Applied Calculus: Data Analysis

Catalog description

The three topic pillars of this course are functions, derivatives, and integrals. We will work on broadening and deepening our understanding of functions as tools of mathematics and as models. We will focus on a derivative as defined by its role in the local approximation of a curve and use derivatives in optimization. We will focus on integrals as a way to compute probabilities and will explore the connection between the probability density function (pdf) and cumulative distribution function (cdf) for a continuous random variable. We will fit models to data visually, by maximizing log likelihood functions, and by using a method of moments. We will rely on software (R and Mathematica) to help us with our calculations in this course.