Be confident your pay structures are fair and competitive by leveraging the power of regression analysis in your compensation work. In just two hours, this course will take the mystery and angst out of regression analysis with a clear, step-by-step approach.
The result: You will be more productive and better able to quickly analyze data and produce valuable insights that lead to better business decisions.
At the end of the class, the Excel spreadsheets used by instructor are yours to keep, along with detailed directions showing how to replicate the functions you’ve learned.
What You Will Learn
- Using linear regression to predict executive pay.
- Using multilinear regression to predict executive pay and test for pay discrimination.
- Using exponential regression to create a base pay policy line and pay scales using market and internal pay data.
- Using regressed data to create an effective scatter chart that combines traditional rectangular pay scales and market and internal median pay lines.
Who Will Benefit from This Course?
This course is ideal for compensation professionals who regularly use Excel to analyze large quantities of data – and who want to work faster and more efficiently.
The course requires an intermediate to advanced knowledge of Excel. Participants also should have access to a computer with Excel 2013 or newer.
This learning experience is part of WorldatWork’s suite of Excel mastery courses, which include:
- Advanced Excel Skills for Compensation Professionals
- Analyzing & Automating Rewards Data with Excel
- Excel Skills for Compensation Professionals
- Dynamic Arrays: Excel Turbo Charged
- Hello Excel Power Query, My New BFF
- Job Titles & Grades: Creating an Interactive Matrix in Excel
- Working Smarter & Faster with Excel Formulas
By successfully completing this course you will earn 2 WorldatWork recertification credits.
View our Return/Cancellation policies and more here.
Contact today to register for this course and take your career to new heights with the latest and expert educational resources.