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18.6501 Fundamentals of Statistics
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Graduate (Fall, Spring)
(Subject meets with 18.650[J], IDS.014[J])
Prereq: 6.3700 or 18.600
Units: 4-0-8
Lecture: MWF1 (2-190) Recitation: R1 (4-270) or R3 (4-153) +final
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A rapid introduction to the theoretical foundations of statistical methods that are useful in many applications. Covers a broad range of topics in a short amount of time with the goal of providing a rigorous and cohesive understanding of the modern statistical landscape. Mathematical language is used for intuition and basic derivations but not proofs. Main topics include: parametric estimation, confidence intervals, hypothesis testing, Bayesian inference, and linear and logistic regression. Additional topics may include: causal inference, nonparametric estimation, and classification. Students in Course 18 must register for the undergraduate version, 18.650.
Fall: P. Rigollet
Spring: A. Katsevich
No textbook information available