This course is part of From Data To Decision With AI.
This course provides an applied introduction to bivariate and multiple regression with a focus on using generative AI as an analytical partner. Students will learn how to effectively structure research questions, execute regression models with AI assistance, and interpret key statistical outputs including coefficients and R-squared values. The curriculum emphasizes practical applications, teaching students to leverage AI tools for streamlining complex analyses and enhancing prediction accuracy. Through hands-on assignments, learners will develop skills in predicting outcomes from data and clearly communicating insights derived from regression models. The course is particularly valuable for professionals seeking to make data-driven decisions in real-world contexts. Those with limited data analysis experience are advised to first complete the prerequisite courses in the specialization for better preparation.
Instructors:
English
Not specified
What you'll learn
Learn how to structure effective research questions for regression analysis
Use AI tools to conduct bivariate and multiple regression
Interpret regression coefficients and understand their practical meaning
Evaluate model fit using R-squared and other statistical measures
Create and interpret data visualizations for regression results
Communicate regression findings effectively to non-technical audiences
Skills you'll gain
This course includes:
30 Minutes PreRecorded video
4 assignments, 1 peer review
Access on Mobile, Tablet, Desktop
FullTime access
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There is 1 module in this course
This course focuses on applying regression analysis techniques with AI assistance to make accurate predictions from data. Students learn both bivariate and multiple regression approaches, with particular emphasis on using generative AI as a partner to streamline the analytical process. The curriculum covers structuring effective research questions, executing regression models, and interpreting key statistical outputs like coefficients and R-squared values. Through practical applications and guided exercises, learners develop skills in using AI tools to predict outcomes and clearly communicate data-driven insights in real-world contexts. The course is particularly valuable for professionals who need to make evidence-based decisions but may not be statistical experts.
Understanding Bivariate and Multiple Regression
Module 1 · 1 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: From Data To Decision With AI
Instructor
Department Chair, Department of Leadership, Policy, and Organizations
Will Doyle is a professor of public policy and higher education in the department of Leadership, Policy and Organizations at Peabody College of Vanderbilt University. Doyle serves as Editor-in-Chief of Research in Higher Education. His research includes evaluating the impact of higher education policy, the antecedents and outcomes of higher education policy at the state level and the study of political behavior as it affects higher education. Prior to joining the faculty at Vanderbilt, he was Senior Policy Analyst at the National Center for Public Policy and Higher Education. Doyle received a Master’s degree in Political Science and a PhD in Higher Education Administration from Stanford University in 2004. Doyle's recent work has explored the link between geographic opportunity for higher education and its impact on both earnings and civic outcomes. His recent policy-related work has examined the status of college affordability in every sector of higher education in all 50 states.
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Frequently asked questions
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