About this Course

11,936 recent views
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level
Approx. 5 hours to complete
English
Subtitles: English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level
Approx. 5 hours to complete
English
Subtitles: English

Offered by

Johns Hopkins University logo

Johns Hopkins University

Syllabus - What you will learn from this course

Week
1

Week 1

2 hours to complete

Introduction and expected values

2 hours to complete
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

Week 2

1 hour to complete

The multivariate normal distribution

1 hour to complete
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

Week 3

1 hour to complete

Distributional results

1 hour to complete
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

Week 4

1 hour to complete

Residuals

1 hour to complete
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

Reviews

TOP REVIEWS FROM ADVANCED LINEAR MODELS FOR DATA SCIENCE 2: STATISTICAL LINEAR MODELS

View all reviews

Frequently Asked Questions

  • 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.
  • 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.

  • You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

More questions? Visit the Learner Help Center.