Astrostatistics

3 credits · Undergraduate

Astrophysical data analysis through cutting-edge data science, statistics, and artificial intelligence techniques. Probability theory; comparison of frequentist and Bayesian inference. Strategies for data exploration, visualization, density estimation, and classification. Standard approaches to regression, parameter estimation, and model selection (e.g. with Markov chain Monte Carlo). Time-series analysis and deep-learning techniques. Python, Jupyter notebooks, Github, and version control for computational workflow. Prerequisite: ASTR 3000. [3] (MNS)