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Advanced Linear Models for Data Science 2: Statistical Linear Models

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Course Description

Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following:- A basic understanding of linear algebra and multivariate calculus.- A basic understanding of statistics and regression models.- At least a little familiarity with proof based mathematics.- Basic knowledge of the R programming language.After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling. This will greatly augment applied data scientists' general understanding of regression models.

Time: 10h

Instructor Details

Brian Caffo

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Brian Caffo, PhD is a professor in the Department of statistics at the Johns Hopkins University Bloomberg School of Public Health. He graduated from the Department of Statistics at the University of Florida in 2001. He works in the fields of computational statistics and neuroinformatics and co-created the SMART ( www.smart-stats.org) working group. He has been the recipient of the Presidential Early Career Award for Scientist ( PECASE) and Engineers and Bloomberg School of Public Health Golden Apple and AMTRA teaching awards.