Stanford Online · Education

Stanford Online

You can gain access to a world of education through Stanford Online, the Stanford School of Engineering’s portal for academic and professional education offered by schools and units throughout Stanford University. https://online.stanford.edu/ Our robust catalog of degree programs, credit-bearing education, professional certificate programs, and free and open content is developed by Stanford faculty, enabling you to expand your knowledge, advance your career, and enhance your life. Stanford Online is operated and managed by the Stanford Engineering Center for Global & Online Education (CGOE). CGOE expands access to Stanford teaching and research, working in collaboration with faculty in the School of Engineering and throughout Stanford University to design and deliver extensive global, online, and enterprise education to a global audience.

Stanford Online

Episodes

Statistical Learning: 4.7 Gaussian Discriminant Analysis (Many Variables)

Statistical Learning: 4.6 Gaussian Discriminant Analysis (One Variable)

Statistical Learning: 4.5 Discriminant Analysis

Statistical Learning: 4.4 Logistic Regression Case Control Sampling and Multiclass

Statistical Learning: 4.3 Multivariate Logistic Regression

Statistical Learning: 4.2 Logistic Regression

Statistical Learning: 4.1 Introduction to Classification Problems

Statistical Learning: 3.R Regression in R

Statistical Learning: 3.5 Extensions of the Linear Model

Statistical Learning: 3.4 Some important questions

Statistical Learning: 3.3 Multiple Linear Regression

Statistical Learning: 3.2 Hypothesis Testing and Confidence Intervals

Statistical Learning: 3.1 Simple linear regression

Statistical Learning: 2.R Introduction to R

Statistical Learning: 2.4 Classification

Statistical Learning: 2.3 Model Selection and Bias Variance Tradeoff

Statistical Learning: 2.2 Dimensionality and Structured Models

Statistical Learning: 2.1 Introduction to Regression Models

Statistical Learning: 1.2 Examples and Framework

Statistical Learning: 1.1 Opening Remarks