Retour à Advanced Linear Models for Data Science 2: Statistical Linear Models
Avis et commentaires pour d'étudiants pour Advanced Linear Models for Data Science 2: Statistical Linear Models par Université Johns-Hopkins
36 évaluations
À propos du cours
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.
Meilleurs avis
DD
Oct 13, 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.
ML
Jan 31, 2017
Good course on applied linear statistical modeling.
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1 - 4 sur 4 Avis pour Advanced Linear Models for Data Science 2: Statistical Linear Models
par Dat
•Oct 13, 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.
par Mark R L
•Jan 31, 2017
Good course on applied linear statistical modeling.
par Pawel P
•Apr 18, 2019
Very informative and interesting.
par Sergio G
•Jul 23, 2017
Very good... Thanks
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