Data Analysis for the Natural Sciences I: Fundamentals

1 Course Unit

This is a course on the fundamentals of data analysis and statistical inference for the natural sciences. Topics include probability distributions, linear and non-linear regression, Monte Carlo methods, frequentist and Bayesian data analysis, parameter and error estimation, Fourier analysis, power spectra, and signal and image analysis techniques. Students will obtain both the theoretical background in data analysis and also get hands-on experience analyzing real scientific data. Prerequisite: Prior programming experience. Fall, even numbered years only Prerequisite: MATH 2400 AND PHYS 2260 1 Course Unit