Statistics for Applications | Mathematics | MIT OpenCourseWare

Course Info

Instructor

Prof. Philippe Rigollet

Departments

Mathematics

As Taught In

Fall 2016

Level

Undergraduate

Topics

Mathematics
- Probability and Statistics

Learning Resource Types

Lecture Notes

Lecture Videos

Problem Sets

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Lecture Videos

Lecture 1: Introduction to Statistics

Lecture 2: Introduction to Statistics (cont.)

Lecture 3: Parametric Inference

Lecture 4: Parametric Inference (cont.) and Maximum Likelihood Estimation

Lecture 5: Maximum Likelihood Estimation (cont.)

Lecture 6: Maximum Likelihood Estimation (cont.) and the Method of Moments

Lecture 7: Parametric Hypothesis Testing

Lecture 8: Parametric Hypothesis Testing (cont.)

Lecture 9: Parametric Hypothesis Testing (cont.)

Lecture 11: Parametric Hypothesis Testing (cont.) and Testing Goodness of Fit

Lecture 12: Testing Goodness of Fit (cont.)

Lecture 13: Regression

Lecture 14: Regression (cont.)

Lecture 15: Regression (cont.)

Lecture 17: Bayesian Statistics

Lecture 18: Bayesian Statistics (cont.)

Lecture 19: Principal Component Analysis

Lecture 20: Principal Component Analysis (cont.)

Lecture 21: Generalized Linear Models

Lecture 22: Generalized Linear Models (cont.)

Lecture 23: Generalized Linear Models (cont.)

Lecture 24: Generalized Linear Models (cont.)

Course Info

Instructor

Prof. Philippe Rigollet

Departments

Mathematics

As Taught In

Fall 2016

Level

Undergraduate

Topics

Mathematics
- Probability and Statistics

Learning Resource Types

Lecture Notes

Lecture Videos

Problem Sets

Download Course

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