Back to Advanced Linear Models for Data Science 2: Statistical Linear Models
Johns Hopkins University

Advanced Linear Models for Data Science 2: Statistical Linear Models

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.

Status: Probability Distribution
Status: Statistical Analysis
AdvancedCourse6 hours

Featured reviews

RL

5.0Reviewed Jan 13, 2023

Great !!! Learning time and I enjoy the math side of it...

SM

5.0Reviewed Apr 2, 2020

This is a great course from Johns Hopkins University . By taking this course, I improved my Data Management, Statistical Programming, and Statistics skills.

ML

5.0Reviewed Jan 30, 2017

Good course on applied linear statistical modeling.

N

5.0Reviewed Oct 12, 2019

It is a very good course for any statistics to learn and have a sweet tastes of math and its behind functionality on data.

SJ

4.0Reviewed Aug 6, 2020

This course is very powerfull for statistical linear

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