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: Statistical Methods
Status: R Programming
AdvancedCourse6 hours

Featured reviews

ML

Reviewed Jan 30, 2017

Good course on applied linear statistical modeling.

N

Reviewed 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.

RL

Reviewed Jan 13, 2023

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

SM

Reviewed 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.

All reviews

Showing: 16 of 16

Sehresh
5.0
Reviewed Apr 3, 2020
Christian
4.0
Reviewed Dec 12, 2020
Ben
3.0
Reviewed May 8, 2022
Ray
5.0
Reviewed Jan 14, 2023
Mark
5.0
Reviewed Jan 31, 2017
Sandeep
4.0
Reviewed Aug 7, 2020
Ian
4.0
Reviewed Aug 22, 2020
Đạt
5.0
Reviewed Oct 12, 2019
Ahmet
5.0
Reviewed Nov 15, 2024
Pawel
5.0
Reviewed Apr 18, 2019
Sergio
5.0
Reviewed Jul 23, 2017
Diana
5.0
Reviewed Oct 14, 2025
wajdi
5.0
Reviewed Jun 6, 2020
SAYANTAN
5.0
Reviewed Jul 27, 2020
RAMAKRISHNA
5.0
Reviewed Jun 30, 2020
Mostofa
3.0
Reviewed Jul 29, 2020