Rutgers University 3 credits Statistics - Data Science
The study of probabilistic and inferential tools is important for applications in data science. Topics covered: Probability distributions; decision theory, Bayesian inference, classification, prediction; law of large numbers, central limit theorem; point and interval estimation; multiple testing, false-discovery rates.
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