4.5
78 个评分
13 条评论

## 课程概述

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....

## 热门审阅

SM

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.

PP

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.

## 1 - Advanced Linear Models for Data Science 2: Statistical Linear Models 的 13 个评论（共 13 个）

Apr 3, 2020

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

Jan 31, 2017

Good course on applied linear statistical modeling.

Dec 12, 2020

I love the deep dive into understanding the math, particularly the vector and matrix algebra, going on underneath the hood. However, I would've loved further examples that kept bringing things back around to how these things can be used in real world scenarios (i.e., biological and other scientific studies). There's a fine line between proofs providing valuable insight vs. proofs being purely academic, and this course may've flirted a bit too much with the latter to be as useful as it could've been.

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.

Apr 18, 2019

Very informative and interesting.

Jul 23, 2017

Very good... Thanks

Jun 6, 2020

thanks u all

Jul 27, 2020

Enjoyable

Jun 30, 2020

Very good

Aug 7, 2020

This course is very powerfull for statistical linear

Aug 22, 2020

A very challenging and deeply insightful course.

May 8, 2022

L​ectures are too esoteric without enough application. There are a couple references to follow-on courses that would hopefully have some "so what" material... But no sign of this so far, and it's been 5 years.

Jul 29, 2020

good