About this Course
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100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 10 hours to complete

Suggested: 6 weeks of study, 1-2 hours/week...

English

Subtitles: English
User
Learners taking this Course are
  • Researchers
  • Data Scientists
  • Economists
  • Data Analysts
  • Machine Learning Engineers
User
Learners taking this Course are
  • Researchers
  • Data Scientists
  • Economists
  • Data Analysts
  • Machine Learning Engineers

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 10 hours to complete

Suggested: 6 weeks of study, 1-2 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Introduction and expected values

7 videos (Total 38 min), 3 readings, 1 quiz
7 videos
Multivariate expected values, the basics4m
Expected values, matrix operations2m
Multivariate variances and covariances5m
Multivariate covariance and variance matrix operations5m
Expected values of quadratic forms3m
Expected value properties of least squares estimates13m
3 readings
Welcome to the class10m
Course textbook10m
Introduction to expected values10m
1 practice exercise
Expected Values30m
Week
2
1 hour to complete

The multivariate normal distribution

4 videos (Total 31 min), 2 readings, 1 quiz
4 videos
The singular normal distribution7m
Normal likelihoods5m
Normal conditional distributions8m
2 readings
Introduction to the multivariate normal10m
A note on the last quiz question.10m
1 practice exercise
the multivariate normal20m
Week
3
1 hour to complete

Distributional results

8 videos (Total 60 min), 1 reading, 1 quiz
8 videos
Confidence intervals for regression coefficients6m
F distribution4m
Coding example7m
Prediction intervals11m
Coding example5m
Confidence ellipsoids7m
Coding example6m
1 reading
Distributional results10m
1 practice exercise
Distributional results20m
Week
4
1 hour to complete

Residuals

4 videos (Total 32 min), 2 readings, 1 quiz
4 videos
Code demonstration3m
Leave one out residuals8m
Press residuals14m
2 readings
Residuals10m
Thanks for taking the course10m
1 practice exercise
Residuals14m
4.8
4 ReviewsChevron Right

Top reviews from Advanced Linear Models for Data Science 2: Statistical Linear Models

By DDOct 13th 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.

By MLJan 31st 2017

Good course on applied linear statistical modeling.

Instructor

Avatar

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

About 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....

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, 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.

More questions? Visit the Learner Help Center.