Вернуться к Advanced Linear Models for Data Science 2: Statistical Linear Models

4.5
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Оценки: 79

## О курсе

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....

## Лучшие рецензии

SM

2 апр. 2020 г.

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

PP

12 окт. 2019 г.

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

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## 1–13 из 13 отзывов о курсе Advanced Linear Models for Data Science 2: Statistical Linear Models

автор: Sehresh M

3 апр. 2020 г.

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

автор: Mark L

31 янв. 2017 г.

Good course on applied linear statistical modeling.

автор: Christian J H

12 дек. 2020 г.

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.

автор: Ben R

8 мая 2022 г.

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.

автор: Đạt N

12 окт. 2019 г.

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

автор: Pawel P

18 апр. 2019 г.

Very informative and interesting.

автор: Sergio G

23 июля 2017 г.

Very good... Thanks

автор: wajdi a

6 июня 2020 г.

thanks u all

автор: SAYANTAN D

27 июля 2020 г.

Enjoyable

автор: RAMAKRISHNA R

30 июня 2020 г.

Very good

автор: Sandeep J

7 авг. 2020 г.

This course is very powerfull for statistical linear

автор: Ian K

22 авг. 2020 г.

A very challenging and deeply insightful course.

автор: Mostofa K

29 июля 2020 г.

good