Learn · Introduction to Computational Thinking and Data Science
Lecture 10 of 15Lecture Videos51 min
Lecture 10: Understanding Experimental Data (cont.)
Prof. Eric Grimson, Prof. John Guttag and Dr. Ana Bell · Massachusetts Institute of Technology
Credits and licence
- From
- Introduction to Computational Thinking and Data Science, 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. Eric Grimson, Prof. John Guttag, Dr. Ana Bell. Introduction to Computational Thinking and Data Science. 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 and Optimization Problems
- Lecture 2: Optimization Problems
- Lecture 3: Graph-theoretic Models
- Lecture 4: Stochastic Thinking
- Lecture 5: Random Walks
- Lecture 6: Monte Carlo Simulation
- Lecture 7: Confidence Intervals
- Lecture 8: Sampling and Standard Error
- Lecture 9: Understanding Experimental Data
- Lecture 10: Understanding Experimental Data (cont.)
- Lecture 11: Introduction to Machine Learning
- Lecture 12: Clustering
- Lecture 13: Classification
- Lecture 14: Classification and Statistical Sins
- Lecture 15: Statistical Sins and Wrap Up