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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
  • 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
ST310: Statistical Computing
ST461: Elements of Statistical Theory: Distributions
ST465: Experimental Research Methods

Additional 400-level MA/ST course from:

ST462: Elements of Statistical Theory: Inference
ST466: Experimental Design
ST471: Statistical Quality Control
ST472: Applied Multivariate Analysis
MA/ST485: Stochastic Processes
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: Programming in Mathematics
MA424: Complex Analysis
MA427: Numerical Analysis
MA428: Computational Mathematics
MA445: Advanced Linear Algebra
ST461: Elements of Statistical Theory: Distributions
MA481: Operations Research
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: Programming in Mathematics
MA421: Analysis I
MA427: Numerical Analysis
MA428: Computational Mathematics
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