 (Advanced Linear Algebra)

ST461 (Elements of Statistical Theory: Distributions)

MA481 (Operations Research)

MA/ST485 (Stochastic Processes)

MA490 (Mathematics Special Topics - when applicable)## Discrete/Algorithmic Track

Discrete mathematics and algorithmics play a fundamental role in modern computational and molecular biology. Problems concerning areas such as genetic mappings, DNA structure and molecular evolution often involve interesting combinatorial and algorithmic models. For example, comparison of extensive molecular sequences and extraction of information from them is a central problem in modern computational biology. This track emphasizes the study of algorithms, and combinatorial and graph theoretic structures.

## Required Courses:

MA395 (Discrete Methods)

MA441 (Ring Theory) and/or ST461 (Elements of Statistical Theory: Distributions)## Additional 400-level MA courses from:

MA302 (MATLAB)

MA421 (Analysis I)

MA431 (Geometry)

MA442 (Group Theory)

MA445 (Advanced Linear Algebra)

MA447 (Number Theory)

MA481 (Operations Research)

MA/ST485 (Stochastic Processes)

MA490 (Mathematics Special Topics - when applicable)