hypothesis
No strong matches for “hypothesis”. Here are the closest videos.
39:49Lec 1 | MIT 18.06 Linear Algebra, Spring 2005
4.9M views • 17 years ago
MIT OpenCourseWare
The first lecture of Gilbert Strang's MIT 18.06 Linear Algebra course, covering the geometry of linear equations. It opens a full 35-lecture university course.
Topic match · Pure mathematics
9:18The Most IMPORTANT Video You'll Ever See (part 1 of 8)
5.4M views • 19 years ago
wonderingmind42
Part 1 of a lecture by physicist Albert Bartlett on the exponential function and its consequences for population growth, resource use and energy. It argues that steady growth rates quickly lead to enormous quantities.
Topic match · Pure mathematics
6:42Carl Sagan - Cosmos - Eratosthenes
3M views • 17 years ago
carlsagandotcom
A short clip from Carl Sagan's Cosmos in which he explains how Eratosthenes measured the circumference of the Earth using shadows in two Egyptian cities. It is a clear, visual account of an ancient scientific feat.
Topic match · Pure mathematics
7:24Cosmos - Carl Sagan - 4th Dimension
5.4M views • 17 years ago
carlsagandotcom
A segment from Carl Sagan's original Cosmos explaining the fourth spatial dimension through analogy with a two-dimensional world and shadow projection.
Topic match · Pure mathematics
1:20:33Lecture 1 | Convex Optimization I (Stanford)
753K views • 18 years ago
Stanford
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.
Topic match · Pure mathematics
1:12:10Practical Common Lisp
98K views • 19 years ago
Google TechTalks
Peter Seibel's 2006 Google TechTalk on Practical Common Lisp, framed by the Sapir-Whorf hypothesis and Paul Graham's Blub paradox. It shows Lisp features such as condition restarts and its generic-function object system.
9:36Dance p 3 Mar09
83K views • 17 years ago
Geoff Cumming
Geoff Cumming uses a simulation to show how wildly the p value varies from one replication to the next because of sampling variability. He argues for estimation and confidence intervals over null hypothesis significance testing.