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Course Description

A simple regression predicts outcomes based on the correlation between two variables; in the real world, however, most decisions are far more complex, often influenced by numerous factors. Multiple regression allows you to consider these additional factors when making decisions. By building on the foundational techniques, you can create a model that more accurately reflects reality, thus enhancing the confidence in your managerial decisions.

In this course, you'll discover how to improve a predictive model by incorporating more variables. You will also use a variety of statistical tools to verify the validity of your model. Additionally, since there might be situations where your system doesn't perfectly fit as you factor in more variables, you will examine how to identify such scenarios and compensate for them when constructing your predictive model. As you introduce multiple regression analysis into your skillset, you will gain a more comprehensive approach to the decision-making process, helping you overcome challenges in your business.

You are required to have completed the following courses or have equivalent experience before taking this course:

  • Data Analysis and Probability
  • Decision Analysis
  • Continuous Distributions
  • Sampling
  • Hypothesis Testing
  • Simple Regression

Faculty Author

David Juran

Benefits to the Learner

  • Improve a predictive model by incorporating more variables
  • Use a variety of statistical tools to verify the validity of your model
  • Adjust your model to handle cases that are nonlinear or non-normal

Target Audience

  • Professionals looking to uncover insights from data
  • Students who are pre-MBA or considering earning an MBA
  • Analysts and researchers
  • Individuals interested in moving into an analyst role
  • Anyone seeking to leverage statistical or analytic skills

Applies Towards the Following Certificates

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Cornell Johnson Graduate School of Management
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