18.650 Fundamentals of Statistics

Catalog description:
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.

Also see the math department’s subject overview for courses on probability and statistics.

Resources:

• Spring 2018 in-class scribe lecture notes
• Fall 2016 OCW (homework, lecture videos, lecture slides)
• Crowdsourced student work
  • homework solutions for OCW’s 2016 version
• EdX version
• Fall 2015 (18.443) OCW (homework, solutions, lecture notes)
• Fall 2006 (18.443) OCW (homework, exams, lecture notes)