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Recommended experience
What you'll learn
Describe the assumptions of the linear regression models.
Use diagnostic plots to detect violations of the assumptions of a linear regression model.
Perform variable selections and model validations.
Skills you'll gain
Details to know
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There are 3 modules in this course
Welcome to Model Diagnostics and Remediation Measures! In this course, we will cover the topics of: Regression Diagnostics, Variance Stabilizing Transformations, Box-Cox Transformation, Transformations to Linearized the Model, Weighted Least Squares, Autocorrelation, Multicollinearity, Variable Selection and Model Validation. In Module 1, we will cover four topics including: Regression Diagnostics, Variance Stabilizing Transformations, Box-Cox Transformation and Transformations to Linearize the model. There is a lot to read, watch, and consume in this module so, let’s get started!
What's included
9 videos6 readings5 assignments1 discussion prompt
Welcome to Module 2 – This module will cover four topics including: Weighted Least Squares, Autocorrelation, Multicollinearity, and Variable Selection and Model Validation. There is a lot to read, watch, and consume in this module so, let’s get started!
What's included
12 videos6 readings5 assignments
What's included
1 assignment
Instructor
Offered by
Recommended if you're interested in Probability and Statistics
University of Pennsylvania
University at Buffalo
Sungkyunkwan University
Build toward a degree
This course is part of the following degree program(s) offered by Illinois Tech. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
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Frequently asked questions
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