This course is part of the Advanced Statistics for Data Science Specialization

4.4
stars
168 ratings

Brian Caffo, PhD

26,488 already enrolled

Offered By

Advanced Statistics for Data Science SpecializationJohns Hopkins University

About this Course

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Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. 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.

Flexible deadlines

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Earn a Certificate upon completion

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Course 3 of 4 in the

Advanced Statistics for Data Science Specialization

Advanced Level

Approx. 8 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish

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Skills you will gain

Statistics
Linear Regression
R Programming
Linear Algebra

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 3 of 4 in the

Advanced Statistics for Data Science Specialization

Advanced Level

Approx. 8 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.57/5 (15 Ratings)

Brian Caffo, PhD

Professor, Biostatistics

Bloomberg School of Public Health

1,488,810 Learners

30 Courses

Offered by

Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

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Syllabus - What you will learn from this course

Week

Week 1

2 hours to complete

Background

We cover some basic matrix algebra results that we will need throughout the class. This includes some basic vector derivatives. In addition, we cover some some basic uses of matrices to create summary statistics from data. This includes calculating and subtracting means from observations (centering) as well as calculating the variance.

2 hours to complete

7 videos (Total 28 min), 4 readings, 1 quiz

Week

Week 2

1 hour to complete

One and two parameter regression

In this module, we cover the basics of regression through the origin and linear regression. Regression through the origin is an interesting case, as one can build up all of multivariate regression with it.

1 hour to complete

6 videos (Total 29 min), 2 readings, 1 quiz

Week

Week 3

1 hour to complete

Linear regression

In this lecture, we focus on linear regression, the most standard technique for investigating unconfounded linear relationships.

1 hour to complete

8 videos (Total 23 min), 2 readings, 1 quiz

Week

Week 4

1 hour to complete

General least squares

We now move on to general least squares where an arbitrary full rank design matrix is fit to a vector outcome.

1 hour to complete

6 videos (Total 39 min), 1 reading, 1 quiz

Reviews

4.4

41 reviews

5 stars
60.23%
4 stars
26.90%
3 stars
8.18%
2 stars
3.50%
1 star
1.16%

TOP REVIEWS FROM ADVANCED LINEAR MODELS FOR DATA SCIENCE 1: LEAST SQUARES

by JASep 8, 2020

This is an excellent course that enabled me to understand how multiple regression in linear models works behind the hood. The practical examples shown by the professor were very helpful. Thank you

by DJApr 22, 2017

A wonderful course to study! Prof. Brian Caffo explains so well!

by CLApr 29, 2020

The course is interesting; but is more theoretical in nature than applied.

by JMMay 8, 2017

Good course. Quite hard. Linear algebra should be your second language as it is assumed to be mastered. Exams should include some personal work.

View all reviews

About the Advanced Statistics for Data Science Specialization

Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression.

This specialization starts with Mathematical Statistics bootcamps, specifically concepts and methods used in biostatistics applications. These range from probability, distribution, and likelihood concepts to hypothesis testing and case-control sampling. This specialization also linear models for data science, starting from understanding least squares from a linear algebraic and mathematical perspective, to statistical linear models, including multivariate regression using the R programming language. These courses will give learners a firm foundation in the linear algebraic treatment of regression modeling, which will greatly augment applied data scientists' general understanding of regression models. This specialization requires a fair amount of mathematical sophistication. Basic calculus and linear algebra are required to engage in the content.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Advanced Linear Models for Data Science 1: Least Squares

About this Course

Skills you will gain