scientific method

A short clip of Richard Feynman explaining the scientific method: guess, compute consequences, compare to experiment, and why vague theories like astrology cannot be proven wrong.

A one-minute clip of Richard Feynman describing the scientific method: guess a law, compute its consequences, and compare with experiment. If it disagrees with experiment, it is wrong.

A two-minute clip of Richard Feynman on the social sciences, discussing what counts as real science versus pseudo science.

A short clip of Richard Feynman on the difference between merely knowing how to reason mathematically and understanding why physical theories work. He discusses holding multiple equivalent ideas and guessing new laws.

A three-minute clip of Richard Feynman using the rules of chess as an analogy for how science works, discovering rules by observation and sometimes meeting surprises like castling. It touches on incremental progress versus revolutions.

Noam Chomsky's 2011 University of Oslo lecture on Newton's contributions to the study of mind. He argues Newton abandoned mechanical explanation and lowered the bar for scientific intelligibility, with consequences for the limits of human understanding. Q&A starts at 45:33.

Richard Hamming's 1995 recording of his talk 'You and Your Research', drawn from his graduate engineering course. He discusses how great scientists pick important problems and build careers, drawing on his years at Bell Labs.

Sean Carroll introduces his video series on the biggest ideas in physics, such as symmetry, space and matter, as informal discussions with follow-up Q&A videos. This is the short opening video of the series.

Sean Carroll gives a Royal Institution talk tracing the history of quantum mechanics from Einstein and Bohr to today. He covers the Copenhagen interpretation and the many worlds interpretation.

Bill Hammack of engineerguy introduces his series on Michael Faraday's lectures on The Chemical History of a Candle. He describes the free companion book and the commentary and caption features that help modern viewers.

The final lecture of Richard Hamming's Learning to Learn course, from 1995, based on his well-known talk 'You and Your Research'. It covers how to do important work and build a career.

The introductory lecture of Richard Hamming's capstone course, The Art of Doing Science and Engineering: Learning to Learn. It focuses on style of thinking and on educating rather than training, using technical material only as illustration.

Psychologist Irving Kirsch gives a distinguished lecture on antidepressant trials and the placebo effect. He argues drug-placebo differences are small outside severe depression.

First lecture of Stanford's CS106A Programming Methodology by Mehran Sahami, giving a course overview and starting on programming. The course teaches software engineering principles using Java.

A one-minute clip from Richard Feynman's 1979 Auckland lecture in which he answers whether you see an object or only its light. It is a short, playful take on perception and on the use of philosophy.

A clip of Richard Feynman contrasting the Greek and Babylonian traditions of mathematical reasoning. It compares the axiomatic approach of mathematicians with how physicists use mathematics.

Hans Rosling uses data and animated statistics to show how world population is changing, why birth rates fall as child survival and wealth rise, and why population is expected to peak around 11 billion. It also tackles common misconceptions about Africa and family planning.

Database pioneer Michael Stonebraker argues that 'big data' is really at least four different problems: big volumes with small analytics, big analytics, velocity, and variety. He comments on where each market is heading.

Michael Betancourt's lecture at MLSS Iceland 2014 on efficient Bayesian inference with Hamiltonian Monte Carlo. It covers MCMC concepts and motivation and the problems of sampling in high-dimensional distributions.

Peter Norvig's UBC distinguished lecture on how massive amounts of simple data, such as for language modeling, can yield understanding that hand-built models could not.

Matt Parker's LMS popular lecture on how seemingly incredible results can be meaningless random patterns. He ranges from ancient Woolworths civilisations to shoelaces and DNA.

Douglas Hofstadter lectures at Uppsala University on how analogy and daring thinking drove Einstein's discovery of light quanta. He argues deep insight in physics comes from imaginative leaps rather than rigid logic.

The first lecture of MIT 6.042J Mathematics for Computer Science, taught by Tom Leighton, introducing mathematical proofs. It covers propositions, implication and basic proof methods.

Terence Tao's AMS Einstein Public Lecture at UCLA on the cosmic distance ladder, the chain of methods astronomers use to measure distances from the Earth to distant galaxies. It is aimed at a general audience.

The introductory lecture of Stephen Boyd's Stanford Convex Optimization I course (EE 364A). It outlines convex sets, functions and problems, and the course's coverage of least-squares, linear and semidefinite programming, duality and interior-point methods.

A 15-minute clip of linguist Stephen Krashen discussing language acquisition, drawn from the 1980s. It presents his input hypothesis and the distinction between acquisition and learning.