DSCI 632. Statistics for Data Science. 4 Credits.
Probability for classical and Bayesian inference. This course will cover statistical uncertainty as applied to hypothesis testing, experimental design, and parameter estimation. Students will gain exposure to common probability distributions in the Sciences, and their application in statistical models, validation of model assumptions, and hypothesis formulation and testing. Basic maximum likelihood methods using linear models (regression, ANOVA) will be covered. Will include an introduction to Bayesian statistics.