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:
Advanced Linear Models for Data Science 2: Statistical Linear Models
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Advanced Linear Models for Data Science 2: Statistical Linear Models
This course is part of Advanced Statistics for Data Science Specialization
Instructor: Brian Caffo, PhD
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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
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Shareable certificate
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Assessments
4 assignments
Taught in English
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This course is part of the Advanced Statistics for Data Science Specialization
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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
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4.7 (15 ratings)Offered by
Recommended if you're interested in Probability and Statistics
Johns Hopkins University
Johns Hopkins University
Johns Hopkins University
Johns Hopkins University
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