Intro. Data Reduction Applica. ((3 Credits))

Catalog description

This is a one semester course in which the theory and application of data reduction and error analysis are introduced. Topics include the binomial distribution, the Gaussian and Poisson probability density functions, estimation of moments, and propagation of uncertainty. Data modeling, including least-squares fitting of linear and polynomial functions, is presented. Using computer softwar, students are expected to apply the concepts of data reduction error analysis to real data sets derived from the physical sciences.