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A free and open online publication of educational material from thousands of MIT courses, covering the entire MIT curriculum, ranging from introductory to the most advanced graduate courses. On the OCW website, each course includes a syllabus, instructional material like notes and reading lists, and learning activities like assignments and solutions. Some courses also have videos, online textbooks, and faculty insights on teaching. Knowledge is your reward. There's no signup or enrollment, and no start or end dates. OCW is self-paced learning at its best. Whether you’re a student, a teacher, or simply a curious person that wants to learn, MIT OpenCourseWare (OCW) offers a wealth of insight, inspiration, videos, and a whole lot more! Get the full picture on the OCW website at https://ocw.mit.edu. Accessibility: https://accessibility.mit.edu/ User comments policy: https://ocw.mit.edu/comments/ (Channel banner photo by Nietnagel on Flickr: https://flic.kr/p/8WXxfK.)
Episodes


Lecture 02: Fundamentals of Probability

Lecture 15: Analyzing Randomized Experiments

Lecture 01: Introduction to 14.310x Data Analysis for Social Scientists

Lecture 05: Summarizing and Describing Data

Lecture 04: Gathering and Collecting Data

Lecture 03: Random Variables, Distributions, and Joint Distributions

Lecture 13. Confidence Intervals, Hypothesis Testing, and Power Calculations

Lecture 20: Omitted Variable Bias

Lecture 17: The Linear Model

Lecture 08: Moments of Distribution

Lecture 09: Expectation, Variance, and Introduction to Regression

Lecture 06: Joint, Marginal, and Conditional Distributions

Lecture 22: Experimental Design

Lecture 10: Special Distributions

Lecture 18: The Multivariate Model

Lecture 18: Discrete Symmetries

Lecture 9: Path Integral Formalism for QFT; Computation of Time-Ordered Correlation Functions

Lecture 11: Computation of Correlation Functions in Perturbation Theory and Feynman Diagrams

Lecture 13: Introducing the Dirac Equation
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