Elementary Probability
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Note: This course is offered by Stanford as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development. This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric...more
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Note: This course is being offered this summer by Stanford as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development. The goals for the course are to gain a facility with using the Fourier transform, both specific techniques and general principles, and learning to recognize when, why, and how it is used....more
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Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.
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Basic probability. Should have a reasonable grounding in basic algebra before watching.
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This is a math course aimed at students with life science majors covering elementary probability, probability distributions, random variables, and limit theorems.
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We first play and then analyze wars of attrition; the games that afflict trench warfare, strikes, and businesses in some competitive settings. We find long and damaging fights can occur in class in these games even when the prizes are small in relation to the accumulated costs. These could be caused by irrationality or by players' having other goals like pride or reputation. But we argue that long, costly fights should be expected in...more
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Insurance provides significant risk management to a broad public, and is an essential tool for promoting human welfare. By pooling large numbers of independent or low-correlated risks, insurance providers can minimize overall risk. The risk management is tailored to individual circumstances and reflects centuries of insurance industry experience with real risks and with moral hazard and selection bias issues. Probability theory and...more
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Professor McBride expands on the recently introduced concept of the wave function by illustrating the relationship of the magnitude of the curvature of the wave function to the kinetic energy of the system, as well as the relationship of the square of the wave function to the electron probability density. The requirement that the wave function not diverge in areas of negative kinetic energy leads to only certain energies being allowed, a...more
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Central Limit Theorem And Convolution; Main Idea, Introduction, Normalization Of The Gaussian, The Gaussian In Probability; Pictorial Demonstration With Convolution, The Setup For The CLT, Key Result: Distribution Of Sums And Convolution (With Proof), Other Assumptions Needed To Set Up CLT, Statement Of The Central Limit Theorem, Using The Fourier Transform To Prove The CLT
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Professor Sylvia Ceyer focuses on p-orbitals, describing nodal planes, angular nodes, and radial probability distributions. The conversation continues forward to wavefunctions for multielectron atoms, beginning with an explanation of electron configuration. The Pauli and spin exclusion principle is covered, and the lecture concludes with a discussion of one electron wavefunctions for multielectron atoms.
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March 30, 2009 - Leonard Susskind discusses the study of statistical analysis as calculating the probability of things subject to the constraints of a conserved quantity. Susskind introduces energy, entropy, temperature, and phase states as they relate directly to statistical mechanics.
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The Tree of Life must be discovered through rigorous analysis. Genetic information is crucial because appearances can be deceiving, and species that look similar can prove to be genetically very dissimilar and not share recent common ancestors. Two criteria, used to determine what the "correct" Tree is, are simplicity and whether the tree maximizes the probability of observing what we actually see.
