Learn · Statistics for Applications
Lecture 11 of 22Lecture Videos1 h 22 min
Lecture 12: Testing Goodness of Fit (cont.)
Prof. Philippe Rigollet · Massachusetts Institute of Technology
Credits and licence
- From
- Statistics for Applications, Massachusetts Institute of Technology (at MIT OpenCourseWare)
- Licence
- CC BY-NC-SA 4.0, as MIT OpenCourseWare states it. Non-commercial use only.
- 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.
- Who can watch
- Tweens profiles and older. How courses are placed
All the lectures
- 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.)