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Learner Reviews & Feedback for Model Diagnostics and Remedial Measures by Illinois Tech
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About the Course
This course is best suited for individuals who have a technical background in mathematics/statistics/computer science/engineering pursuing a career change to jobs or industries that are data-driven such as finance, retain, tech, healthcare, government and many more. The opportunity is endless.
This course is part of the Performance Based Admission courses for the Data Science program.
In this course, we will learn what happens to our regression model when these assumptions have not been met. How can we detect these discrepancies in model assumptions and how do we remediate the problems will be addressed in this course.
Upon successful completion of this course, you will be able to:
-describe the assumptions of the linear regression models.
-use diagnostic plots to detect violations of the assumptions of a linear regression model.
-perform a transformation of variables in building regression models.
-use suitable tools to detect and remove heteroscedastic errors.
-use suitable tools to remediate autocorrelation.
-use suitable tools to remediate collinear data.
-perform variable selections and model validations.
Top reviews
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1 - 2 of 2 Reviews for Model Diagnostics and Remedial Measures
By Zakariya B
•Jul 17, 2025
very interesting contents and the lecture make them easier to grasp
By Zixiang Z
•Oct 12, 2024
The teaching professor was very good.