Johns Hopkins University
Advanced Linear Models for Data Science 2: Statistical Linear Models
Johns Hopkins University

Advanced Linear Models for Data Science 2: Statistical Linear Models

Brian Caffo, PhD

Instructor: Brian Caffo, PhD

23,526 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.5

(96 reviews)

Advanced level
Designed for those already in the industry
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.5

(96 reviews)

Advanced level
Designed for those already in the industry
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace

Details to know

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Assessments

4 assignments

Taught in English

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There are 4 modules in this course

In this module, we cover the basics of the course as well as the prerequisites. We then cover the basics of expected values for multivariate vectors. We conclude with the moment properties of the ordinary least squares estimates.

What's included

7 videos3 readings1 assignment

In this module, we build up the multivariate and singular normal distribution by starting with iid normals.

What's included

4 videos2 readings1 assignment

In this module, we build the basic distributional results that we see in multivariable regression.

What's included

8 videos1 reading1 assignment

In this module we will revisit residuals and consider their distributional results. We also consider the so-called PRESS residuals and show how they can be calculated without re-fitting the model.

What's included

4 videos2 readings1 assignment

Instructor

Instructor ratings
4.7 (15 ratings)
Brian Caffo, PhD
Johns Hopkins University
30 Courses1,637,887 learners

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Recommended if you're interested in Probability and Statistics

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4.5

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RL
5

Reviewed on Jan 13, 2023

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Reviewed on Apr 2, 2020

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Reviewed on Jan 30, 2017

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