This course focuses on the problem of supervised learning from the perspective …
This course focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. It develops basic tools such as Regularization including Support Vector Machines for regression and classification. It derives generalization bounds using both stability and VC theory. It also discusses topics such as boosting and feature selection and examines applications in several areas: Computer Vision, Computer Graphics, Text Classification and Bioinformatics. The final projects and hands-on applications and exercises are planned, paralleling the rapidly increasing practical uses of the techniques described in the subject.
Statistical Mechanics is a probabilistic approach to equilibrium properties of large numbers …
Statistical Mechanics is a probabilistic approach to equilibrium properties of large numbers of degrees of freedom. In this two-semester course, basic principles are examined. Topics include: thermodynamics, probability theory, kinetic theory, classical statistical mechanics, interacting systems, quantum statistical mechanics, and identical particles.
This course discusses the principles and methods of statistical mechanics. Topics covered …
This course discusses the principles and methods of statistical mechanics. Topics covered include classical and quantum statistics, grand ensembles, fluctuations, molecular distribution functions, other concepts in equilibrium statistical mechanics, and topics in thermodynamics and statistical mechanics of irreversible processes.
This course is an introduction to statistical data analysis. Topics are chosen …
This course is an introduction to statistical data analysis. Topics are chosen from applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and nonparametric statistics.
Statistical thinking is a way of understanding a complex world by describing …
Statistical thinking is a way of understanding a complex world by describing it in relatively simple terms that nonetheless capture essential aspects of its structure, and that also provide us some idea of how uncertain we are about our knowledge. The foundations of statistical thinking come primarily from mathematics and statistics, but also from computer science, psychology, and other fields of study.
This 13-minute video lesson provides analysis of variance 2: Calculating SSW and …
This 13-minute video lesson provides analysis of variance 2: Calculating SSW and SSB (total sum of squares within and between). [Statistics playlist: Lesson 76 of 85]
This 12-minute video lesson plays with the formula for variance of a …
This 12-minute video lesson plays with the formula for variance of a population. And looks at alternate variance formulas. [Statistics playlist: Lesson 16 of 85]
This 8-minute video lesson takes problems from CK12.org to discuss using the …
This 8-minute video lesson takes problems from CK12.org to discuss using the Empirical Rule with a standard normal distribution. [Statistics playlist: Lesson 33 of 85]
This 10-minute video lesson takes some problems from CK12.org and uses the …
This 10-minute video lesson takes some problems from CK12.org and uses the empirical rule (or 68-95-99.7 rule) to estimate probabilities for normal distributions. [Statistics playlist: Lesson 32 of 85]
This 11-minute video lesson takes some problems from CK12.org and discusses of …
This 11-minute video lesson takes some problems from CK12.org and discusses of how "normal" a distribution might be. [Statistics playlist: Lesson 30 of 85]
This 3-minute video lesson provides clarification of the previous video on the …
This 3-minute video lesson provides clarification of the previous video on the confidence interval for difference of means. [Statistics playlist: Lesson 57 of 85]
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