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Course18.650 / 18.650122 lectures28 h 1 min

Statistics for Applications

Prof. Philippe Rigollet · Massachusetts Institute of Technology

Start with lecture 1 At MIT OpenCourseWare

About

This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathematics in the research and development of efficient statistical methods.

Lectures

Lecture Videos

  1. Lecture 1: Introduction to Statistics 1 h 19 min · Video
  2. Lecture 2: Introduction to Statistics (cont.) 1 h 18 min · Video
  3. Lecture 3: Parametric Inference 1 h 23 min · Video
  4. Lecture 4: Parametric Inference (cont.) and Maximum Likelihood Estimation 1 h 18 min · Video
  5. Lecture 5: Maximum Likelihood Estimation (cont.) 1 h 17 min · Video
  6. Lecture 6: Maximum Likelihood Estimation (cont.) and the Method of Moments 1 h 20 min · Video
  7. Lecture 7: Parametric Hypothesis Testing 1 h 19 min · Video
  8. Lecture 8: Parametric Hypothesis Testing (cont.) 1 h 19 min · Video
  9. Lecture 9: Parametric Hypothesis Testing (cont.) 1 h 22 min · Video
  10. Lecture 11: Parametric Hypothesis Testing (cont.) and Testing Goodness of Fit 1 h 23 min · Video
  11. Lecture 12: Testing Goodness of Fit (cont.) 1 h 22 min · Video
  12. Lecture 13: Regression 1 h 17 min · Video
  13. Lecture 14: Regression (cont.) 1 h 14 min · Video
  14. Lecture 15: Regression (cont.) 1 h 16 min · Video
  15. Lecture 17: Bayesian Statistics 1 h 19 min · Video
  16. Lecture 18: Bayesian Statistics (cont.) 1 h 4 min · Video
  17. Lecture 19: Principal Component Analysis 1 h 18 min · Video
  18. Lecture 20: Principal Component Analysis (cont.) 1 h 17 min · Video
  19. Lecture 21: Generalized Linear Models 1 h 16 min · Video
  20. Lecture 22: Generalized Linear Models (cont.) 1 h 18 min · Video
  21. Lecture 23: Generalized Linear Models (cont.) 1 h 19 min · Video
  22. Lecture 24: Generalized Linear Models (cont.) 55 min · Video

Syllabus and materials

At MIT OpenCourseWare, as the course publishes them.

Credits and licence

Institution
Massachusetts Institute of Technology
Department
Mathematics
Teacher
Prof. Philippe Rigollet
Term
Fall 2016
Level
Undergraduate
Language
English
Subjects
Mathematics
Source
MIT OpenCourseWare
Licence
CC BY-NC-SA 4.0, as MIT OpenCourseWare states it. Non-commercial use only. MIT OpenCourseWare's terms
Attribution
Prof. Philippe Rigollet. Statistics for Applications. Fall 2016. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu/. License: Creative Commons BY-NC-SA.
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