Spring 2007 
M, W, 2:10-3:40 
Observatory, A-101 
EXAM GROUP 16: 

How to design experiments and get the most information from noisy, incomplete, flawed, and biased data sets. Basics of probability theory; Bernouli trials; Bayes theorem; random variables; distributions; functions of random variables; moments and characteristic functions; Fourier transform analysis; Stochastic processes; estimation of power spectra. Digital data processing: sampling theorem, filtering; fast Fourier transform; spectrum of quantized data sets. Weighted least mean squares analysis and nonlinear parameter estimation. Noise processes in periodic phenomena. Image processing and restoration techniques.

Back to Harvard University Department of Astronomy Academics.
Back to Harvard University Department of Astronomy Courses.