## Christopher Chong

Assistant Professor of Mathematics

**Current teaching schedule available on the public course finder.**

### Contact Information

cchong@bowdoin.edu

207-725-3577

Mathematics

Searles Science Building - 125

### Teaching this semester

### MATH 1300. Biostatistics

An introduction to the statistical methods used in the life sciences. Emphasizes conceptual understanding and includes topics from exploratory data analysis, the planning and design of experiments, probability, and statistical inference. One and two sample t-procedures and their non-parametric analogs, one-way ANOVA, simple linear regression, goodness of fit tests, and the chi-square test for independence are discussed. An average of four to five hours of class meetings and computer laboratory sessions per week. Not open to students who have credit for Mathematics 1200 or have credit or are concurrently enrolled in Mathematics 1400.

### MATH 2208. Ordinary Differential Equations

A study of some of the ordinary differential equations that model a variety of systems in the physical, natural and social sciences. Classical methods for solving differential equations with an emphasis on modern, qualitative techniques for studying the behavior of solutions to differential equations. Applications to the analysis of a broad set of topics, including population dynamics, oscillators and economic markets. Computer software is used as an important tool, but no prior programming background is assumed.

### Teaching next semester

### MATH 2208. Ordinary Differential Equations

A study of some of the ordinary differential equations that model a variety of systems in the physical, natural and social sciences. Classical methods for solving differential equations with an emphasis on modern, qualitative techniques for studying the behavior of solutions to differential equations. Applications to the analysis of a broad set of topics, including population dynamics, oscillators and economic markets. Computer software is used as an important tool, but no prior programming background is assumed.

### MATH 3209. Partial Differential Equations

A study of some of the partial differential equations that model a variety of systems in the natural and social sciences. Classical methods for solving partial differential equations are covered, as well as modern, numerical techniques for approximating solutions. Applications to the analysis of a broad set of topics, including air quality, traffic flow, and imaging. Computer software is used as an important tool.

### Education

- B.S. (New Hampshire)
- M.S. (San Diego State University)
- Ph.D. (Karlsruhe Institute of Technology-Germany)