Chris K. Caldwell

Descriptive measures, elementary probability, sampling, random variables. Discrete probability distributions, normal probability distributions, and introduction to inference theory. Descriptive measures, elementary probability, sampling, random variables. Discrete probability distributions, normal probability distributions, and introduction to inference theory.

This course will introduce mathematics and statistics majors to formal mathematical and statistical written and verbal communication including, but not limited to, preparing presentations and written papers in the mathematical and statistical sciences. The course will also provide majors with assistance in preparing resumes and various requirements, procedures, and guidelines of graduate school applications.

The integers: well-ordering, different bases, divisibility, primes, and factoring. The fundamental theorem of arithmetic and the division algorithm. Diophantine equations and applications of congruences. Pseudo-random numbers, pseudoprimes, and cryptography.

Functions and their graphs (including polynomial, rational, exponential, and logarithmic), exponents, roots, radicals, rational expressions, factoring polynomials, zeroes of polynomials, solutions of linear and nonlinear equations and inequalities, systems of equations and inequalities, matrices and determinants, inverse functions. Three hours of lecture and two hours of lab.

Limits and continuity. Derivatives and integrals of polynomial, exponential, logarithmic, trigonometric, and hyperbolic functions. Techniques of integration, conics, parametric and polar equations, indeterminate forms, and improper integrals. Infinite series, including Taylor's series. Must be taken in sequence. , including Taylor's series. Must be taken in sequence.

University of California, Berkeley

In 1984 I received my Ph.D. in algebraic number theory at the University of California at Berkeley, working under the topologist P. Emory Thomas.