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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.

状态:Applied Mathematics
状态:Regression Analysis
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RL

5.0评论日期:Jan 13, 2023

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

ML

5.0评论日期:Jan 30, 2017

Good course on applied linear statistical modeling.

N

5.0评论日期: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.

SM

5.0评论日期: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.

SJ

4.0评论日期:Aug 6, 2020

This course is very powerfull for statistical linear

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